From 1799633091a3adcc6658063a8dc21f2bbc27e657 Mon Sep 17 00:00:00 2001 From: jazelly Date: Sat, 20 Apr 2024 13:26:27 +0930 Subject: [PATCH 01/96] feat: llama2 7b with qlora --- finetune_llama2_7b_qlora.ipynb | 1008 ++++++++++++++++++++++++++++++++ 1 file changed, 1008 insertions(+) create mode 100644 finetune_llama2_7b_qlora.ipynb diff --git a/finetune_llama2_7b_qlora.ipynb b/finetune_llama2_7b_qlora.ipynb new file mode 100644 index 0000000..c484134 --- /dev/null +++ b/finetune_llama2_7b_qlora.ipynb @@ -0,0 +1,1008 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "7822dbb1-f25f-40ff-930a-9a0ec065fc01", + "metadata": {}, + "source": [ + "# Fintune LLaMa-2 7B Chat model with QLoRA\n", + "\n", + "In this example, we are going to explore how to use SFT (Supervised Fine-tuning) to train LLaMa-2 7B model. To drastically reduce the VRAM usage, we must fine-tune the model in 4-bit precision, which is why we’ll use QLoRA here.\n", + "\n", + "As a result, this example perfectly runs on a RTX 3080 with only 10G VRAM, with the help of QLoRA.\n", + "\n", + "## Setup\n", + "\n", + "Make sure you have the following requirements\n", + "```\n", + "bitsandbytes==0.40.2\n", + "accelerate==0.21.0\n", + "peft==0.4.0\n", + "trl==0.4.7\n", + "datasets==2.17.0\n", + "transformers==4.31.0\n", + "```\n", + "Of course, as usual, you will need `torch` and `torchvision`" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "bc9cfbfa-9073-48b0-b7cf-301ca22d7c49", + "metadata": {}, + "outputs": [], + "source": [ + "import os\n", + "import torch\n", + "from datasets import load_dataset\n", + "from transformers import (\n", + " AutoModelForCausalLM,\n", + " AutoTokenizer,\n", + " BitsAndBytesConfig,\n", + " HfArgumentParser,\n", + " TrainingArguments,\n", + " pipeline,\n", + " logging,\n", + ")\n", + "from peft import LoraConfig, PeftModel\n", + "from trl import SFTTrainer\n", + "\n", + "# The model that you want to train from the Hugging Face hub\n", + "model_name = \"NousResearch/llama-2-7b-chat-hf\"\n", + "\n", + "# The instruction dataset to use\n", + "dataset_name = \"AdiOO7/llama-2-finance\"\n", + "\n", + "# Fine-tuned model name\n", + "new_model = \"llama-2-7b-test-finance\"\n", + "\n", + "################################################################################\n", + "# QLoRA parameters\n", + "################################################################################\n", + "\n", + "# LoRA attention dimension\n", + "lora_r = 64\n", + "\n", + "# Alpha parameter for LoRA scaling\n", + "lora_alpha = 16\n", + "\n", + "# Dropout probability for LoRA layers\n", + "lora_dropout = 0.1\n", + "\n", + "################################################################################\n", + "# bitsandbytes parameters\n", + "################################################################################\n", + "\n", + "# Activate 4-bit precision base model loading\n", + "use_4bit = True\n", + "\n", + "# Compute dtype for 4-bit base models\n", + "bnb_4bit_compute_dtype = \"float16\"\n", + "\n", + "# Quantization type (fp4 or nf4)\n", + "bnb_4bit_quant_type = \"nf4\"\n", + "\n", + "# Activate nested quantization for 4-bit base models (double quantization)\n", + "use_nested_quant = False\n", + "\n", + "################################################################################\n", + "# TrainingArguments parameters\n", + "################################################################################\n", + "\n", + "# Output directory where the model predictions and checkpoints will be stored\n", + "output_dir = \"./results\"\n", + "\n", + "# Number of training epochs\n", + "num_train_epochs = 1\n", + "\n", + "# Enable fp16/bf16 training (set bf16 to True with an A100)\n", + "fp16 = False\n", + "bf16 = False\n", + "\n", + "# Batch size per GPU for training\n", + "per_device_train_batch_size = 4\n", + "\n", + "# Batch size per GPU for evaluation\n", + "per_device_eval_batch_size = 4\n", + "\n", + "# Number of update steps to accumulate the gradients for\n", + "gradient_accumulation_steps = 1\n", + "\n", + "# Enable gradient checkpointing\n", + "gradient_checkpointing = True\n", + "\n", + "# Maximum gradient normal (gradient clipping)\n", + "max_grad_norm = 0.3\n", + "\n", + "# Initial learning rate (AdamW optimizer)\n", + "learning_rate = 2e-4\n", + "\n", + "# Weight decay to apply to all layers except bias/LayerNorm weights\n", + "weight_decay = 0.001\n", + "\n", + "# Optimizer to use\n", + "optim = \"paged_adamw_32bit\"\n", + "\n", + "# Learning rate schedule (constant a bit better than cosine)\n", + "lr_scheduler_type = \"constant\"\n", + "\n", + "# Number of training steps (overrides num_train_epochs)\n", + "max_steps = -1\n", + "\n", + "# Ratio of steps for a linear warmup (from 0 to learning rate)\n", + "warmup_ratio = 0.03\n", + "\n", + "# Group sequences into batches with same length\n", + "# Saves memory and speeds up training considerably\n", + "group_by_length = True\n", + "\n", + "# Save checkpoint every X updates steps\n", + "save_steps = 25\n", + "\n", + "# Log every X updates steps\n", + "logging_steps = 25\n", + "\n", + "################################################################################\n", + "# SFT parameters\n", + "################################################################################\n", + "\n", + "# Maximum sequence length to use\n", + "max_seq_length = None\n", + "\n", + "# Pack multiple short examples in the same input sequence to increase efficiency\n", + "packing = False\n", + "\n", + "# Load the entire model on the GPU 0\n", + "device_map = {\"\": 0}" + ] + }, + { + "cell_type": "markdown", + "id": "71b2717a-c046-4938-b7cb-06d029d6e34f", + "metadata": {}, + "source": [ + "## Configure `bitsandbytes` for 4-bit quantization" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "e490c5db-148c-4931-9581-f24265075399", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "loading model - this gonna take some time for the first timer\n" + ] + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "d9f2d4954cb04a4c837797238cd68cff", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Loading checkpoint shards: 0%| | 0/2 [00:00= 8:\n", + " print(\"=\" * 80)\n", + " print(\"Your GPU supports bfloat16: accelerate training with bf16=True\")\n", + " print(\"=\" * 80)\n", + "\n", + "\n", + "# Load LLaMA tokenizer\n", + "tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)\n", + "tokenizer.pad_token = tokenizer.eos_token\n", + "tokenizer.padding_side = \"right\" # Fix weird overflow issue with fp16 training" + ] + }, + { + "cell_type": "markdown", + "id": "2ce034e8-1471-4555-99f8-b7ea223e295c", + "metadata": {}, + "source": [ + "## Peft parameters\n", + "\n", + "Traditional fine-tuning of pre-trained language models (PLMs) requires updating all of the model's parameters, which is computationally expensive and requires massive amounts of data.\n", + "\n", + "Parameter-Efficient Fine-Tuning (PEFT) works by only updating a small subset of the model's most influential parameters, making it much more efficient. Learn about parameters by reading the PEFT official [doc](https://huggingface.co/docs/peft/main/en/conceptual_guides/lora)." + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "67961adc-91ce-4da6-9385-8312a052f72f", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Load LoRA configuration\n" + ] + } + ], + "source": [ + "print('Load LoRA configuration')\n", + "peft_config = LoraConfig(\n", + " lora_alpha=lora_alpha,\n", + " lora_dropout=lora_dropout,\n", + " r=lora_r,\n", + " bias=\"none\",\n", + " task_type=\"CAUSAL_LM\",\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "d7cb8d39-c59d-4e79-aa4f-2f7e52f18e10", + "metadata": {}, + "source": [ + "## Traning parameters\n", + "\n", + "Below is a list of hyperparameters that can be used to optimize the training process:\n", + "\n", + "- output_dir: The output directory is where the model predictions and checkpoints will be stored.\n", + "- num_train_epochs: One training epoch.\n", + "- fp16/bf16: Disable fp16/bf16 training.\n", + "- per_device_train_batch_size: Batch size per GPU for training.\n", + "- per_device_eval_batch_size: Batch size per GPU for evaluation.\n", + "- gradient_accumulation_steps: This refers to the number of steps required to accumulate the gradients during the update process.\n", + "- gradient_checkpointing: Enabling gradient checkpointing.\n", + "- max_grad_norm: Gradient clipping.\n", + "- learning_rate: Initial learning rate.\n", + "- weight_decay: Weight decay is applied to all layers except bias/LayerNorm weights.\n", + "- Optim: Model optimizer (AdamW optimizer).\n", + "- lr_scheduler_type: Learning rate schedule.\n", + "- max_steps: Number of training steps.\n", + "- warmup_ratio: Ratio of steps for a linear warmup.\n", + "- group_by_length: This can significantly improve performance and accelerate the training process.\n", + "- save_steps: Save checkpoint every 25 update steps.\n", + "- logging_steps: Log every 25 update steps" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "2cbdbbe6-2092-43c3-a625-d367b01b8836", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/peft/utils/other.py:102: FutureWarning: prepare_model_for_int8_training is deprecated and will be removed in a future version. Use prepare_model_for_kbit_training instead.\n", + " warnings.warn(\n", + "/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/trl/trainer/sft_trainer.py:159: UserWarning: You didn't pass a `max_seq_length` argument to the SFTTrainer, this will default to 1024\n", + " warnings.warn(\n" + ] + } + ], + "source": [ + "# Set training parameters\n", + "training_arguments = TrainingArguments(\n", + " output_dir=output_dir,\n", + " num_train_epochs=num_train_epochs,\n", + " per_device_train_batch_size=per_device_train_batch_size,\n", + " gradient_accumulation_steps=gradient_accumulation_steps,\n", + " optim=optim,\n", + " save_steps=save_steps,\n", + " logging_steps=logging_steps,\n", + " learning_rate=learning_rate,\n", + " weight_decay=weight_decay,\n", + " fp16=fp16,\n", + " bf16=bf16,\n", + " max_grad_norm=max_grad_norm,\n", + " max_steps=max_steps,\n", + " warmup_ratio=warmup_ratio,\n", + " group_by_length=group_by_length,\n", + " lr_scheduler_type=lr_scheduler_type,\n", + " report_to=\"tensorboard\"\n", + ")\n", + "\n", + "# Set supervised fine-tuning parameters\n", + "trainer = SFTTrainer(\n", + " model=model,\n", + " train_dataset=dataset[\"train\"],\n", + " peft_config=peft_config,\n", + " dataset_text_field=\"text\",\n", + " max_seq_length=max_seq_length,\n", + " tokenizer=tokenizer,\n", + " args=training_arguments,\n", + " packing=packing,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "811b63b6-d52e-4f6d-8ee0-8645389e45f0", + "metadata": {}, + "source": [ + "## Train\n", + "\n", + "Now we can do the actual training with SFT." + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "6ef38a9b-c59f-4c26-8724-aa714a99223d", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "You're using a LlamaTokenizerFast tokenizer. Please note that with a fast tokenizer, using the `__call__` method is faster than using a method to encode the text followed by a call to the `pad` method to get a padded encoding.\n", + "`use_cache=True` is incompatible with gradient checkpointing. Setting `use_cache=False`...\n", + "/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.\n", + " warnings.warn(\n" + ] + }, + { + "data": { + "text/html": [ + "\n", + "
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" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.\n", + " warnings.warn(\n", + "/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.\n", + " warnings.warn(\n", + "/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.\n", + " warnings.warn(\n", + "/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.\n", + " warnings.warn(\n", + "/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.\n", + " warnings.warn(\n", + "/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.\n", + " warnings.warn(\n", + "/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.\n", + " warnings.warn(\n", + "/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.\n", + " warnings.warn(\n", + "/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.\n", + " warnings.warn(\n", + "/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.\n", + " warnings.warn(\n", + "/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.\n", + " warnings.warn(\n", + "/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.\n", + " warnings.warn(\n", + "/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.\n", + " warnings.warn(\n", + "/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.\n", + " warnings.warn(\n", + "/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.\n", + " warnings.warn(\n", + "/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.\n", + " warnings.warn(\n", + "/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.\n", + " warnings.warn(\n", + "/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.\n", + " warnings.warn(\n", + "/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.\n", + " warnings.warn(\n", + "/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.\n", + " warnings.warn(\n", + "/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.\n", + " warnings.warn(\n", + "/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.\n", + " warnings.warn(\n", + "/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.\n", + " warnings.warn(\n", + "/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.\n", + " warnings.warn(\n", + "/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.\n", + " warnings.warn(\n", + "/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.\n", + " warnings.warn(\n", + "/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.\n", + " warnings.warn(\n", + "/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.\n", + " warnings.warn(\n", + "/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.\n", + " warnings.warn(\n", + "/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.\n", + " warnings.warn(\n", + "/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.\n", + " warnings.warn(\n", + "/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.\n", + " warnings.warn(\n", + "/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.\n", + " warnings.warn(\n", + "/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.\n", + " warnings.warn(\n", + "/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.\n", + " warnings.warn(\n", + "/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.\n", + " warnings.warn(\n", + "/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.\n", + " warnings.warn(\n", + "/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.\n", + " warnings.warn(\n", + "/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.\n", + " warnings.warn(\n", + "/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.\n", + " warnings.warn(\n", + "/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.\n", + " warnings.warn(\n", + "/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.\n", + " warnings.warn(\n", + "/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.\n", + " warnings.warn(\n", + "/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.\n", + " warnings.warn(\n", + "/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.\n", + " warnings.warn(\n", + "/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.\n", + " warnings.warn(\n", + "/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.\n", + " warnings.warn(\n", + "/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.\n", + " warnings.warn(\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Execution time: 758.4831464290619 seconds\n" + ] + } + ], + "source": [ + "import time\n", + "\n", + "start_time = time.time()\n", + "\n", + "# Train model\n", + "trainer.train()\n", + "\n", + "end_time = time.time()\n", + "execution_time = end_time - start_time\n", + "print(\"Execution time: \", execution_time, \"seconds\")\n", + "\n", + "# Save trained model\n", + "trainer.model.save_pretrained(new_model)" + ] + }, + { + "cell_type": "markdown", + "id": "89abb2ae-d819-4231-8c6c-0ac58dd2edce", + "metadata": {}, + "source": [ + "## Inference with new model\n", + "\n", + "Once the training is done, we can test the input/output from new model. Here I throw a question from the original dataset. And unsurprisingly, the model returns the correct answer. The problem is the model repeating it selft with continued text. I have not found a fix yet. Please raise an issue in github if you know the fix." + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "26fda72d-aa8b-4dfd-a684-3538c6e95f7a", + "metadata": {}, + "outputs": [ + { + "ename": "OutOfMemoryError", + "evalue": "CUDA out of memory. Tried to allocate 86.00 MiB. GPU 0 has a total capacity of 10.00 GiB of which 0 bytes is free. Including non-PyTorch memory, this process has 17179869184.00 GiB memory in use. Of the allocated memory 16.11 GiB is allocated by PyTorch, and 129.54 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mOutOfMemoryError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[16], line 6\u001b[0m\n\u001b[1;32m 4\u001b[0m prompt \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mthe company has no plans to move all production to Russia\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 5\u001b[0m pipe \u001b[38;5;241m=\u001b[39m pipeline(task\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtext-generation\u001b[39m\u001b[38;5;124m\"\u001b[39m, model\u001b[38;5;241m=\u001b[39mmodel, tokenizer\u001b[38;5;241m=\u001b[39mtokenizer, max_length\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m200\u001b[39m)\n\u001b[0;32m----> 6\u001b[0m result \u001b[38;5;241m=\u001b[39m \u001b[43mpipe\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43mf\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m### Instruction: What is the sentiment of this tweet? Please choose an answer from \u001b[39;49m\u001b[38;5;130;43;01m{{\u001b[39;49;00m\u001b[38;5;124;43mnegative/neutral/positive\u001b[39;49m\u001b[38;5;130;43;01m}}\u001b[39;49;00m\u001b[38;5;124;43m ### Human: \u001b[39;49m\u001b[38;5;132;43;01m{\u001b[39;49;00m\u001b[43mprompt\u001b[49m\u001b[38;5;132;43;01m}\u001b[39;49;00m\u001b[38;5;124;43m ### Assistant:\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m 7\u001b[0m \u001b[38;5;28mprint\u001b[39m(result[\u001b[38;5;241m0\u001b[39m][\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mgenerated_text\u001b[39m\u001b[38;5;124m'\u001b[39m])\n", + "File \u001b[0;32m/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/transformers/pipelines/text_generation.py:200\u001b[0m, in \u001b[0;36mTextGenerationPipeline.__call__\u001b[0;34m(self, text_inputs, **kwargs)\u001b[0m\n\u001b[1;32m 159\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__call__\u001b[39m(\u001b[38;5;28mself\u001b[39m, text_inputs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[1;32m 160\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 161\u001b[0m \u001b[38;5;124;03m Complete the prompt(s) given as inputs.\u001b[39;00m\n\u001b[1;32m 162\u001b[0m \n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 198\u001b[0m \u001b[38;5;124;03m ids of the generated text.\u001b[39;00m\n\u001b[1;32m 199\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[0;32m--> 200\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43msuper\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[38;5;21;43m__call__\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mtext_inputs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/transformers/pipelines/base.py:1122\u001b[0m, in \u001b[0;36mPipeline.__call__\u001b[0;34m(self, inputs, num_workers, batch_size, *args, **kwargs)\u001b[0m\n\u001b[1;32m 1114\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mnext\u001b[39m(\n\u001b[1;32m 1115\u001b[0m \u001b[38;5;28miter\u001b[39m(\n\u001b[1;32m 1116\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mget_iterator(\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 1119\u001b[0m )\n\u001b[1;32m 1120\u001b[0m )\n\u001b[1;32m 1121\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 1122\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrun_single\u001b[49m\u001b[43m(\u001b[49m\u001b[43minputs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpreprocess_params\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mforward_params\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpostprocess_params\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/transformers/pipelines/base.py:1129\u001b[0m, in \u001b[0;36mPipeline.run_single\u001b[0;34m(self, inputs, preprocess_params, forward_params, postprocess_params)\u001b[0m\n\u001b[1;32m 1127\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mrun_single\u001b[39m(\u001b[38;5;28mself\u001b[39m, inputs, preprocess_params, forward_params, postprocess_params):\n\u001b[1;32m 1128\u001b[0m model_inputs \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mpreprocess(inputs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mpreprocess_params)\n\u001b[0;32m-> 1129\u001b[0m model_outputs \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mforward\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmodel_inputs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mforward_params\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1130\u001b[0m outputs \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mpostprocess(model_outputs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mpostprocess_params)\n\u001b[1;32m 1131\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m outputs\n", + "File \u001b[0;32m/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/transformers/pipelines/base.py:1028\u001b[0m, in \u001b[0;36mPipeline.forward\u001b[0;34m(self, model_inputs, **forward_params)\u001b[0m\n\u001b[1;32m 1026\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m inference_context():\n\u001b[1;32m 1027\u001b[0m model_inputs \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_ensure_tensor_on_device(model_inputs, device\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdevice)\n\u001b[0;32m-> 1028\u001b[0m model_outputs \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_forward\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmodel_inputs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mforward_params\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1029\u001b[0m model_outputs \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_ensure_tensor_on_device(model_outputs, device\u001b[38;5;241m=\u001b[39mtorch\u001b[38;5;241m.\u001b[39mdevice(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcpu\u001b[39m\u001b[38;5;124m\"\u001b[39m))\n\u001b[1;32m 1030\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n", + "File \u001b[0;32m/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/transformers/pipelines/text_generation.py:261\u001b[0m, in \u001b[0;36mTextGenerationPipeline._forward\u001b[0;34m(self, model_inputs, **generate_kwargs)\u001b[0m\n\u001b[1;32m 258\u001b[0m generate_kwargs[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmin_length\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m prefix_length\n\u001b[1;32m 260\u001b[0m \u001b[38;5;66;03m# BS x SL\u001b[39;00m\n\u001b[0;32m--> 261\u001b[0m generated_sequence \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmodel\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mgenerate\u001b[49m\u001b[43m(\u001b[49m\u001b[43minput_ids\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43minput_ids\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mattention_mask\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mattention_mask\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mgenerate_kwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 262\u001b[0m out_b \u001b[38;5;241m=\u001b[39m generated_sequence\u001b[38;5;241m.\u001b[39mshape[\u001b[38;5;241m0\u001b[39m]\n\u001b[1;32m 263\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mframework \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mpt\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n", + "File \u001b[0;32m/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/utils/_contextlib.py:115\u001b[0m, in \u001b[0;36mcontext_decorator..decorate_context\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 112\u001b[0m \u001b[38;5;129m@functools\u001b[39m\u001b[38;5;241m.\u001b[39mwraps(func)\n\u001b[1;32m 113\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mdecorate_context\u001b[39m(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[1;32m 114\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m ctx_factory():\n\u001b[0;32m--> 115\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/transformers/generation/utils.py:1538\u001b[0m, in \u001b[0;36mGenerationMixin.generate\u001b[0;34m(self, inputs, generation_config, logits_processor, stopping_criteria, prefix_allowed_tokens_fn, synced_gpus, assistant_model, streamer, **kwargs)\u001b[0m\n\u001b[1;32m 1532\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[1;32m 1533\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mnum_return_sequences has to be 1 when doing greedy search, \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 1534\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mbut is \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mgeneration_config\u001b[38;5;241m.\u001b[39mnum_return_sequences\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 1535\u001b[0m )\n\u001b[1;32m 1537\u001b[0m \u001b[38;5;66;03m# 11. run greedy search\u001b[39;00m\n\u001b[0;32m-> 1538\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mgreedy_search\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 1539\u001b[0m \u001b[43m \u001b[49m\u001b[43minput_ids\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1540\u001b[0m \u001b[43m \u001b[49m\u001b[43mlogits_processor\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mlogits_processor\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1541\u001b[0m \u001b[43m \u001b[49m\u001b[43mstopping_criteria\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstopping_criteria\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1542\u001b[0m \u001b[43m \u001b[49m\u001b[43mpad_token_id\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mgeneration_config\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mpad_token_id\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1543\u001b[0m \u001b[43m \u001b[49m\u001b[43meos_token_id\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mgeneration_config\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43meos_token_id\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1544\u001b[0m \u001b[43m \u001b[49m\u001b[43moutput_scores\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mgeneration_config\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43moutput_scores\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1545\u001b[0m \u001b[43m \u001b[49m\u001b[43mreturn_dict_in_generate\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mgeneration_config\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mreturn_dict_in_generate\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1546\u001b[0m \u001b[43m \u001b[49m\u001b[43msynced_gpus\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43msynced_gpus\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1547\u001b[0m \u001b[43m \u001b[49m\u001b[43mstreamer\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstreamer\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1548\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mmodel_kwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1549\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1551\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m is_contrastive_search_gen_mode:\n\u001b[1;32m 1552\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m generation_config\u001b[38;5;241m.\u001b[39mnum_return_sequences \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m1\u001b[39m:\n", + "File \u001b[0;32m/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/transformers/generation/utils.py:2362\u001b[0m, in \u001b[0;36mGenerationMixin.greedy_search\u001b[0;34m(self, input_ids, logits_processor, stopping_criteria, max_length, pad_token_id, eos_token_id, output_attentions, output_hidden_states, output_scores, return_dict_in_generate, synced_gpus, streamer, **model_kwargs)\u001b[0m\n\u001b[1;32m 2359\u001b[0m model_inputs \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mprepare_inputs_for_generation(input_ids, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mmodel_kwargs)\n\u001b[1;32m 2361\u001b[0m \u001b[38;5;66;03m# forward pass to get next token\u001b[39;00m\n\u001b[0;32m-> 2362\u001b[0m outputs \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m(\u001b[49m\n\u001b[1;32m 2363\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mmodel_inputs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 2364\u001b[0m \u001b[43m \u001b[49m\u001b[43mreturn_dict\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m 2365\u001b[0m \u001b[43m \u001b[49m\u001b[43moutput_attentions\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43moutput_attentions\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 2366\u001b[0m \u001b[43m \u001b[49m\u001b[43moutput_hidden_states\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43moutput_hidden_states\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 2367\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 2369\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m synced_gpus \u001b[38;5;129;01mand\u001b[39;00m this_peer_finished:\n\u001b[1;32m 2370\u001b[0m \u001b[38;5;28;01mcontinue\u001b[39;00m \u001b[38;5;66;03m# don't waste resources running the code we don't need\u001b[39;00m\n", + "File \u001b[0;32m/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:1511\u001b[0m, in \u001b[0;36mModule._wrapped_call_impl\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 1509\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_compiled_call_impl(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs) \u001b[38;5;66;03m# type: ignore[misc]\u001b[39;00m\n\u001b[1;32m 1510\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 1511\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_call_impl\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:1520\u001b[0m, in \u001b[0;36mModule._call_impl\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 1515\u001b[0m \u001b[38;5;66;03m# If we don't have any hooks, we want to skip the rest of the logic in\u001b[39;00m\n\u001b[1;32m 1516\u001b[0m \u001b[38;5;66;03m# this function, and just call forward.\u001b[39;00m\n\u001b[1;32m 1517\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m (\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_backward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_backward_pre_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_forward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_forward_pre_hooks\n\u001b[1;32m 1518\u001b[0m \u001b[38;5;129;01mor\u001b[39;00m _global_backward_pre_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_backward_hooks\n\u001b[1;32m 1519\u001b[0m \u001b[38;5;129;01mor\u001b[39;00m _global_forward_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_forward_pre_hooks):\n\u001b[0;32m-> 1520\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mforward_call\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1522\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m 1523\u001b[0m result \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n", + "File \u001b[0;32m/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/accelerate/hooks.py:165\u001b[0m, in \u001b[0;36madd_hook_to_module..new_forward\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 163\u001b[0m output \u001b[38;5;241m=\u001b[39m old_forward(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[1;32m 164\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m--> 165\u001b[0m output \u001b[38;5;241m=\u001b[39m \u001b[43mold_forward\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 166\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m module\u001b[38;5;241m.\u001b[39m_hf_hook\u001b[38;5;241m.\u001b[39mpost_forward(module, output)\n", + "File \u001b[0;32m/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/transformers/models/llama/modeling_llama.py:806\u001b[0m, in \u001b[0;36mLlamaForCausalLM.forward\u001b[0;34m(self, input_ids, attention_mask, position_ids, past_key_values, inputs_embeds, labels, use_cache, output_attentions, output_hidden_states, return_dict)\u001b[0m\n\u001b[1;32m 803\u001b[0m return_dict \u001b[38;5;241m=\u001b[39m return_dict \u001b[38;5;28;01mif\u001b[39;00m return_dict \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mconfig\u001b[38;5;241m.\u001b[39muse_return_dict\n\u001b[1;32m 805\u001b[0m \u001b[38;5;66;03m# decoder outputs consists of (dec_features, layer_state, dec_hidden, dec_attn)\u001b[39;00m\n\u001b[0;32m--> 806\u001b[0m outputs \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmodel\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 807\u001b[0m \u001b[43m \u001b[49m\u001b[43minput_ids\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43minput_ids\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 808\u001b[0m \u001b[43m \u001b[49m\u001b[43mattention_mask\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mattention_mask\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 809\u001b[0m \u001b[43m \u001b[49m\u001b[43mposition_ids\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mposition_ids\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 810\u001b[0m \u001b[43m \u001b[49m\u001b[43mpast_key_values\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mpast_key_values\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 811\u001b[0m \u001b[43m \u001b[49m\u001b[43minputs_embeds\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43minputs_embeds\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 812\u001b[0m \u001b[43m \u001b[49m\u001b[43muse_cache\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43muse_cache\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 813\u001b[0m \u001b[43m \u001b[49m\u001b[43moutput_attentions\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43moutput_attentions\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 814\u001b[0m \u001b[43m \u001b[49m\u001b[43moutput_hidden_states\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43moutput_hidden_states\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 815\u001b[0m \u001b[43m \u001b[49m\u001b[43mreturn_dict\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mreturn_dict\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 816\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 818\u001b[0m hidden_states \u001b[38;5;241m=\u001b[39m outputs[\u001b[38;5;241m0\u001b[39m]\n\u001b[1;32m 819\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mpretraining_tp \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m1\u001b[39m:\n", + "File \u001b[0;32m/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:1511\u001b[0m, in \u001b[0;36mModule._wrapped_call_impl\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 1509\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_compiled_call_impl(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs) \u001b[38;5;66;03m# type: ignore[misc]\u001b[39;00m\n\u001b[1;32m 1510\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 1511\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_call_impl\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:1520\u001b[0m, in \u001b[0;36mModule._call_impl\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 1515\u001b[0m \u001b[38;5;66;03m# If we don't have any hooks, we want to skip the rest of the logic in\u001b[39;00m\n\u001b[1;32m 1516\u001b[0m \u001b[38;5;66;03m# this function, and just call forward.\u001b[39;00m\n\u001b[1;32m 1517\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m (\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_backward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_backward_pre_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_forward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_forward_pre_hooks\n\u001b[1;32m 1518\u001b[0m \u001b[38;5;129;01mor\u001b[39;00m _global_backward_pre_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_backward_hooks\n\u001b[1;32m 1519\u001b[0m \u001b[38;5;129;01mor\u001b[39;00m _global_forward_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_forward_pre_hooks):\n\u001b[0;32m-> 1520\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mforward_call\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1522\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m 1523\u001b[0m result \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n", + "File \u001b[0;32m/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/accelerate/hooks.py:165\u001b[0m, in \u001b[0;36madd_hook_to_module..new_forward\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 163\u001b[0m output \u001b[38;5;241m=\u001b[39m old_forward(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[1;32m 164\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m--> 165\u001b[0m output \u001b[38;5;241m=\u001b[39m \u001b[43mold_forward\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 166\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m module\u001b[38;5;241m.\u001b[39m_hf_hook\u001b[38;5;241m.\u001b[39mpost_forward(module, output)\n", + "File \u001b[0;32m/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/transformers/models/llama/modeling_llama.py:685\u001b[0m, in \u001b[0;36mLlamaModel.forward\u001b[0;34m(self, input_ids, attention_mask, position_ids, past_key_values, inputs_embeds, use_cache, output_attentions, output_hidden_states, return_dict)\u001b[0m\n\u001b[1;32m 681\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m module(\u001b[38;5;241m*\u001b[39minputs, output_attentions, \u001b[38;5;28;01mNone\u001b[39;00m)\n\u001b[1;32m 683\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m custom_forward\n\u001b[0;32m--> 685\u001b[0m layer_outputs \u001b[38;5;241m=\u001b[39m \u001b[43mtorch\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mutils\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcheckpoint\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcheckpoint\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 686\u001b[0m \u001b[43m \u001b[49m\u001b[43mcreate_custom_forward\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdecoder_layer\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 687\u001b[0m \u001b[43m \u001b[49m\u001b[43mhidden_states\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 688\u001b[0m \u001b[43m \u001b[49m\u001b[43mattention_mask\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 689\u001b[0m \u001b[43m \u001b[49m\u001b[43mposition_ids\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 690\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m 691\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 692\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 693\u001b[0m layer_outputs \u001b[38;5;241m=\u001b[39m decoder_layer(\n\u001b[1;32m 694\u001b[0m hidden_states,\n\u001b[1;32m 695\u001b[0m attention_mask\u001b[38;5;241m=\u001b[39mattention_mask,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 699\u001b[0m use_cache\u001b[38;5;241m=\u001b[39muse_cache,\n\u001b[1;32m 700\u001b[0m )\n", + "File \u001b[0;32m/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/_compile.py:24\u001b[0m, in \u001b[0;36m_disable_dynamo..inner\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 20\u001b[0m \u001b[38;5;129m@functools\u001b[39m\u001b[38;5;241m.\u001b[39mwraps(fn)\n\u001b[1;32m 21\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21minner\u001b[39m(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[1;32m 22\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mtorch\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_dynamo\u001b[39;00m\n\u001b[0;32m---> 24\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mtorch\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_dynamo\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdisable\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfn\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mrecursive\u001b[49m\u001b[43m)\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/_dynamo/eval_frame.py:489\u001b[0m, in \u001b[0;36m_TorchDynamoContext.__call__.._fn\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 487\u001b[0m dynamo_config_ctx\u001b[38;5;241m.\u001b[39m\u001b[38;5;21m__enter__\u001b[39m()\n\u001b[1;32m 488\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 489\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfn\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 490\u001b[0m \u001b[38;5;28;01mfinally\u001b[39;00m:\n\u001b[1;32m 491\u001b[0m set_eval_frame(prior)\n", + "File \u001b[0;32m/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/_dynamo/external_utils.py:17\u001b[0m, in \u001b[0;36mwrap_inline..inner\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 15\u001b[0m \u001b[38;5;129m@functools\u001b[39m\u001b[38;5;241m.\u001b[39mwraps(fn)\n\u001b[1;32m 16\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21minner\u001b[39m(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[0;32m---> 17\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m 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For more details, please see \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 560\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mhttps://pytorch.org/docs/master/notes/extending.func.html\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 561\u001b[0m )\n", + "File \u001b[0;32m/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/utils/checkpoint.py:261\u001b[0m, in \u001b[0;36mCheckpointFunction.forward\u001b[0;34m(ctx, run_function, preserve_rng_state, *args)\u001b[0m\n\u001b[1;32m 258\u001b[0m ctx\u001b[38;5;241m.\u001b[39msave_for_backward(\u001b[38;5;241m*\u001b[39mtensor_inputs)\n\u001b[1;32m 260\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m torch\u001b[38;5;241m.\u001b[39mno_grad():\n\u001b[0;32m--> 261\u001b[0m outputs \u001b[38;5;241m=\u001b[39m \u001b[43mrun_function\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 262\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m outputs\n", + "File \u001b[0;32m/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/transformers/models/llama/modeling_llama.py:681\u001b[0m, in \u001b[0;36mLlamaModel.forward..create_custom_forward..custom_forward\u001b[0;34m(*inputs)\u001b[0m\n\u001b[1;32m 679\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mcustom_forward\u001b[39m(\u001b[38;5;241m*\u001b[39minputs):\n\u001b[1;32m 680\u001b[0m \u001b[38;5;66;03m# None for past_key_value\u001b[39;00m\n\u001b[0;32m--> 681\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mmodule\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43minputs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43moutput_attentions\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:1511\u001b[0m, in \u001b[0;36mModule._wrapped_call_impl\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 1509\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_compiled_call_impl(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs) \u001b[38;5;66;03m# type: ignore[misc]\u001b[39;00m\n\u001b[1;32m 1510\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 1511\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_call_impl\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:1520\u001b[0m, in \u001b[0;36mModule._call_impl\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 1515\u001b[0m \u001b[38;5;66;03m# If we don't have any hooks, we want to skip the rest of the logic in\u001b[39;00m\n\u001b[1;32m 1516\u001b[0m \u001b[38;5;66;03m# this function, and just call forward.\u001b[39;00m\n\u001b[1;32m 1517\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m (\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_backward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_backward_pre_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_forward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_forward_pre_hooks\n\u001b[1;32m 1518\u001b[0m \u001b[38;5;129;01mor\u001b[39;00m _global_backward_pre_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_backward_hooks\n\u001b[1;32m 1519\u001b[0m \u001b[38;5;129;01mor\u001b[39;00m _global_forward_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_forward_pre_hooks):\n\u001b[0;32m-> 1520\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mforward_call\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1522\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m 1523\u001b[0m result \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n", + "File \u001b[0;32m/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/accelerate/hooks.py:165\u001b[0m, in \u001b[0;36madd_hook_to_module..new_forward\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 163\u001b[0m output \u001b[38;5;241m=\u001b[39m old_forward(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[1;32m 164\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m--> 165\u001b[0m output \u001b[38;5;241m=\u001b[39m \u001b[43mold_forward\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 166\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m module\u001b[38;5;241m.\u001b[39m_hf_hook\u001b[38;5;241m.\u001b[39mpost_forward(module, output)\n", + "File \u001b[0;32m/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/transformers/models/llama/modeling_llama.py:421\u001b[0m, in \u001b[0;36mLlamaDecoderLayer.forward\u001b[0;34m(self, hidden_states, attention_mask, position_ids, past_key_value, output_attentions, use_cache)\u001b[0m\n\u001b[1;32m 419\u001b[0m residual \u001b[38;5;241m=\u001b[39m hidden_states\n\u001b[1;32m 420\u001b[0m hidden_states \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mpost_attention_layernorm(hidden_states)\n\u001b[0;32m--> 421\u001b[0m hidden_states \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmlp\u001b[49m\u001b[43m(\u001b[49m\u001b[43mhidden_states\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 422\u001b[0m hidden_states \u001b[38;5;241m=\u001b[39m residual \u001b[38;5;241m+\u001b[39m hidden_states\n\u001b[1;32m 424\u001b[0m outputs \u001b[38;5;241m=\u001b[39m (hidden_states,)\n", + "File \u001b[0;32m/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:1511\u001b[0m, in \u001b[0;36mModule._wrapped_call_impl\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 1509\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_compiled_call_impl(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs) \u001b[38;5;66;03m# type: ignore[misc]\u001b[39;00m\n\u001b[1;32m 1510\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 1511\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_call_impl\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:1520\u001b[0m, in \u001b[0;36mModule._call_impl\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 1515\u001b[0m \u001b[38;5;66;03m# If we don't have any hooks, we want to skip the rest of the logic in\u001b[39;00m\n\u001b[1;32m 1516\u001b[0m \u001b[38;5;66;03m# this function, and just call forward.\u001b[39;00m\n\u001b[1;32m 1517\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m (\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_backward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_backward_pre_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_forward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_forward_pre_hooks\n\u001b[1;32m 1518\u001b[0m \u001b[38;5;129;01mor\u001b[39;00m _global_backward_pre_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_backward_hooks\n\u001b[1;32m 1519\u001b[0m \u001b[38;5;129;01mor\u001b[39;00m _global_forward_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_forward_pre_hooks):\n\u001b[0;32m-> 1520\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mforward_call\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1522\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m 1523\u001b[0m result \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n", + "File \u001b[0;32m/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/accelerate/hooks.py:165\u001b[0m, in \u001b[0;36madd_hook_to_module..new_forward\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 163\u001b[0m output \u001b[38;5;241m=\u001b[39m old_forward(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[1;32m 164\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m--> 165\u001b[0m output \u001b[38;5;241m=\u001b[39m \u001b[43mold_forward\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 166\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m module\u001b[38;5;241m.\u001b[39m_hf_hook\u001b[38;5;241m.\u001b[39mpost_forward(module, output)\n", + "File \u001b[0;32m/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/transformers/models/llama/modeling_llama.py:216\u001b[0m, in \u001b[0;36mLlamaMLP.forward\u001b[0;34m(self, x)\u001b[0m\n\u001b[1;32m 214\u001b[0m down_proj \u001b[38;5;241m=\u001b[39m \u001b[38;5;28msum\u001b[39m(down_proj)\n\u001b[1;32m 215\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m--> 216\u001b[0m down_proj \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdown_proj(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mact_fn(\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mgate_proj\u001b[49m\u001b[43m(\u001b[49m\u001b[43mx\u001b[49m\u001b[43m)\u001b[49m) \u001b[38;5;241m*\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mup_proj(x))\n\u001b[1;32m 218\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m down_proj\n", + "File \u001b[0;32m/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:1511\u001b[0m, in \u001b[0;36mModule._wrapped_call_impl\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 1509\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_compiled_call_impl(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs) \u001b[38;5;66;03m# type: ignore[misc]\u001b[39;00m\n\u001b[1;32m 1510\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 1511\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_call_impl\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:1520\u001b[0m, in \u001b[0;36mModule._call_impl\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 1515\u001b[0m \u001b[38;5;66;03m# If we don't have any hooks, we want to skip the rest of the logic in\u001b[39;00m\n\u001b[1;32m 1516\u001b[0m \u001b[38;5;66;03m# this function, and just call forward.\u001b[39;00m\n\u001b[1;32m 1517\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m (\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_backward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_backward_pre_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_forward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_forward_pre_hooks\n\u001b[1;32m 1518\u001b[0m \u001b[38;5;129;01mor\u001b[39;00m _global_backward_pre_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_backward_hooks\n\u001b[1;32m 1519\u001b[0m \u001b[38;5;129;01mor\u001b[39;00m _global_forward_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_forward_pre_hooks):\n\u001b[0;32m-> 1520\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mforward_call\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1522\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m 1523\u001b[0m result \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n", + "File \u001b[0;32m/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/accelerate/hooks.py:165\u001b[0m, in \u001b[0;36madd_hook_to_module..new_forward\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 163\u001b[0m output \u001b[38;5;241m=\u001b[39m old_forward(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[1;32m 164\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m--> 165\u001b[0m output \u001b[38;5;241m=\u001b[39m \u001b[43mold_forward\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 166\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m module\u001b[38;5;241m.\u001b[39m_hf_hook\u001b[38;5;241m.\u001b[39mpost_forward(module, output)\n", + "File \u001b[0;32m/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/bitsandbytes/nn/modules.py:221\u001b[0m, in \u001b[0;36mLinear4bit.forward\u001b[0;34m(self, x)\u001b[0m\n\u001b[1;32m 218\u001b[0m x \u001b[38;5;241m=\u001b[39m x\u001b[38;5;241m.\u001b[39mto(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcompute_dtype)\n\u001b[1;32m 220\u001b[0m bias \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mbias \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mbias\u001b[38;5;241m.\u001b[39mto(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcompute_dtype)\n\u001b[0;32m--> 221\u001b[0m out \u001b[38;5;241m=\u001b[39m \u001b[43mbnb\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmatmul_4bit\u001b[49m\u001b[43m(\u001b[49m\u001b[43mx\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mweight\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mt\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbias\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mbias\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mquant_state\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mweight\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mquant_state\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 223\u001b[0m out \u001b[38;5;241m=\u001b[39m out\u001b[38;5;241m.\u001b[39mto(inp_dtype)\n\u001b[1;32m 225\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m out\n", + "File \u001b[0;32m/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/bitsandbytes/autograd/_functions.py:579\u001b[0m, in \u001b[0;36mmatmul_4bit\u001b[0;34m(A, B, quant_state, out, bias)\u001b[0m\n\u001b[1;32m 577\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m out\n\u001b[1;32m 578\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m--> 579\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mMatMul4Bit\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mapply\u001b[49m\u001b[43m(\u001b[49m\u001b[43mA\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mB\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mout\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbias\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mquant_state\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/torch/autograd/function.py:553\u001b[0m, in \u001b[0;36mFunction.apply\u001b[0;34m(cls, *args, **kwargs)\u001b[0m\n\u001b[1;32m 550\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m torch\u001b[38;5;241m.\u001b[39m_C\u001b[38;5;241m.\u001b[39m_are_functorch_transforms_active():\n\u001b[1;32m 551\u001b[0m \u001b[38;5;66;03m# See NOTE: [functorch vjp and autograd interaction]\u001b[39;00m\n\u001b[1;32m 552\u001b[0m args \u001b[38;5;241m=\u001b[39m _functorch\u001b[38;5;241m.\u001b[39mutils\u001b[38;5;241m.\u001b[39munwrap_dead_wrappers(args)\n\u001b[0;32m--> 553\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43msuper\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mapply\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;66;03m# type: ignore[misc]\u001b[39;00m\n\u001b[1;32m 555\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m is_setup_ctx_defined:\n\u001b[1;32m 556\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mRuntimeError\u001b[39;00m(\n\u001b[1;32m 557\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mIn order to use an autograd.Function with functorch transforms \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 558\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m(vmap, grad, jvp, jacrev, ...), it must override the setup_context \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 559\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mstaticmethod. For more details, please see \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 560\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mhttps://pytorch.org/docs/master/notes/extending.func.html\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 561\u001b[0m )\n", + "File \u001b[0;32m/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/bitsandbytes/autograd/_functions.py:516\u001b[0m, in \u001b[0;36mMatMul4Bit.forward\u001b[0;34m(ctx, A, B, out, bias, state)\u001b[0m\n\u001b[1;32m 511\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m torch\u001b[38;5;241m.\u001b[39mempty(A\u001b[38;5;241m.\u001b[39mshape[:\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m] \u001b[38;5;241m+\u001b[39m B_shape[:\u001b[38;5;241m1\u001b[39m], dtype\u001b[38;5;241m=\u001b[39mA\u001b[38;5;241m.\u001b[39mdtype, device\u001b[38;5;241m=\u001b[39mA\u001b[38;5;241m.\u001b[39mdevice)\n\u001b[1;32m 514\u001b[0m \u001b[38;5;66;03m# 1. Dequantize\u001b[39;00m\n\u001b[1;32m 515\u001b[0m \u001b[38;5;66;03m# 2. MatmulnN\u001b[39;00m\n\u001b[0;32m--> 516\u001b[0m output \u001b[38;5;241m=\u001b[39m torch\u001b[38;5;241m.\u001b[39mnn\u001b[38;5;241m.\u001b[39mfunctional\u001b[38;5;241m.\u001b[39mlinear(A, \u001b[43mF\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdequantize_4bit\u001b[49m\u001b[43m(\u001b[49m\u001b[43mB\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mstate\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241m.\u001b[39mto(A\u001b[38;5;241m.\u001b[39mdtype)\u001b[38;5;241m.\u001b[39mt(), bias)\n\u001b[1;32m 518\u001b[0m \u001b[38;5;66;03m# 3. Save state\u001b[39;00m\n\u001b[1;32m 519\u001b[0m ctx\u001b[38;5;241m.\u001b[39mstate \u001b[38;5;241m=\u001b[39m state\n", + "File \u001b[0;32m/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/bitsandbytes/functional.py:908\u001b[0m, in \u001b[0;36mdequantize_4bit\u001b[0;34m(A, quant_state, absmax, out, blocksize, quant_type)\u001b[0m\n\u001b[1;32m 905\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m absmax\u001b[38;5;241m.\u001b[39mdtype \u001b[38;5;241m!=\u001b[39m torch\u001b[38;5;241m.\u001b[39mfloat32: absmax \u001b[38;5;241m=\u001b[39m absmax\u001b[38;5;241m.\u001b[39mfloat()\n\u001b[1;32m 907\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m out \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m--> 908\u001b[0m out \u001b[38;5;241m=\u001b[39m \u001b[43mtorch\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mempty\u001b[49m\u001b[43m(\u001b[49m\u001b[43mshape\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdtype\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdtype\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdevice\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mA\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdevice\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 910\u001b[0m n \u001b[38;5;241m=\u001b[39m out\u001b[38;5;241m.\u001b[39mnumel()\n\u001b[1;32m 913\u001b[0m device \u001b[38;5;241m=\u001b[39m pre_call(A\u001b[38;5;241m.\u001b[39mdevice)\n", + "\u001b[0;31mOutOfMemoryError\u001b[0m: CUDA out of memory. Tried to allocate 86.00 MiB. GPU 0 has a total capacity of 10.00 GiB of which 0 bytes is free. Including non-PyTorch memory, this process has 17179869184.00 GiB memory in use. Of the allocated memory 16.11 GiB is allocated by PyTorch, and 129.54 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)" + ] + } + ], + "source": [ + "logging.set_verbosity(logging.CRITICAL)\n", + "\n", + "# Run text generation pipeline with our next model\n", + "prompt = \"the company has no plans to move all production to Russia\"\n", + "pipe = pipeline(task=\"text-generation\", model=model, tokenizer=tokenizer, max_length=200)\n", + "result = pipe(f\"### Instruction: What is the sentiment of this tweet? Please choose an answer from {{negative/neutral/positive}} ### Human: {prompt} ### Assistant:\")\n", + "print(result[0]['generated_text'])" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "79b86045-287c-484c-a4a0-9a566fa64ddd", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[INST] What is a large language model? [/INST] A large language model is a type of artificial intelligence (AI) model that is trained on a large dataset of text to generate language outputs that are coherent and natural-sounding. everybody is talking about the next big thing in AI: large language models. Large language models are neural networks that are trained on vast amounts of text data to generate language outputs that are coherent and natural-sounding. These models are capable of generating text that is often indistinguishable from human-written text, and they have a wide range of applications, from chatbots and language translation to content generation and text summarization. In this article, we will explore the current state of large language models, their applications, and the challenges and limitations of these models. What is a large language model? A large language model is a type of neural network that is trained on a large dataset of text\n" + ] + } + ], + "source": [ + "# Ignore warnings\n", + "logging.set_verbosity(logging.CRITICAL)\n", + "\n", + "# Run text generation pipeline with our next model\n", + "prompt = \"What is a large language model?\"\n", + "pipe = pipeline(task=\"text-generation\", model=model, tokenizer=tokenizer, max_length=200)\n", + "result = pipe(f\"[INST] {prompt} [/INST]\")\n", + "print(result[0]['generated_text'])" + ] + }, + { + "cell_type": "markdown", + "id": "e1fabff4-1058-4de0-9f74-a7610bcd9cb4", + "metadata": {}, + "source": [ + "## Store the trained model\n", + "\n", + "How can we store our new llama-2-7b-test-finance model now? We need to merge the weights from LoRA with the base model. Unfortunately, as far as I know, there is no straightforward way to do it: we need to reload the base model in FP16 precision and use the peft library to merge everything. Alas, it also creates a problem with the VRAM (despite emptying it), so I recommend restarting the notebook, re-executing the three first cells, and then executing the next one." + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "d1b48bd5-f833-426a-a2a3-db121d5c9820", + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "c131b29dacb64ae7b762554ff087ed4c", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Loading checkpoint shards: 0%| | 0/2 [00:00 2\u001b[0m base_model \u001b[38;5;241m=\u001b[39m \u001b[43mAutoModelForCausalLM\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfrom_pretrained\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 3\u001b[0m \u001b[43m \u001b[49m\u001b[43mmodel_name\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 4\u001b[0m \u001b[43m \u001b[49m\u001b[43mlow_cpu_mem_usage\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m 5\u001b[0m \u001b[43m \u001b[49m\u001b[43mreturn_dict\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m 6\u001b[0m \u001b[43m \u001b[49m\u001b[43mtorch_dtype\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtorch\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfloat16\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 7\u001b[0m \u001b[43m \u001b[49m\u001b[43mdevice_map\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdevice_map\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 8\u001b[0m \u001b[43m)\u001b[49m\n\u001b[1;32m 9\u001b[0m model \u001b[38;5;241m=\u001b[39m PeftModel\u001b[38;5;241m.\u001b[39mfrom_pretrained(base_model, new_model)\n\u001b[1;32m 10\u001b[0m model \u001b[38;5;241m=\u001b[39m model\u001b[38;5;241m.\u001b[39mmerge_and_unload()\n", + "File \u001b[0;32m/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/transformers/models/auto/auto_factory.py:493\u001b[0m, in \u001b[0;36m_BaseAutoModelClass.from_pretrained\u001b[0;34m(cls, pretrained_model_name_or_path, *model_args, **kwargs)\u001b[0m\n\u001b[1;32m 491\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28mtype\u001b[39m(config) \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mcls\u001b[39m\u001b[38;5;241m.\u001b[39m_model_mapping\u001b[38;5;241m.\u001b[39mkeys():\n\u001b[1;32m 492\u001b[0m model_class \u001b[38;5;241m=\u001b[39m _get_model_class(config, \u001b[38;5;28mcls\u001b[39m\u001b[38;5;241m.\u001b[39m_model_mapping)\n\u001b[0;32m--> 493\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mmodel_class\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfrom_pretrained\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 494\u001b[0m \u001b[43m \u001b[49m\u001b[43mpretrained_model_name_or_path\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mmodel_args\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mconfig\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mconfig\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mhub_kwargs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\n\u001b[1;32m 495\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 496\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[1;32m 497\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mUnrecognized configuration class \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mconfig\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__class__\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m for this kind of AutoModel: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mcls\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m.\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 498\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mModel type should be one of \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m, \u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;241m.\u001b[39mjoin(c\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mfor\u001b[39;00m\u001b[38;5;250m \u001b[39mc\u001b[38;5;250m \u001b[39m\u001b[38;5;129;01min\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28mcls\u001b[39m\u001b[38;5;241m.\u001b[39m_model_mapping\u001b[38;5;241m.\u001b[39mkeys())\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 499\u001b[0m )\n", + "File \u001b[0;32m/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/transformers/modeling_utils.py:2903\u001b[0m, in \u001b[0;36mPreTrainedModel.from_pretrained\u001b[0;34m(cls, pretrained_model_name_or_path, config, cache_dir, ignore_mismatched_sizes, force_download, local_files_only, token, revision, use_safetensors, *model_args, **kwargs)\u001b[0m\n\u001b[1;32m 2893\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m dtype_orig \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 2894\u001b[0m torch\u001b[38;5;241m.\u001b[39mset_default_dtype(dtype_orig)\n\u001b[1;32m 2896\u001b[0m (\n\u001b[1;32m 2897\u001b[0m model,\n\u001b[1;32m 2898\u001b[0m missing_keys,\n\u001b[1;32m 2899\u001b[0m unexpected_keys,\n\u001b[1;32m 2900\u001b[0m mismatched_keys,\n\u001b[1;32m 2901\u001b[0m offload_index,\n\u001b[1;32m 2902\u001b[0m error_msgs,\n\u001b[0;32m-> 2903\u001b[0m ) \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mcls\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_load_pretrained_model\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 2904\u001b[0m \u001b[43m \u001b[49m\u001b[43mmodel\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 2905\u001b[0m \u001b[43m \u001b[49m\u001b[43mstate_dict\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 2906\u001b[0m \u001b[43m \u001b[49m\u001b[43mloaded_state_dict_keys\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;66;43;03m# XXX: rename?\u001b[39;49;00m\n\u001b[1;32m 2907\u001b[0m \u001b[43m \u001b[49m\u001b[43mresolved_archive_file\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 2908\u001b[0m \u001b[43m \u001b[49m\u001b[43mpretrained_model_name_or_path\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 2909\u001b[0m \u001b[43m \u001b[49m\u001b[43mignore_mismatched_sizes\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mignore_mismatched_sizes\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 2910\u001b[0m \u001b[43m \u001b[49m\u001b[43msharded_metadata\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43msharded_metadata\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 2911\u001b[0m \u001b[43m \u001b[49m\u001b[43m_fast_init\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m_fast_init\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 2912\u001b[0m \u001b[43m \u001b[49m\u001b[43mlow_cpu_mem_usage\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mlow_cpu_mem_usage\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 2913\u001b[0m \u001b[43m \u001b[49m\u001b[43mdevice_map\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdevice_map\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 2914\u001b[0m \u001b[43m \u001b[49m\u001b[43moffload_folder\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43moffload_folder\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 2915\u001b[0m \u001b[43m \u001b[49m\u001b[43moffload_state_dict\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43moffload_state_dict\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 2916\u001b[0m \u001b[43m \u001b[49m\u001b[43mdtype\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtorch_dtype\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 2917\u001b[0m \u001b[43m \u001b[49m\u001b[43mis_quantized\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mload_in_8bit\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01mor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mload_in_4bit\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 2918\u001b[0m \u001b[43m \u001b[49m\u001b[43mkeep_in_fp32_modules\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mkeep_in_fp32_modules\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 2919\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 2921\u001b[0m model\u001b[38;5;241m.\u001b[39mis_loaded_in_4bit \u001b[38;5;241m=\u001b[39m load_in_4bit\n\u001b[1;32m 2922\u001b[0m model\u001b[38;5;241m.\u001b[39mis_loaded_in_8bit \u001b[38;5;241m=\u001b[39m load_in_8bit\n", + "File \u001b[0;32m/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/transformers/modeling_utils.py:3260\u001b[0m, in \u001b[0;36mPreTrainedModel._load_pretrained_model\u001b[0;34m(cls, model, state_dict, loaded_keys, resolved_archive_file, pretrained_model_name_or_path, ignore_mismatched_sizes, sharded_metadata, _fast_init, low_cpu_mem_usage, device_map, offload_folder, offload_state_dict, dtype, is_quantized, keep_in_fp32_modules)\u001b[0m\n\u001b[1;32m 3250\u001b[0m mismatched_keys \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m _find_mismatched_keys(\n\u001b[1;32m 3251\u001b[0m state_dict,\n\u001b[1;32m 3252\u001b[0m model_state_dict,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 3256\u001b[0m ignore_mismatched_sizes,\n\u001b[1;32m 3257\u001b[0m )\n\u001b[1;32m 3259\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m low_cpu_mem_usage:\n\u001b[0;32m-> 3260\u001b[0m new_error_msgs, offload_index, state_dict_index \u001b[38;5;241m=\u001b[39m \u001b[43m_load_state_dict_into_meta_model\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 3261\u001b[0m \u001b[43m \u001b[49m\u001b[43mmodel_to_load\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 3262\u001b[0m \u001b[43m \u001b[49m\u001b[43mstate_dict\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 3263\u001b[0m \u001b[43m \u001b[49m\u001b[43mloaded_keys\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 3264\u001b[0m \u001b[43m \u001b[49m\u001b[43mstart_prefix\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 3265\u001b[0m \u001b[43m \u001b[49m\u001b[43mexpected_keys\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 3266\u001b[0m \u001b[43m \u001b[49m\u001b[43mdevice_map\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdevice_map\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 3267\u001b[0m \u001b[43m \u001b[49m\u001b[43moffload_folder\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43moffload_folder\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 3268\u001b[0m \u001b[43m \u001b[49m\u001b[43moffload_index\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43moffload_index\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 3269\u001b[0m \u001b[43m \u001b[49m\u001b[43mstate_dict_folder\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstate_dict_folder\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 3270\u001b[0m \u001b[43m \u001b[49m\u001b[43mstate_dict_index\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstate_dict_index\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 3271\u001b[0m \u001b[43m \u001b[49m\u001b[43mdtype\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdtype\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 3272\u001b[0m \u001b[43m \u001b[49m\u001b[43mis_quantized\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mis_quantized\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 3273\u001b[0m \u001b[43m \u001b[49m\u001b[43mis_safetensors\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mis_safetensors\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 3274\u001b[0m \u001b[43m \u001b[49m\u001b[43mkeep_in_fp32_modules\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mkeep_in_fp32_modules\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 3275\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 3276\u001b[0m error_msgs \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m new_error_msgs\n\u001b[1;32m 3277\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n", + "File \u001b[0;32m/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/transformers/modeling_utils.py:717\u001b[0m, in \u001b[0;36m_load_state_dict_into_meta_model\u001b[0;34m(model, state_dict, loaded_state_dict_keys, start_prefix, expected_keys, device_map, offload_folder, offload_index, state_dict_folder, state_dict_index, dtype, is_quantized, is_safetensors, keep_in_fp32_modules)\u001b[0m\n\u001b[1;32m 714\u001b[0m state_dict_index \u001b[38;5;241m=\u001b[39m offload_weight(param, param_name, state_dict_folder, state_dict_index)\n\u001b[1;32m 715\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m is_quantized:\n\u001b[1;32m 716\u001b[0m \u001b[38;5;66;03m# For backward compatibility with older versions of `accelerate`\u001b[39;00m\n\u001b[0;32m--> 717\u001b[0m \u001b[43mset_module_tensor_to_device\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmodel\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mparam_name\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mparam_device\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mset_module_kwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 718\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 719\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m param\u001b[38;5;241m.\u001b[39mdtype \u001b[38;5;241m==\u001b[39m torch\u001b[38;5;241m.\u001b[39mint8 \u001b[38;5;129;01mand\u001b[39;00m param_name\u001b[38;5;241m.\u001b[39mreplace(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mweight\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mSCB\u001b[39m\u001b[38;5;124m\"\u001b[39m) \u001b[38;5;129;01min\u001b[39;00m state_dict\u001b[38;5;241m.\u001b[39mkeys():\n", + "File \u001b[0;32m/mnt/e/github/my/finetune/.venv/lib/python3.10/site-packages/accelerate/utils/modeling.py:298\u001b[0m, in \u001b[0;36mset_module_tensor_to_device\u001b[0;34m(module, tensor_name, device, value, dtype, fp16_statistics)\u001b[0m\n\u001b[1;32m 296\u001b[0m module\u001b[38;5;241m.\u001b[39m_parameters[tensor_name] \u001b[38;5;241m=\u001b[39m param_cls(new_value, requires_grad\u001b[38;5;241m=\u001b[39mold_value\u001b[38;5;241m.\u001b[39mrequires_grad)\n\u001b[1;32m 297\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(value, torch\u001b[38;5;241m.\u001b[39mTensor):\n\u001b[0;32m--> 298\u001b[0m new_value \u001b[38;5;241m=\u001b[39m \u001b[43mvalue\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mto\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdevice\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 299\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 300\u001b[0m new_value \u001b[38;5;241m=\u001b[39m torch\u001b[38;5;241m.\u001b[39mtensor(value, device\u001b[38;5;241m=\u001b[39mdevice)\n", + "\u001b[0;31mOutOfMemoryError\u001b[0m: CUDA out of memory. Tried to allocate 86.00 MiB. GPU 0 has a total capacity of 10.00 GiB of which 0 bytes is free. Including non-PyTorch memory, this process has 17179869184.00 GiB memory in use. Of the allocated memory 16.11 GiB is allocated by PyTorch, and 128.01 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)" + ] + } + ], + "source": [ + "# Reload model in FP16 and merge it with LoRA weights\n", + "base_model = AutoModelForCausalLM.from_pretrained(\n", + " model_name,\n", + " low_cpu_mem_usage=True,\n", + " return_dict=True,\n", + " torch_dtype=torch.float16,\n", + " device_map=device_map,\n", + ")\n", + "model = PeftModel.from_pretrained(base_model, new_model)\n", + "model = model.merge_and_unload()\n", + "\n", + "# Reload tokenizer to save it\n", + "tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)\n", + "tokenizer.pad_token = tokenizer.eos_token\n", + "tokenizer.padding_side = \"right\"" + ] + }, + { + "cell_type": "markdown", + "id": "0a4af587-ab15-40ad-8343-fe3354d9febf", + "metadata": {}, + "source": [ + "## Push to HF\n", + "\n", + "Our weights are merged and we reloaded the tokenizer. We can now push everything to the Hugging Face Hub to save our model." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "261ff374-9f5e-4c71-bbe6-c12c3dd1df51", + "metadata": {}, + "outputs": [], + "source": [ + "model.push_to_hub(new_model, use_temp_dir=False)\n", + "tokenizer.push_to_hub(new_model, use_temp_dir=False)" + ] + }, + { + "cell_type": "markdown", + "id": "c76d3650-75e2-4c32-a2e3-88f6490790a3", + "metadata": {}, + "source": [ + "## Acknowledgements\n", + "\n", + "This example is greatly inspired by Maxime Labonne @mlabonne and his great blog post https://mlabonne.github.io/blog/posts/Fine_Tune_Your_Own_Llama_2_Model_in_a_Colab_Notebook.html " + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.12" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} From 20f8cf8c28beeb68edb2dd9b0f6c5cabb6666817 Mon Sep 17 00:00:00 2001 From: jazelly Date: Mon, 22 Apr 2024 16:15:17 +0930 Subject: [PATCH 02/96] restructure --- README.md | 40 ++++++++++ .../notebook/sft_qlora.ipynb | 15 ++-- llama2/requirements.txt | 9 +++ llama2/script/sft.py | 80 +++++++++++++++++++ llama2/script/utils.py | 27 +++++++ 5 files changed, 163 insertions(+), 8 deletions(-) rename finetune_llama2_7b_qlora.ipynb => llama2/notebook/sft_qlora.ipynb (99%) create mode 100644 llama2/requirements.txt create mode 100644 llama2/script/sft.py create mode 100644 llama2/script/utils.py diff --git a/README.md b/README.md index dbe19fb..5536f96 100644 --- a/README.md +++ b/README.md @@ -1,2 +1,42 @@ # FinetuneLLMs Collections of all kinds of LLMs finetuning scripts + +## Installation dependencies + +### Install pytorch + +The easist way to do this is via conda. If you don't have conda, please go to [the installation guide](https://conda.io/projects/conda/en/latest/user-guide/install/index.html) + +``` +conda install pytorch torchvision torchaudio pytorch-cuda=11.7 -c pytorch -c nvidia +``` + +If you don't want to use conda, I recommend virtual env for different LLMs, as they have different requirements + +#### For Linux + +Install CUDA from [Nvidia installation guide](https://docs.nvidia.com/cuda/cuda-installation-guide-linux/) + +``` +cd llama2 +python3 -m venv .llama2 +source ./.llama2/bin/activate +pip3 install torch +pip3 install -r requirements.txt +``` + +#### For Windows + +Enable WSL2 on your machine +Install CUDA inside WSL by followwing the Linux guide. + + +#### For Mac + +Incoming, with mlx + + +## Usage + +LLM scripts are categorized by their names. Under each, you will see `notebook/`, for `jupyter notebook`, and `script/`, for `python` scripts. They should share same dependencies. +The training dataset or logic, however, might not be the same, as the purpose of this repo is to share various different examples of finetuning scripts so you can grasp the ideas. \ No newline at end of file diff --git a/finetune_llama2_7b_qlora.ipynb b/llama2/notebook/sft_qlora.ipynb similarity index 99% rename from finetune_llama2_7b_qlora.ipynb rename to llama2/notebook/sft_qlora.ipynb index c484134..6d01cb1 100644 --- a/finetune_llama2_7b_qlora.ipynb +++ b/llama2/notebook/sft_qlora.ipynb @@ -15,14 +15,13 @@ "\n", "Make sure you have the following requirements\n", "```\n", - "bitsandbytes==0.40.2\n", - "accelerate==0.21.0\n", - "peft==0.4.0\n", - "trl==0.4.7\n", - "datasets==2.17.0\n", - "transformers==4.31.0\n", - "```\n", - "Of course, as usual, you will need `torch` and `torchvision`" + "bitsandbytes>=0.40.2\n", + "accelerate>=0.21.0\n", + "peft>=0.4.0\n", + "trl>=0.4.7\n", + "datasets>=2.17.0\n", + "transformers>=4.31.0\n", + "```" ] }, { diff --git a/llama2/requirements.txt b/llama2/requirements.txt new file mode 100644 index 0000000..22cf563 --- /dev/null +++ b/llama2/requirements.txt @@ -0,0 +1,9 @@ +transformers +trl +peft +accelerate +datasets +bitsandbytes +scipy +sentencepiece +gradio \ No newline at end of file diff --git a/llama2/script/sft.py b/llama2/script/sft.py new file mode 100644 index 0000000..c1ce41c --- /dev/null +++ b/llama2/script/sft.py @@ -0,0 +1,80 @@ +import os +import torch + +from transformers import AutoModelForCausalLM, AutoTokenizer, TrainingArguments,BitsAndBytesConfig +from datasets import load_dataset +from trl import SFTTrainer +from peft import AutoPeftModelForCausalLM, LoraConfig, get_peft_model, prepare_model_for_kbit_training +from utils import find_all_linear_names, print_trainable_parameters + +output_dir="./results" +model_name ="NousResearch/Llama-2-7b-hf" + +dataset = load_dataset("json", data_files="conversations.json",split="train") + +bnb_config = BitsAndBytesConfig( + load_in_4bit=True, + bnb_4bit_quant_type="nf4", + bnb_4bit_compute_dtype=torch.bfloat16, +) + +base_model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, quantization_config=bnb_config) +base_model.config.use_cache = False +base_model = prepare_model_for_kbit_training(base_model) + +tokenizer = AutoTokenizer.from_pretrained(model_name) +tokenizer.pad_token = tokenizer.eos_token +tokenizer.padding_side = "right" # Fix weird overflow issue with fp16 training + +# Change the LORA hyperparameters accordingly to fit your use case +peft_config = LoraConfig( + r=128, + lora_alpha=16, + target_modules=find_all_linear_names(base_model), + lora_dropout=0.05, + bias="none", + task_type="CAUSAL_LM", +) + +base_model = get_peft_model(base_model, peft_config) +print_trainable_parameters(base_model) + +def formatting_prompts_func(example): + output_texts = [] + for i in range(len(example['prompt'])): + text = f"An AI tool that corrects and rephrase user text grammar errors delimited by triple backticks to standard English.\n### Input: ```{example['prompt'][i]}```\n ### Output: {example['completion'][i]}" + output_texts.append(text) + return output_texts + +# Parameters for training arguments details => https://github.com/huggingface/transformers/blob/main/src/transformers/training_args.py#L158 +training_args = TrainingArguments( + per_device_train_batch_size=4, + gradient_accumulation_steps=4, + gradient_checkpointing =True, + max_grad_norm= 0.3, + num_train_epochs=15, + learning_rate=2e-4, + bf16=True, + save_total_limit=3, + logging_steps=10, + output_dir=output_dir, + optim="paged_adamw_32bit", + lr_scheduler_type="cosine", + warmup_ratio=0.05, +) + +trainer = SFTTrainer( + base_model, + train_dataset=dataset, + tokenizer=tokenizer, + max_seq_length=2048, + formatting_func=formatting_prompts_func, + args=training_args +) + +trainer.train() +trainer.save_model(output_dir) + +output_dir = os.path.join(output_dir, "final_checkpoint") +trainer.model.save_pretrained(output_dir) +tokenizer.save_pretrained(output_dir) \ No newline at end of file diff --git a/llama2/script/utils.py b/llama2/script/utils.py new file mode 100644 index 0000000..5022698 --- /dev/null +++ b/llama2/script/utils.py @@ -0,0 +1,27 @@ +import torch +import bitsandbytes as bnb + +def find_all_linear_names(model): + cls = bnb.nn.Linear4bit + lora_module_names = set() + for name, module in model.named_modules(): + if isinstance(module, cls): + names = name.split('.') + lora_module_names.add(names[0] if len(names) == 1 else names[-1]) + + return list(lora_module_names) + + +def print_trainable_parameters(model): + """ + Prints the number of trainable parameters in the model. + """ + trainable_params = 0 + all_param = 0 + for _, param in model.named_parameters(): + all_param += param.numel() + if param.requires_grad: + trainable_params += param.numel() + print( + f"trainable params: {trainable_params} | all params: {all_param} | trainables%: {100 * trainable_params / all_param}" + ) \ No newline at end of file From b3f60333f687711b216b098a3a17e333baee2b58 Mon Sep 17 00:00:00 2001 From: jazelly Date: Thu, 25 Apr 2024 09:34:04 +0930 Subject: [PATCH 03/96] feat: add llama3 and phi3 --- .gitignore | 3 + README.md | 21 ++- llama3/notebook/orpo_dpo.ipynb | 313 +++++++++++++++++++++++++++++++++ llama3/requirements.txt | 6 + phi3/requirements.txt | 3 + phi3/script/sft.py | 129 ++++++++++++++ 6 files changed, 471 insertions(+), 4 deletions(-) create mode 100644 llama3/notebook/orpo_dpo.ipynb create mode 100644 llama3/requirements.txt create mode 100644 phi3/requirements.txt create mode 100644 phi3/script/sft.py diff --git a/.gitignore b/.gitignore index 68bc17f..76523d7 100644 --- a/.gitignore +++ b/.gitignore @@ -127,6 +127,7 @@ venv/ ENV/ env.bak/ venv.bak/ +*/.venv # Spyder project settings .spyderproject @@ -158,3 +159,5 @@ cython_debug/ # and can be added to the global gitignore or merged into this file. For a more nuclear # option (not recommended) you can uncomment the following to ignore the entire idea folder. #.idea/ + +results/ \ No newline at end of file diff --git a/README.md b/README.md index 5536f96..7045ca3 100644 --- a/README.md +++ b/README.md @@ -1,7 +1,11 @@ # FinetuneLLMs Collections of all kinds of LLMs finetuning scripts -## Installation dependencies +This repo aims to provide the finest collection of all tuning scripts that can be easily accessed by anyone. + +Every training script in this repo is tested across multiple platforms. + +## Install dependencies ### Install pytorch @@ -27,8 +31,9 @@ pip3 install -r requirements.txt #### For Windows -Enable WSL2 on your machine -Install CUDA inside WSL by followwing the Linux guide. +Enable WSL2 on your machine. + +Install CUDA inside WSL by following the Linux guide. #### For Mac @@ -39,4 +44,12 @@ Incoming, with mlx ## Usage LLM scripts are categorized by their names. Under each, you will see `notebook/`, for `jupyter notebook`, and `script/`, for `python` scripts. They should share same dependencies. -The training dataset or logic, however, might not be the same, as the purpose of this repo is to share various different examples of finetuning scripts so you can grasp the ideas. \ No newline at end of file +The training dataset or logic, however, might not be the same, as the purpose of this repo is to share various different examples of finetuning scripts so you can grasp the ideas. + + +## TODO + +- [ ] Try training at GGML and GGUF level +- [ ] Explore OLLAMA +- [ ] Explore mlx examples +- [ ] Explore Finetuning Model in LangChain with OLLAMA \ No newline at end of file diff --git a/llama3/notebook/orpo_dpo.ipynb b/llama3/notebook/orpo_dpo.ipynb new file mode 100644 index 0000000..dabf7ed --- /dev/null +++ b/llama3/notebook/orpo_dpo.ipynb @@ -0,0 +1,313 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 13, + "id": "a09aefb6-e591-44d7-9fea-506fa5874f34", + "metadata": {}, + "outputs": [], + "source": [ + "import gc\n", + "import os\n", + "\n", + "import torch\n", + "from datasets import load_dataset\n", + "# from google.colab import userdata\n", + "from peft import LoraConfig, PeftModel, prepare_model_for_kbit_training\n", + "from transformers import (\n", + " AutoModelForCausalLM,\n", + " AutoTokenizer,\n", + " BitsAndBytesConfig,\n", + " TrainingArguments,\n", + " pipeline,\n", + ")\n", + "from trl import ORPOConfig, ORPOTrainer, setup_chat_format" + ] + }, + { + "cell_type": "markdown", + "id": "e92a0dd5-a9f7-495b-95ad-9624ca8d3f6f", + "metadata": {}, + "source": [ + "Flash attention is not stable. I encountered an issue with `NameError: name 'index_first_axis' is not defined`, and the only resolution was to not use flash attention. If you know the fix. please contact me or raise an issue." + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "5f139bc1-f5c6-44a6-8c22-337303f1a6f4", + "metadata": {}, + "outputs": [], + "source": [ + "attn_implementation = \"eager\"\n", + "torch_dtype = torch.float16" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "6776fea8-1a1a-4fec-aec5-8e6603e62904", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n" + ] + }, + { + "ename": "ValueError", + "evalue": "\n Some modules are dispatched on the CPU or the disk. Make sure you have enough GPU RAM to fit the\n quantized model. If you want to dispatch the model on the CPU or the disk while keeping these modules\n in 32-bit, you need to set `llm_int8_enable_fp32_cpu_offload=True` and pass a custom `device_map` to\n `from_pretrained`. Check\n https://huggingface.co/docs/transformers/main/en/main_classes/quantization#offload-between-cpu-and-gpu\n for more details.\n ", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[15], line 27\u001b[0m\n\u001b[1;32m 24\u001b[0m tokenizer \u001b[38;5;241m=\u001b[39m AutoTokenizer\u001b[38;5;241m.\u001b[39mfrom_pretrained(base_model)\n\u001b[1;32m 26\u001b[0m \u001b[38;5;66;03m# Load model\u001b[39;00m\n\u001b[0;32m---> 27\u001b[0m model \u001b[38;5;241m=\u001b[39m \u001b[43mAutoModelForCausalLM\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfrom_pretrained\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 28\u001b[0m \u001b[43m \u001b[49m\u001b[43mbase_model\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 29\u001b[0m \u001b[43m \u001b[49m\u001b[43mquantization_config\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mbnb_config\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 30\u001b[0m \u001b[43m \u001b[49m\u001b[43mdevice_map\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mauto\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 31\u001b[0m \u001b[43m \u001b[49m\u001b[43mattn_implementation\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mattn_implementation\u001b[49m\n\u001b[1;32m 32\u001b[0m \u001b[43m)\u001b[49m\n\u001b[1;32m 33\u001b[0m model, tokenizer \u001b[38;5;241m=\u001b[39m setup_chat_format(model, tokenizer)\n\u001b[1;32m 34\u001b[0m model \u001b[38;5;241m=\u001b[39m prepare_model_for_kbit_training(model)\n", + "File \u001b[0;32m~/anaconda3/envs/llama3/lib/python3.10/site-packages/transformers/models/auto/auto_factory.py:563\u001b[0m, in \u001b[0;36m_BaseAutoModelClass.from_pretrained\u001b[0;34m(cls, pretrained_model_name_or_path, *model_args, **kwargs)\u001b[0m\n\u001b[1;32m 561\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28mtype\u001b[39m(config) \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mcls\u001b[39m\u001b[38;5;241m.\u001b[39m_model_mapping\u001b[38;5;241m.\u001b[39mkeys():\n\u001b[1;32m 562\u001b[0m model_class \u001b[38;5;241m=\u001b[39m _get_model_class(config, \u001b[38;5;28mcls\u001b[39m\u001b[38;5;241m.\u001b[39m_model_mapping)\n\u001b[0;32m--> 563\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mmodel_class\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfrom_pretrained\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 564\u001b[0m \u001b[43m \u001b[49m\u001b[43mpretrained_model_name_or_path\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mmodel_args\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mconfig\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mconfig\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mhub_kwargs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\n\u001b[1;32m 565\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 566\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[1;32m 567\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mUnrecognized configuration class \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mconfig\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__class__\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m for this kind of AutoModel: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mcls\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m.\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 568\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mModel type should be one of \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m, \u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;241m.\u001b[39mjoin(c\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mfor\u001b[39;00m\u001b[38;5;250m \u001b[39mc\u001b[38;5;250m \u001b[39m\u001b[38;5;129;01min\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28mcls\u001b[39m\u001b[38;5;241m.\u001b[39m_model_mapping\u001b[38;5;241m.\u001b[39mkeys())\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 569\u001b[0m )\n", + "File \u001b[0;32m~/anaconda3/envs/llama3/lib/python3.10/site-packages/transformers/modeling_utils.py:3627\u001b[0m, in \u001b[0;36mPreTrainedModel.from_pretrained\u001b[0;34m(cls, pretrained_model_name_or_path, config, cache_dir, ignore_mismatched_sizes, force_download, local_files_only, token, revision, use_safetensors, *model_args, **kwargs)\u001b[0m\n\u001b[1;32m 3624\u001b[0m device_map \u001b[38;5;241m=\u001b[39m infer_auto_device_map(model, dtype\u001b[38;5;241m=\u001b[39mtarget_dtype, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mdevice_map_kwargs)\n\u001b[1;32m 3626\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m hf_quantizer \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m-> 3627\u001b[0m \u001b[43mhf_quantizer\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mvalidate_environment\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdevice_map\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdevice_map\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 3629\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m device_map \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 3630\u001b[0m model\u001b[38;5;241m.\u001b[39mtie_weights()\n", + "File \u001b[0;32m~/anaconda3/envs/llama3/lib/python3.10/site-packages/transformers/quantizers/quantizer_bnb_4bit.py:86\u001b[0m, in \u001b[0;36mBnb4BitHfQuantizer.validate_environment\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 82\u001b[0m device_map_without_lm_head \u001b[38;5;241m=\u001b[39m {\n\u001b[1;32m 83\u001b[0m key: device_map[key] \u001b[38;5;28;01mfor\u001b[39;00m key \u001b[38;5;129;01min\u001b[39;00m device_map\u001b[38;5;241m.\u001b[39mkeys() \u001b[38;5;28;01mif\u001b[39;00m key \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmodules_to_not_convert\n\u001b[1;32m 84\u001b[0m }\n\u001b[1;32m 85\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcpu\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;129;01min\u001b[39;00m device_map_without_lm_head\u001b[38;5;241m.\u001b[39mvalues() \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mdisk\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;129;01min\u001b[39;00m device_map_without_lm_head\u001b[38;5;241m.\u001b[39mvalues():\n\u001b[0;32m---> 86\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[1;32m 87\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 88\u001b[0m \u001b[38;5;124;03m Some modules are dispatched on the CPU or the disk. Make sure you have enough GPU RAM to fit the\u001b[39;00m\n\u001b[1;32m 89\u001b[0m \u001b[38;5;124;03m quantized model. If you want to dispatch the model on the CPU or the disk while keeping these modules\u001b[39;00m\n\u001b[1;32m 90\u001b[0m \u001b[38;5;124;03m in 32-bit, you need to set `llm_int8_enable_fp32_cpu_offload=True` and pass a custom `device_map` to\u001b[39;00m\n\u001b[1;32m 91\u001b[0m \u001b[38;5;124;03m `from_pretrained`. Check\u001b[39;00m\n\u001b[1;32m 92\u001b[0m \u001b[38;5;124;03m https://huggingface.co/docs/transformers/main/en/main_classes/quantization#offload-between-cpu-and-gpu\u001b[39;00m\n\u001b[1;32m 93\u001b[0m \u001b[38;5;124;03m for more details.\u001b[39;00m\n\u001b[1;32m 94\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[1;32m 95\u001b[0m )\n\u001b[1;32m 97\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m version\u001b[38;5;241m.\u001b[39mparse(importlib\u001b[38;5;241m.\u001b[39mmetadata\u001b[38;5;241m.\u001b[39mversion(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mbitsandbytes\u001b[39m\u001b[38;5;124m\"\u001b[39m)) \u001b[38;5;241m<\u001b[39m version\u001b[38;5;241m.\u001b[39mparse(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m0.39.0\u001b[39m\u001b[38;5;124m\"\u001b[39m):\n\u001b[1;32m 98\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[1;32m 99\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mYou have a version of `bitsandbytes` that is not compatible with 4bit inference and training\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 100\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m make sure you have the latest version of `bitsandbytes` installed\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 101\u001b[0m )\n", + "\u001b[0;31mValueError\u001b[0m: \n Some modules are dispatched on the CPU or the disk. Make sure you have enough GPU RAM to fit the\n quantized model. If you want to dispatch the model on the CPU or the disk while keeping these modules\n in 32-bit, you need to set `llm_int8_enable_fp32_cpu_offload=True` and pass a custom `device_map` to\n `from_pretrained`. Check\n https://huggingface.co/docs/transformers/main/en/main_classes/quantization#offload-between-cpu-and-gpu\n for more details.\n " + ] + } + ], + "source": [ + "# Model\n", + "base_model = \"NousResearch/Meta-Llama-3-8B\"\n", + "new_model = \"OrpoLlama-3-8B\"\n", + "\n", + "# QLoRA config\n", + "bnb_config = BitsAndBytesConfig(\n", + " load_in_4bit=True,\n", + " bnb_4bit_quant_type=\"nf4\",\n", + " bnb_4bit_compute_dtype=torch_dtype,\n", + " bnb_4bit_use_double_quant=True,\n", + ")\n", + "\n", + "# LoRA config\n", + "peft_config = LoraConfig(\n", + " r=16,\n", + " lora_alpha=32,\n", + " lora_dropout=0.05,\n", + " bias=\"none\",\n", + " task_type=\"CAUSAL_LM\",\n", + " target_modules=['up_proj', 'down_proj', 'gate_proj', 'k_proj', 'q_proj', 'v_proj', 'o_proj']\n", + ")\n", + "\n", + "# Load tokenizer\n", + "tokenizer = AutoTokenizer.from_pretrained(base_model)\n", + "\n", + "# Load model\n", + "model = AutoModelForCausalLM.from_pretrained(\n", + " base_model,\n", + " quantization_config=bnb_config,\n", + " device_map=\"auto\",\n", + " attn_implementation=attn_implementation\n", + ")\n", + "model, tokenizer = setup_chat_format(model, tokenizer)\n", + "model = prepare_model_for_kbit_training(model)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "db4031a9-fcb1-4295-a9b7-1db11a753939", + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "5e41c9fc89cd476ea844f9076855f2ab", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Downloading data: 0%| | 0.00/115M [00:00 27\u001b[0m \u001b[43mtrainer\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtrain\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 28\u001b[0m trainer\u001b[38;5;241m.\u001b[39msave_model(new_model)\n", + "File \u001b[0;32m~/anaconda3/envs/llama3/lib/python3.10/site-packages/transformers/trainer.py:1859\u001b[0m, in \u001b[0;36mTrainer.train\u001b[0;34m(self, resume_from_checkpoint, trial, ignore_keys_for_eval, **kwargs)\u001b[0m\n\u001b[1;32m 1857\u001b[0m hf_hub_utils\u001b[38;5;241m.\u001b[39menable_progress_bars()\n\u001b[1;32m 1858\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 1859\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43minner_training_loop\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 1860\u001b[0m \u001b[43m \u001b[49m\u001b[43margs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1861\u001b[0m \u001b[43m \u001b[49m\u001b[43mresume_from_checkpoint\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mresume_from_checkpoint\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1862\u001b[0m \u001b[43m \u001b[49m\u001b[43mtrial\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtrial\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1863\u001b[0m \u001b[43m 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simply add the average of previous logged losses\u001b[39;00m\n\u001b[1;32m 2211\u001b[0m tr_loss \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m tr_loss \u001b[38;5;241m/\u001b[39m (\u001b[38;5;241m1\u001b[39m \u001b[38;5;241m+\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mstate\u001b[38;5;241m.\u001b[39mglobal_step \u001b[38;5;241m-\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_globalstep_last_logged)\n", + "File \u001b[0;32m~/anaconda3/envs/llama3/lib/python3.10/site-packages/transformers/trainer.py:3138\u001b[0m, in \u001b[0;36mTrainer.training_step\u001b[0;34m(self, model, inputs)\u001b[0m\n\u001b[1;32m 3135\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m loss_mb\u001b[38;5;241m.\u001b[39mreduce_mean()\u001b[38;5;241m.\u001b[39mdetach()\u001b[38;5;241m.\u001b[39mto(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39margs\u001b[38;5;241m.\u001b[39mdevice)\n\u001b[1;32m 3137\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m 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return_outputs)\u001b[0m\n\u001b[1;32m 783\u001b[0m compute_loss_context_manager \u001b[38;5;241m=\u001b[39m torch\u001b[38;5;241m.\u001b[39mcuda\u001b[38;5;241m.\u001b[39mamp\u001b[38;5;241m.\u001b[39mautocast \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_peft_has_been_casted_to_bf16 \u001b[38;5;28;01melse\u001b[39;00m nullcontext\n\u001b[1;32m 785\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m compute_loss_context_manager():\n\u001b[0;32m--> 786\u001b[0m loss, metrics \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_batch_loss_metrics\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmodel\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43minputs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtrain_eval\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mtrain\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m 788\u001b[0m \u001b[38;5;66;03m# force log the metrics\u001b[39;00m\n\u001b[1;32m 789\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mstore_metrics(metrics, train_eval\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtrain\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n", + "File \u001b[0;32m~/anaconda3/envs/llama3/lib/python3.10/site-packages/trl/trainer/orpo_trainer.py:746\u001b[0m, in \u001b[0;36mORPOTrainer.get_batch_loss_metrics\u001b[0;34m(self, model, batch, train_eval)\u001b[0m\n\u001b[1;32m 737\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"Compute the ORPO loss and other metrics for the given batch of inputs for train or test.\"\"\"\u001b[39;00m\n\u001b[1;32m 738\u001b[0m metrics \u001b[38;5;241m=\u001b[39m {}\n\u001b[1;32m 740\u001b[0m (\n\u001b[1;32m 741\u001b[0m policy_chosen_logps,\n\u001b[1;32m 742\u001b[0m policy_rejected_logps,\n\u001b[1;32m 743\u001b[0m policy_chosen_logits,\n\u001b[1;32m 744\u001b[0m policy_rejected_logits,\n\u001b[1;32m 745\u001b[0m policy_nll_loss,\n\u001b[0;32m--> 746\u001b[0m ) \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mconcatenated_forward\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmodel\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbatch\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 748\u001b[0m losses, chosen_rewards, rejected_rewards, log_odds_ratio, log_odds_chosen \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39modds_ratio_loss(\n\u001b[1;32m 749\u001b[0m policy_chosen_logps, policy_rejected_logps\n\u001b[1;32m 750\u001b[0m )\n\u001b[1;32m 751\u001b[0m \u001b[38;5;66;03m# full ORPO loss\u001b[39;00m\n", + "File \u001b[0;32m~/anaconda3/envs/llama3/lib/python3.10/site-packages/trl/trainer/orpo_trainer.py:686\u001b[0m, in \u001b[0;36mORPOTrainer.concatenated_forward\u001b[0;34m(self, model, batch)\u001b[0m\n\u001b[1;32m 676\u001b[0m len_chosen \u001b[38;5;241m=\u001b[39m batch[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mchosen_labels\u001b[39m\u001b[38;5;124m\"\u001b[39m]\u001b[38;5;241m.\u001b[39mshape[\u001b[38;5;241m0\u001b[39m]\n\u001b[1;32m 678\u001b[0m model_kwargs \u001b[38;5;241m=\u001b[39m (\n\u001b[1;32m 679\u001b[0m {\n\u001b[1;32m 680\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mdecoder_input_ids\u001b[39m\u001b[38;5;124m\"\u001b[39m: \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_shift_right(concatenated_batch[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mconcatenated_labels\u001b[39m\u001b[38;5;124m\"\u001b[39m]),\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 683\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m {}\n\u001b[1;32m 684\u001b[0m )\n\u001b[0;32m--> 686\u001b[0m outputs \u001b[38;5;241m=\u001b[39m \u001b[43mmodel\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 687\u001b[0m \u001b[43m \u001b[49m\u001b[43mconcatenated_batch\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mconcatenated_input_ids\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 688\u001b[0m \u001b[43m \u001b[49m\u001b[43mattention_mask\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mconcatenated_batch\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mconcatenated_attention_mask\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 689\u001b[0m \u001b[43m \u001b[49m\u001b[43muse_cache\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m 690\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mmodel_kwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 691\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 692\u001b[0m all_logits \u001b[38;5;241m=\u001b[39m outputs\u001b[38;5;241m.\u001b[39mlogits\n\u001b[1;32m 694\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mcross_entropy_loss\u001b[39m(logits, labels):\n", + "File \u001b[0;32m~/anaconda3/envs/llama3/lib/python3.10/site-packages/torch/nn/modules/module.py:1518\u001b[0m, in \u001b[0;36mModule._wrapped_call_impl\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 1516\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_compiled_call_impl(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs) \u001b[38;5;66;03m# type: ignore[misc]\u001b[39;00m\n\u001b[1;32m 1517\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 1518\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_call_impl\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/anaconda3/envs/llama3/lib/python3.10/site-packages/torch/nn/modules/module.py:1527\u001b[0m, in \u001b[0;36mModule._call_impl\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 1522\u001b[0m \u001b[38;5;66;03m# If we don't have any hooks, we want to skip the rest of the logic in\u001b[39;00m\n\u001b[1;32m 1523\u001b[0m \u001b[38;5;66;03m# this function, and just call forward.\u001b[39;00m\n\u001b[1;32m 1524\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m (\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_backward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_backward_pre_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_forward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_forward_pre_hooks\n\u001b[1;32m 1525\u001b[0m \u001b[38;5;129;01mor\u001b[39;00m _global_backward_pre_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_backward_hooks\n\u001b[1;32m 1526\u001b[0m \u001b[38;5;129;01mor\u001b[39;00m _global_forward_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_forward_pre_hooks):\n\u001b[0;32m-> 1527\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mforward_call\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1529\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m 1530\u001b[0m result \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n", + "File \u001b[0;32m~/anaconda3/envs/llama3/lib/python3.10/site-packages/peft/peft_model.py:1129\u001b[0m, in \u001b[0;36mPeftModelForCausalLM.forward\u001b[0;34m(self, input_ids, attention_mask, inputs_embeds, labels, output_attentions, output_hidden_states, return_dict, task_ids, **kwargs)\u001b[0m\n\u001b[1;32m 1127\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_enable_peft_forward_hooks(\u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[1;32m 1128\u001b[0m kwargs \u001b[38;5;241m=\u001b[39m {k: v \u001b[38;5;28;01mfor\u001b[39;00m k, v \u001b[38;5;129;01min\u001b[39;00m kwargs\u001b[38;5;241m.\u001b[39mitems() \u001b[38;5;28;01mif\u001b[39;00m k \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mspecial_peft_forward_args}\n\u001b[0;32m-> 1129\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mbase_model\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 1130\u001b[0m \u001b[43m \u001b[49m\u001b[43minput_ids\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43minput_ids\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1131\u001b[0m \u001b[43m \u001b[49m\u001b[43mattention_mask\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mattention_mask\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1132\u001b[0m \u001b[43m \u001b[49m\u001b[43minputs_embeds\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43minputs_embeds\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1133\u001b[0m \u001b[43m \u001b[49m\u001b[43mlabels\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mlabels\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1134\u001b[0m \u001b[43m \u001b[49m\u001b[43moutput_attentions\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43moutput_attentions\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1135\u001b[0m \u001b[43m \u001b[49m\u001b[43moutput_hidden_states\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43moutput_hidden_states\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1136\u001b[0m \u001b[43m \u001b[49m\u001b[43mreturn_dict\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mreturn_dict\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1137\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1138\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1140\u001b[0m batch_size \u001b[38;5;241m=\u001b[39m _get_batch_size(input_ids, inputs_embeds)\n\u001b[1;32m 1141\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m attention_mask \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 1142\u001b[0m \u001b[38;5;66;03m# concat prompt attention mask\u001b[39;00m\n", + "File \u001b[0;32m~/anaconda3/envs/llama3/lib/python3.10/site-packages/torch/nn/modules/module.py:1518\u001b[0m, in \u001b[0;36mModule._wrapped_call_impl\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 1516\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_compiled_call_impl(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs) \u001b[38;5;66;03m# type: ignore[misc]\u001b[39;00m\n\u001b[1;32m 1517\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 1518\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_call_impl\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/anaconda3/envs/llama3/lib/python3.10/site-packages/torch/nn/modules/module.py:1527\u001b[0m, in \u001b[0;36mModule._call_impl\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 1522\u001b[0m \u001b[38;5;66;03m# If we don't have any hooks, we want to skip the rest of the logic in\u001b[39;00m\n\u001b[1;32m 1523\u001b[0m \u001b[38;5;66;03m# this function, and just call forward.\u001b[39;00m\n\u001b[1;32m 1524\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m (\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_backward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_backward_pre_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_forward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_forward_pre_hooks\n\u001b[1;32m 1525\u001b[0m \u001b[38;5;129;01mor\u001b[39;00m _global_backward_pre_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_backward_hooks\n\u001b[1;32m 1526\u001b[0m \u001b[38;5;129;01mor\u001b[39;00m _global_forward_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_forward_pre_hooks):\n\u001b[0;32m-> 1527\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mforward_call\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1529\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m 1530\u001b[0m result \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n", + "File \u001b[0;32m~/anaconda3/envs/llama3/lib/python3.10/site-packages/peft/tuners/tuners_utils.py:161\u001b[0m, in \u001b[0;36mBaseTuner.forward\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 160\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mforward\u001b[39m(\u001b[38;5;28mself\u001b[39m, \u001b[38;5;241m*\u001b[39margs: Any, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs: Any):\n\u001b[0;32m--> 161\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmodel\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mforward\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/anaconda3/envs/llama3/lib/python3.10/site-packages/accelerate/hooks.py:166\u001b[0m, in \u001b[0;36madd_hook_to_module..new_forward\u001b[0;34m(module, *args, **kwargs)\u001b[0m\n\u001b[1;32m 164\u001b[0m output \u001b[38;5;241m=\u001b[39m module\u001b[38;5;241m.\u001b[39m_old_forward(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[1;32m 165\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m--> 166\u001b[0m output \u001b[38;5;241m=\u001b[39m \u001b[43mmodule\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_old_forward\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 167\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m module\u001b[38;5;241m.\u001b[39m_hf_hook\u001b[38;5;241m.\u001b[39mpost_forward(module, output)\n", + "File \u001b[0;32m~/anaconda3/envs/llama3/lib/python3.10/site-packages/transformers/models/llama/modeling_llama.py:1208\u001b[0m, in \u001b[0;36mLlamaForCausalLM.forward\u001b[0;34m(self, input_ids, attention_mask, position_ids, past_key_values, inputs_embeds, labels, use_cache, output_attentions, output_hidden_states, return_dict, cache_position)\u001b[0m\n\u001b[1;32m 1205\u001b[0m return_dict \u001b[38;5;241m=\u001b[39m return_dict \u001b[38;5;28;01mif\u001b[39;00m return_dict \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mconfig\u001b[38;5;241m.\u001b[39muse_return_dict\n\u001b[1;32m 1207\u001b[0m \u001b[38;5;66;03m# decoder outputs consists of (dec_features, layer_state, dec_hidden, dec_attn)\u001b[39;00m\n\u001b[0;32m-> 1208\u001b[0m outputs \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmodel\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 1209\u001b[0m \u001b[43m \u001b[49m\u001b[43minput_ids\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43minput_ids\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1210\u001b[0m \u001b[43m \u001b[49m\u001b[43mattention_mask\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mattention_mask\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1211\u001b[0m \u001b[43m \u001b[49m\u001b[43mposition_ids\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mposition_ids\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1212\u001b[0m \u001b[43m \u001b[49m\u001b[43mpast_key_values\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mpast_key_values\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1213\u001b[0m \u001b[43m \u001b[49m\u001b[43minputs_embeds\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43minputs_embeds\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1214\u001b[0m \u001b[43m \u001b[49m\u001b[43muse_cache\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43muse_cache\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1215\u001b[0m \u001b[43m \u001b[49m\u001b[43moutput_attentions\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43moutput_attentions\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1216\u001b[0m \u001b[43m \u001b[49m\u001b[43moutput_hidden_states\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43moutput_hidden_states\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1217\u001b[0m \u001b[43m \u001b[49m\u001b[43mreturn_dict\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mreturn_dict\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1218\u001b[0m \u001b[43m \u001b[49m\u001b[43mcache_position\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcache_position\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1219\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1221\u001b[0m hidden_states \u001b[38;5;241m=\u001b[39m outputs[\u001b[38;5;241m0\u001b[39m]\n\u001b[1;32m 1222\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mconfig\u001b[38;5;241m.\u001b[39mpretraining_tp \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m1\u001b[39m:\n", + "File \u001b[0;32m~/anaconda3/envs/llama3/lib/python3.10/site-packages/torch/nn/modules/module.py:1518\u001b[0m, in \u001b[0;36mModule._wrapped_call_impl\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 1516\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_compiled_call_impl(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs) \u001b[38;5;66;03m# type: ignore[misc]\u001b[39;00m\n\u001b[1;32m 1517\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 1518\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_call_impl\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/anaconda3/envs/llama3/lib/python3.10/site-packages/torch/nn/modules/module.py:1527\u001b[0m, in \u001b[0;36mModule._call_impl\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 1522\u001b[0m \u001b[38;5;66;03m# If we don't have any hooks, we want to skip the rest of the logic in\u001b[39;00m\n\u001b[1;32m 1523\u001b[0m \u001b[38;5;66;03m# this function, and just call forward.\u001b[39;00m\n\u001b[1;32m 1524\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m (\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_backward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_backward_pre_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_forward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_forward_pre_hooks\n\u001b[1;32m 1525\u001b[0m \u001b[38;5;129;01mor\u001b[39;00m _global_backward_pre_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_backward_hooks\n\u001b[1;32m 1526\u001b[0m \u001b[38;5;129;01mor\u001b[39;00m _global_forward_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_forward_pre_hooks):\n\u001b[0;32m-> 1527\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mforward_call\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1529\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m 1530\u001b[0m result \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n", + "File \u001b[0;32m~/anaconda3/envs/llama3/lib/python3.10/site-packages/accelerate/hooks.py:166\u001b[0m, in \u001b[0;36madd_hook_to_module..new_forward\u001b[0;34m(module, *args, **kwargs)\u001b[0m\n\u001b[1;32m 164\u001b[0m output \u001b[38;5;241m=\u001b[39m module\u001b[38;5;241m.\u001b[39m_old_forward(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[1;32m 165\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m--> 166\u001b[0m output \u001b[38;5;241m=\u001b[39m \u001b[43mmodule\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_old_forward\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 167\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m module\u001b[38;5;241m.\u001b[39m_hf_hook\u001b[38;5;241m.\u001b[39mpost_forward(module, output)\n", + "File \u001b[0;32m~/anaconda3/envs/llama3/lib/python3.10/site-packages/transformers/models/llama/modeling_llama.py:1007\u001b[0m, in \u001b[0;36mLlamaModel.forward\u001b[0;34m(self, input_ids, attention_mask, position_ids, past_key_values, inputs_embeds, use_cache, output_attentions, output_hidden_states, return_dict, cache_position)\u001b[0m\n\u001b[1;32m 1004\u001b[0m all_hidden_states \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m (hidden_states,)\n\u001b[1;32m 1006\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mgradient_checkpointing \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mtraining:\n\u001b[0;32m-> 1007\u001b[0m layer_outputs \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_gradient_checkpointing_func\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 1008\u001b[0m \u001b[43m \u001b[49m\u001b[43mdecoder_layer\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[38;5;21;43m__call__\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1009\u001b[0m \u001b[43m \u001b[49m\u001b[43mhidden_states\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1010\u001b[0m \u001b[43m \u001b[49m\u001b[43mcausal_mask\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1011\u001b[0m \u001b[43m \u001b[49m\u001b[43mposition_ids\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1012\u001b[0m \u001b[43m \u001b[49m\u001b[43mpast_key_values\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1013\u001b[0m \u001b[43m \u001b[49m\u001b[43moutput_attentions\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1014\u001b[0m \u001b[43m \u001b[49m\u001b[43muse_cache\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1015\u001b[0m \u001b[43m \u001b[49m\u001b[43mcache_position\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1016\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1017\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 1018\u001b[0m layer_outputs \u001b[38;5;241m=\u001b[39m decoder_layer(\n\u001b[1;32m 1019\u001b[0m hidden_states,\n\u001b[1;32m 1020\u001b[0m attention_mask\u001b[38;5;241m=\u001b[39mcausal_mask,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 1025\u001b[0m cache_position\u001b[38;5;241m=\u001b[39mcache_position,\n\u001b[1;32m 1026\u001b[0m )\n", + "File \u001b[0;32m~/anaconda3/envs/llama3/lib/python3.10/site-packages/torch/_compile.py:24\u001b[0m, in \u001b[0;36m_disable_dynamo..inner\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 20\u001b[0m \u001b[38;5;129m@functools\u001b[39m\u001b[38;5;241m.\u001b[39mwraps(fn)\n\u001b[1;32m 21\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21minner\u001b[39m(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[1;32m 22\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mtorch\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_dynamo\u001b[39;00m\n\u001b[0;32m---> 24\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mtorch\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_dynamo\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdisable\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfn\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mrecursive\u001b[49m\u001b[43m)\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m 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\u001b[0;32m~/anaconda3/envs/llama3/lib/python3.10/site-packages/torch/_dynamo/external_utils.py:17\u001b[0m, in \u001b[0;36mwrap_inline..inner\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 15\u001b[0m \u001b[38;5;129m@functools\u001b[39m\u001b[38;5;241m.\u001b[39mwraps(fn)\n\u001b[1;32m 16\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21minner\u001b[39m(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[0;32m---> 17\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfn\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/anaconda3/envs/llama3/lib/python3.10/site-packages/torch/utils/checkpoint.py:451\u001b[0m, in \u001b[0;36mcheckpoint\u001b[0;34m(function, use_reentrant, context_fn, determinism_check, debug, *args, **kwargs)\u001b[0m\n\u001b[1;32m 446\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m context_fn \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m noop_context_fn \u001b[38;5;129;01mor\u001b[39;00m debug \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mFalse\u001b[39;00m:\n\u001b[1;32m 447\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[1;32m 448\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mPassing `context_fn` or `debug` is only supported when \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 449\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124muse_reentrant=False.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 450\u001b[0m )\n\u001b[0;32m--> 451\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mCheckpointFunction\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mapply\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfunction\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpreserve\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 452\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 453\u001b[0m gen \u001b[38;5;241m=\u001b[39m _checkpoint_without_reentrant_generator(\n\u001b[1;32m 454\u001b[0m function, preserve, context_fn, determinism_check, debug, \u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs\n\u001b[1;32m 455\u001b[0m )\n", + "File \u001b[0;32m~/anaconda3/envs/llama3/lib/python3.10/site-packages/torch/autograd/function.py:539\u001b[0m, in \u001b[0;36mFunction.apply\u001b[0;34m(cls, *args, **kwargs)\u001b[0m\n\u001b[1;32m 536\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m torch\u001b[38;5;241m.\u001b[39m_C\u001b[38;5;241m.\u001b[39m_are_functorch_transforms_active():\n\u001b[1;32m 537\u001b[0m \u001b[38;5;66;03m# See NOTE: [functorch vjp and autograd interaction]\u001b[39;00m\n\u001b[1;32m 538\u001b[0m args \u001b[38;5;241m=\u001b[39m _functorch\u001b[38;5;241m.\u001b[39mutils\u001b[38;5;241m.\u001b[39munwrap_dead_wrappers(args)\n\u001b[0;32m--> 539\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43msuper\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mapply\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;66;03m# type: ignore[misc]\u001b[39;00m\n\u001b[1;32m 541\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mcls\u001b[39m\u001b[38;5;241m.\u001b[39msetup_context \u001b[38;5;241m==\u001b[39m _SingleLevelFunction\u001b[38;5;241m.\u001b[39msetup_context:\n\u001b[1;32m 542\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mRuntimeError\u001b[39;00m(\n\u001b[1;32m 543\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mIn order to use an autograd.Function with functorch transforms \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 544\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m(vmap, grad, jvp, jacrev, ...), it must override the setup_context \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 545\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mstaticmethod. For more details, please see \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 546\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mhttps://pytorch.org/docs/master/notes/extending.func.html\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 547\u001b[0m )\n", + "File \u001b[0;32m~/anaconda3/envs/llama3/lib/python3.10/site-packages/torch/utils/checkpoint.py:230\u001b[0m, in \u001b[0;36mCheckpointFunction.forward\u001b[0;34m(ctx, run_function, preserve_rng_state, *args)\u001b[0m\n\u001b[1;32m 227\u001b[0m ctx\u001b[38;5;241m.\u001b[39msave_for_backward(\u001b[38;5;241m*\u001b[39mtensor_inputs)\n\u001b[1;32m 229\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m torch\u001b[38;5;241m.\u001b[39mno_grad():\n\u001b[0;32m--> 230\u001b[0m outputs \u001b[38;5;241m=\u001b[39m \u001b[43mrun_function\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 231\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m outputs\n", + "File \u001b[0;32m~/anaconda3/envs/llama3/lib/python3.10/site-packages/torch/nn/modules/module.py:1518\u001b[0m, in \u001b[0;36mModule._wrapped_call_impl\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 1516\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_compiled_call_impl(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs) \u001b[38;5;66;03m# type: ignore[misc]\u001b[39;00m\n\u001b[1;32m 1517\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 1518\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_call_impl\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/anaconda3/envs/llama3/lib/python3.10/site-packages/torch/nn/modules/module.py:1527\u001b[0m, in \u001b[0;36mModule._call_impl\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 1522\u001b[0m \u001b[38;5;66;03m# If we don't have any hooks, we want to skip the rest of the logic in\u001b[39;00m\n\u001b[1;32m 1523\u001b[0m \u001b[38;5;66;03m# this function, and just call forward.\u001b[39;00m\n\u001b[1;32m 1524\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m (\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_backward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_backward_pre_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_forward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_forward_pre_hooks\n\u001b[1;32m 1525\u001b[0m \u001b[38;5;129;01mor\u001b[39;00m _global_backward_pre_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_backward_hooks\n\u001b[1;32m 1526\u001b[0m \u001b[38;5;129;01mor\u001b[39;00m _global_forward_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_forward_pre_hooks):\n\u001b[0;32m-> 1527\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mforward_call\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1529\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m 1530\u001b[0m result \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n", + "File \u001b[0;32m~/anaconda3/envs/llama3/lib/python3.10/site-packages/accelerate/hooks.py:166\u001b[0m, in \u001b[0;36madd_hook_to_module..new_forward\u001b[0;34m(module, *args, **kwargs)\u001b[0m\n\u001b[1;32m 164\u001b[0m output \u001b[38;5;241m=\u001b[39m module\u001b[38;5;241m.\u001b[39m_old_forward(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[1;32m 165\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m--> 166\u001b[0m output \u001b[38;5;241m=\u001b[39m \u001b[43mmodule\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_old_forward\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 167\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m module\u001b[38;5;241m.\u001b[39m_hf_hook\u001b[38;5;241m.\u001b[39mpost_forward(module, output)\n", + "File \u001b[0;32m~/anaconda3/envs/llama3/lib/python3.10/site-packages/transformers/models/llama/modeling_llama.py:741\u001b[0m, in \u001b[0;36mLlamaDecoderLayer.forward\u001b[0;34m(self, hidden_states, attention_mask, position_ids, past_key_value, output_attentions, use_cache, cache_position, **kwargs)\u001b[0m\n\u001b[1;32m 738\u001b[0m hidden_states \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39minput_layernorm(hidden_states)\n\u001b[1;32m 740\u001b[0m \u001b[38;5;66;03m# Self Attention\u001b[39;00m\n\u001b[0;32m--> 741\u001b[0m hidden_states, self_attn_weights, present_key_value \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mself_attn\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 742\u001b[0m \u001b[43m \u001b[49m\u001b[43mhidden_states\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mhidden_states\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 743\u001b[0m \u001b[43m \u001b[49m\u001b[43mattention_mask\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mattention_mask\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 744\u001b[0m \u001b[43m \u001b[49m\u001b[43mposition_ids\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mposition_ids\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 745\u001b[0m \u001b[43m \u001b[49m\u001b[43mpast_key_value\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mpast_key_value\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 746\u001b[0m \u001b[43m \u001b[49m\u001b[43moutput_attentions\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43moutput_attentions\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 747\u001b[0m \u001b[43m \u001b[49m\u001b[43muse_cache\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43muse_cache\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 748\u001b[0m \u001b[43m \u001b[49m\u001b[43mcache_position\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcache_position\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 749\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 750\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 751\u001b[0m hidden_states \u001b[38;5;241m=\u001b[39m residual \u001b[38;5;241m+\u001b[39m hidden_states\n\u001b[1;32m 753\u001b[0m \u001b[38;5;66;03m# Fully Connected\u001b[39;00m\n", + "File \u001b[0;32m~/anaconda3/envs/llama3/lib/python3.10/site-packages/torch/nn/modules/module.py:1518\u001b[0m, in \u001b[0;36mModule._wrapped_call_impl\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 1516\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_compiled_call_impl(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs) \u001b[38;5;66;03m# type: ignore[misc]\u001b[39;00m\n\u001b[1;32m 1517\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 1518\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_call_impl\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/anaconda3/envs/llama3/lib/python3.10/site-packages/torch/nn/modules/module.py:1527\u001b[0m, in \u001b[0;36mModule._call_impl\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 1522\u001b[0m \u001b[38;5;66;03m# If we don't have any hooks, we want to skip the rest of the logic in\u001b[39;00m\n\u001b[1;32m 1523\u001b[0m \u001b[38;5;66;03m# this function, and just call forward.\u001b[39;00m\n\u001b[1;32m 1524\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m (\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_backward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_backward_pre_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_forward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_forward_pre_hooks\n\u001b[1;32m 1525\u001b[0m \u001b[38;5;129;01mor\u001b[39;00m _global_backward_pre_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_backward_hooks\n\u001b[1;32m 1526\u001b[0m \u001b[38;5;129;01mor\u001b[39;00m _global_forward_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_forward_pre_hooks):\n\u001b[0;32m-> 1527\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mforward_call\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1529\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m 1530\u001b[0m result \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n", + "File \u001b[0;32m~/anaconda3/envs/llama3/lib/python3.10/site-packages/accelerate/hooks.py:166\u001b[0m, in \u001b[0;36madd_hook_to_module..new_forward\u001b[0;34m(module, *args, **kwargs)\u001b[0m\n\u001b[1;32m 164\u001b[0m output \u001b[38;5;241m=\u001b[39m module\u001b[38;5;241m.\u001b[39m_old_forward(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[1;32m 165\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m--> 166\u001b[0m output \u001b[38;5;241m=\u001b[39m \u001b[43mmodule\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_old_forward\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 167\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m module\u001b[38;5;241m.\u001b[39m_hf_hook\u001b[38;5;241m.\u001b[39mpost_forward(module, output)\n", + "File \u001b[0;32m~/anaconda3/envs/llama3/lib/python3.10/site-packages/transformers/models/llama/modeling_llama.py:490\u001b[0m, in \u001b[0;36mLlamaFlashAttention2.forward\u001b[0;34m(self, hidden_states, attention_mask, position_ids, past_key_value, output_attentions, use_cache, cache_position, **kwargs)\u001b[0m\n\u001b[1;32m 487\u001b[0m key_states \u001b[38;5;241m=\u001b[39m key_states\u001b[38;5;241m.\u001b[39mto(target_dtype)\n\u001b[1;32m 488\u001b[0m value_states \u001b[38;5;241m=\u001b[39m value_states\u001b[38;5;241m.\u001b[39mto(target_dtype)\n\u001b[0;32m--> 490\u001b[0m attn_output \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_flash_attention_forward\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 491\u001b[0m \u001b[43m \u001b[49m\u001b[43mquery_states\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mkey_states\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mvalue_states\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mattention_mask\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mq_len\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdropout\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdropout_rate\u001b[49m\n\u001b[1;32m 492\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 494\u001b[0m attn_output \u001b[38;5;241m=\u001b[39m attn_output\u001b[38;5;241m.\u001b[39mreshape(bsz, q_len, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mhidden_size)\u001b[38;5;241m.\u001b[39mcontiguous()\n\u001b[1;32m 495\u001b[0m attn_output \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mo_proj(attn_output)\n", + "File \u001b[0;32m~/anaconda3/envs/llama3/lib/python3.10/site-packages/transformers/models/llama/modeling_llama.py:533\u001b[0m, in \u001b[0;36mLlamaFlashAttention2._flash_attention_forward\u001b[0;34m(self, query_states, key_states, value_states, attention_mask, query_length, dropout, softmax_scale)\u001b[0m\n\u001b[1;32m 531\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m attention_mask \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 532\u001b[0m batch_size \u001b[38;5;241m=\u001b[39m query_states\u001b[38;5;241m.\u001b[39mshape[\u001b[38;5;241m0\u001b[39m]\n\u001b[0;32m--> 533\u001b[0m query_states, key_states, value_states, indices_q, cu_seq_lens, max_seq_lens \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_upad_input\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 534\u001b[0m \u001b[43m \u001b[49m\u001b[43mquery_states\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mkey_states\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mvalue_states\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mattention_mask\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mquery_length\u001b[49m\n\u001b[1;32m 535\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 537\u001b[0m cu_seqlens_q, cu_seqlens_k \u001b[38;5;241m=\u001b[39m cu_seq_lens\n\u001b[1;32m 538\u001b[0m max_seqlen_in_batch_q, max_seqlen_in_batch_k \u001b[38;5;241m=\u001b[39m max_seq_lens\n", + "File \u001b[0;32m~/anaconda3/envs/llama3/lib/python3.10/site-packages/transformers/models/llama/modeling_llama.py:565\u001b[0m, in \u001b[0;36mLlamaFlashAttention2._upad_input\u001b[0;34m(self, query_layer, key_layer, value_layer, attention_mask, query_length)\u001b[0m\n\u001b[1;32m 562\u001b[0m indices_k, cu_seqlens_k, max_seqlen_in_batch_k \u001b[38;5;241m=\u001b[39m _get_unpad_data(attention_mask)\n\u001b[1;32m 563\u001b[0m batch_size, kv_seq_len, num_key_value_heads, head_dim \u001b[38;5;241m=\u001b[39m key_layer\u001b[38;5;241m.\u001b[39mshape\n\u001b[0;32m--> 565\u001b[0m key_layer \u001b[38;5;241m=\u001b[39m \u001b[43mindex_first_axis\u001b[49m(\n\u001b[1;32m 566\u001b[0m key_layer\u001b[38;5;241m.\u001b[39mreshape(batch_size \u001b[38;5;241m*\u001b[39m kv_seq_len, num_key_value_heads, head_dim), indices_k\n\u001b[1;32m 567\u001b[0m )\n\u001b[1;32m 568\u001b[0m value_layer \u001b[38;5;241m=\u001b[39m index_first_axis(\n\u001b[1;32m 569\u001b[0m value_layer\u001b[38;5;241m.\u001b[39mreshape(batch_size \u001b[38;5;241m*\u001b[39m kv_seq_len, num_key_value_heads, head_dim), indices_k\n\u001b[1;32m 570\u001b[0m )\n\u001b[1;32m 571\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m query_length \u001b[38;5;241m==\u001b[39m kv_seq_len:\n", + "\u001b[0;31mNameError\u001b[0m: name 'index_first_axis' is not defined" + ] + } + ], + "source": [ + "orpo_args = ORPOConfig(\n", + " learning_rate=8e-6,\n", + " beta=0.1,\n", + " lr_scheduler_type=\"linear\",\n", + " max_length=1024,\n", + " max_prompt_length=512,\n", + " per_device_train_batch_size=2,\n", + " per_device_eval_batch_size=2,\n", + " gradient_accumulation_steps=4,\n", + " optim=\"paged_adamw_8bit\",\n", + " num_train_epochs=1,\n", + " evaluation_strategy=\"steps\",\n", + " eval_steps=0.2,\n", + " logging_steps=1,\n", + " warmup_steps=10,\n", + " output_dir=\"./results/\",\n", + ")\n", + "\n", + "trainer = ORPOTrainer(\n", + " model=model,\n", + " args=orpo_args,\n", + " train_dataset=dataset[\"train\"],\n", + " eval_dataset=dataset[\"test\"],\n", + " peft_config=peft_config,\n", + " tokenizer=tokenizer,\n", + ")\n", + "trainer.train()\n", + "trainer.save_model(new_model)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b2fafda4-7fd6-4612-9e72-ffe106e232fd", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.14" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/llama3/requirements.txt b/llama3/requirements.txt new file mode 100644 index 0000000..acd4a29 --- /dev/null +++ b/llama3/requirements.txt @@ -0,0 +1,6 @@ +transformers +datasets +accelerate +peft +trl +bitsandbytes diff --git a/phi3/requirements.txt b/phi3/requirements.txt new file mode 100644 index 0000000..02a56f0 --- /dev/null +++ b/phi3/requirements.txt @@ -0,0 +1,3 @@ +datasets +trl +transformers \ No newline at end of file diff --git a/phi3/script/sft.py b/phi3/script/sft.py new file mode 100644 index 0000000..1e7e8bd --- /dev/null +++ b/phi3/script/sft.py @@ -0,0 +1,129 @@ +import torch +from datasets import load_dataset +from trl import SFTTrainer +from transformers import AutoModelForCausalLM, AutoTokenizer, TrainingArguments + +""" +A simple example on using SFTTrainer and Accelerate to finetune Phi-3 models. For +a more advanced example, please follow HF alignment-handbook/scripts/run_sft.py +1. Install accelerate: + conda install -c conda-forge accelerate +2. Setup accelerate config: + accelerate config +to simply use all the GPUs available: + python -c "from accelerate.utils import write_basic_config; write_basic_config(mixed_precision='bf16')" +check accelerate config: + accelerate env +3. Run the code: + accelerate launch sample_finetune.py +""" + +################### +# Hyper-parameters +################### +args = { + "bf16": True, + "do_eval": False, + "learning_rate": 5.0e-06, + "log_level": "info", + "logging_steps": 20, + "logging_strategy": "steps", + "lr_scheduler_type": "cosine", + "num_train_epochs": 1, + "max_steps": -1, + "output_dir": "./checkpoint_dir", + "overwrite_output_dir": True, + "per_device_eval_batch_size": 4, + "per_device_train_batch_size": 8, + "remove_unused_columns": True, + "save_steps": 100, + "save_total_limit": 1, + "seed": 0, + "gradient_checkpointing": True, + "gradient_checkpointing_kwargs":{"use_reentrant": False}, + "gradient_accumulation_steps": 1, + "warmup_ratio": 0.2, + } + +training_args = TrainingArguments(**args) + + +################ +# Modle Loading +################ +checkpoint_path = "microsoft/Phi-3-mini-4k-instruct" +# checkpoint_path = "microsoft/Phi-3-mini-128k-instruct" +model_kwargs = dict( + use_cache=False, + trust_remote_code=True, + attn_implementation="flash_attention_2", # loading the model with flash-attenstion support + torch_dtype=torch.bfloat16, + device_map="cuda", +) +model = AutoModelForCausalLM.from_pretrained(checkpoint_path, **model_kwargs) +tokenizer = AutoTokenizer.from_pretrained(checkpoint_path) +tokenizer.pad_token = tokenizer.unk_token # use unk rather than eos token to prevent endless generation +tokenizer.pad_token_id = tokenizer.convert_tokens_to_ids(tokenizer.pad_token) +tokenizer.padding_side = 'right' + +################## +# Data Processing +################## +def apply_chat_template( + example, + tokenizer, +): + messages = example["messages"] + # Add an empty system message if there is none + if messages[0]["role"] != "system": + messages.insert(0, {"role": "system", "content": ""}) + example["text"] = tokenizer.apply_chat_template( + messages, tokenize=False, add_generation_prompt=False) + return example + +raw_dataset = load_dataset("HuggingFaceH4/ultrachat_200k") +column_names = list(raw_dataset["train_sft"].features) + +processed_dataset = raw_dataset.map( + apply_chat_template, + fn_kwargs={"tokenizer": tokenizer}, + num_proc=12, + remove_columns=column_names, + desc="Applying chat template", +) +train_dataset = processed_dataset["train_sft"] +eval_dataset = processed_dataset["test_sft"] + + +########### +# Training +########### +trainer = SFTTrainer( + model=model, + args=training_args, + train_dataset=train_dataset, + eval_dataset=eval_dataset, + max_seq_length=2048, + dataset_text_field="text", + tokenizer=tokenizer, + packing=True +) +train_result = trainer.train() +metrics = train_result.metrics +trainer.log_metrics("train", metrics) +trainer.save_metrics("train", metrics) +trainer.save_state() + +############# +# Evaluation +############# +tokenizer.padding_side = 'left' +metrics = trainer.evaluate() +metrics["eval_samples"] = len(eval_dataset) +trainer.log_metrics("eval", metrics) +trainer.save_metrics("eval", metrics) + +############ +# Save model +############ +trainer.save_model(training_args.output_dir) From 772e8ae522b61699d8437d3e1f73133ab6f9bf7a Mon Sep 17 00:00:00 2001 From: jazelly Date: Thu, 2 May 2024 21:31:29 +0930 Subject: [PATCH 04/96] chore: add submodule slowllama --- .gitmodules | 3 +++ mac/slowllama | 1 + 2 files changed, 4 insertions(+) create mode 100644 .gitmodules create mode 160000 mac/slowllama diff --git a/.gitmodules b/.gitmodules new file mode 100644 index 0000000..b58f250 --- /dev/null +++ b/.gitmodules @@ -0,0 +1,3 @@ +[submodule "mac/slowllama"] + path = mac/slowllama + url = git@github.com:okuvshynov/slowllama.git diff --git a/mac/slowllama b/mac/slowllama new file mode 160000 index 0000000..0d8a4cf --- /dev/null +++ b/mac/slowllama @@ -0,0 +1 @@ +Subproject commit 0d8a4cf5dc8767db81d019812f054a77ce68b31e From f2c1b89c045f69308289fe77c9a11a2d1585a7c0 Mon Sep 17 00:00:00 2001 From: jazelly Date: Thu, 2 May 2024 22:33:13 +0930 Subject: [PATCH 05/96] fix: path issues in slowllama --- .gitignore | 3 ++- .gitmodules | 2 +- 2 files changed, 3 insertions(+), 2 deletions(-) diff --git a/.gitignore b/.gitignore index 76523d7..3d282ae 100644 --- a/.gitignore +++ b/.gitignore @@ -160,4 +160,5 @@ cython_debug/ # option (not recommended) you can uncomment the following to ignore the entire idea folder. #.idea/ -results/ \ No newline at end of file +results/ +llama-2-7b/ \ No newline at end of file diff --git a/.gitmodules b/.gitmodules index b58f250..23bad3e 100644 --- a/.gitmodules +++ b/.gitmodules @@ -1,3 +1,3 @@ [submodule "mac/slowllama"] path = mac/slowllama - url = git@github.com:okuvshynov/slowllama.git + url = git@github.com:jazelly/slowllama.git From 4999f7d272c3504b6fdfe099d18a5a5613f25606 Mon Sep 17 00:00:00 2001 From: jazelly Date: Sat, 4 May 2024 20:43:57 +0930 Subject: [PATCH 06/96] ignore update --- .gitignore | 1 + 1 file changed, 1 insertion(+) diff --git a/.gitignore b/.gitignore index 76523d7..f265664 100644 --- a/.gitignore +++ b/.gitignore @@ -160,4 +160,5 @@ cython_debug/ # option (not recommended) you can uncomment the following to ignore the entire idea folder. #.idea/ +checkpoint_dir/ results/ \ No newline at end of file From ffb34bdce96c63dd20323212fa1c89c4b621c8de Mon Sep 17 00:00:00 2001 From: jazelly Date: Sun, 5 May 2024 18:02:29 +0930 Subject: [PATCH 07/96] feat: support finetune llama in gguf --- .gitmodules | 3 + llama-gguf/README.md | 75 ++ llama-gguf/llama.cpp | 1 + llama-gguf/shakespeare.txt | 2469 ++++++++++++++++++++++++++++++++++++ 4 files changed, 2548 insertions(+) create mode 100644 llama-gguf/README.md create mode 160000 llama-gguf/llama.cpp create mode 100644 llama-gguf/shakespeare.txt diff --git a/.gitmodules b/.gitmodules index 23bad3e..98a3545 100644 --- a/.gitmodules +++ b/.gitmodules @@ -1,3 +1,6 @@ [submodule "mac/slowllama"] path = mac/slowllama url = git@github.com:jazelly/slowllama.git +[submodule "llama-gguf/llama.cpp"] + path = llama-gguf/llama.cpp + url = git@github.com:ggerganov/llama.cpp.git diff --git a/llama-gguf/README.md b/llama-gguf/README.md new file mode 100644 index 0000000..87123b5 --- /dev/null +++ b/llama-gguf/README.md @@ -0,0 +1,75 @@ +## Finetune LLAMA based model in GGUF format + +We will utilize `llama.cpp` to finetune a GGUF model, so that you can customize it and inference it in a programmatic way. `llama.cpp` is a pure C/C++ implementation of LLAMA model with 0 denpendencies, +So you can run this on any OS. + +## Setup + +- First, init the submodule if you haven't. + ``` + git submodule update --init + cd llama.cpp + ``` + +- Using `make`: + - On Linux or MacOS: + + ```bash + make + ``` + + **Note**: for `Debug` builds, run `make LLAMA_DEBUG=1` + + - On Windows: + + 1. Download the latest fortran version of [w64devkit](https://github.com/skeeto/w64devkit/releases). + 2. Extract `w64devkit` on your pc. + 3. Run `w64devkit.exe`. + 4. Use the `cd` command to reach the `llama.cpp` folder. + 5. From here you can run: + ```bash + make + ``` + +- Using `CMake`: + + ```bash + cmake -B build + cmake --build build --config Release + ``` + + **Note**: for `Debug` builds, there are two cases: + + - Single-config generators (e.g. default = `Unix Makefiles`; note that they just ignore the `--config` flag): + + ```bash + cmake -B build -DCMAKE_BUILD_TYPE=Debug + cmake --build build + ``` + + - Multi-config generators (`-G` param set to Visual Studio, XCode...): + + ```bash + cmake -B build -G "Xcode" + cmake --build build --config Debug + ``` + +- Once the build is done, you can do an example finetuning like this + ``` + cd build + + # get training data + wget https://raw.githubusercontent.com/brunoklein99/deep-learning-notes/master/shakespeare.txt + + # download a gguf model + huggingface-cli login + huggingface-cli download QuantFactory/Meta-Llama-3-8B-GGUF Meta-Llama-3-8B.Q8_0.gguf --local-dir models + + # start training + ./bin/finetune --model-base models/Meta-Llama-3-8B.Q8_0.gguf --checkpoint-in chk-lora-open-llama-3b-v2-q8_0-shakespeare-LATEST.gguf --checkpoint-out chk-lora-open-llama-3b-v2-q8_0-shakespeare-ITERATION.gguf --lora-out lora-open-llama-3b-v2-q8_0-shakespeare-ITERATION.bin --train-data "shakespeare.txt" --save-every 10 --threads 6 --adam-iter 30 --batch 4 --ctx 6 --use-checkpointing + ``` + +- For more help + ``` + ./bin/finetune --help + ``` \ No newline at end of file diff --git a/llama-gguf/llama.cpp b/llama-gguf/llama.cpp new file mode 160000 index 0000000..03fb8a0 --- /dev/null +++ b/llama-gguf/llama.cpp @@ -0,0 +1 @@ +Subproject commit 03fb8a002df2e96104f9e06de9c78d2a8ed91e92 diff --git a/llama-gguf/shakespeare.txt b/llama-gguf/shakespeare.txt new file mode 100644 index 0000000..dce66b2 --- /dev/null +++ b/llama-gguf/shakespeare.txt @@ -0,0 +1,2469 @@ +THE SONNETS + +by William Shakespeare + +From fairest creatures we desire increase, +That thereby beauty's rose might never die, +But as the riper should by time decease, +His tender heir might bear his memory: +But thou contracted to thine own bright eyes, +Feed'st thy light's flame with self-substantial fuel, +Making a famine where abundance lies, +Thy self thy foe, to thy sweet self too cruel: +Thou that art now the world's fresh ornament, +And only herald to the gaudy spring, +Within thine own bud buriest thy content, +And tender churl mak'st waste in niggarding: +Pity the world, or else this glutton be, +To eat the world's due, by the grave and thee. + +When forty winters shall besiege thy brow, +And dig deep trenches in thy beauty's field, +Thy youth's proud livery so gazed on now, +Will be a tattered weed of small worth held: +Then being asked, where all thy beauty lies, +Where all the treasure of thy lusty days; +To say within thine own deep sunken eyes, +Were an all-eating shame, and thriftless praise. +How much more praise deserved thy beauty's use, +If thou couldst answer 'This fair child of mine +Shall sum my count, and make my old excuse' +Proving his beauty by succession thine. +This were to be new made when thou art old, +And see thy blood warm when thou feel'st it cold. + +Look in thy glass and tell the face thou viewest, +Now is the time that face should form another, +Whose fresh repair if now thou not renewest, +Thou dost beguile the world, unbless some mother. +For where is she so fair whose uneared womb +Disdains the tillage of thy husbandry? +Or who is he so fond will be the tomb, +Of his self-love to stop posterity? +Thou art thy mother's glass and she in thee +Calls back the lovely April of her prime, +So thou through windows of thine age shalt see, +Despite of wrinkles this thy golden time. +But if thou live remembered not to be, +Die single and thine image dies with thee. + +Unthrifty loveliness why dost thou spend, +Upon thy self thy beauty's legacy? +Nature's bequest gives nothing but doth lend, +And being frank she lends to those are free: +Then beauteous niggard why dost thou abuse, +The bounteous largess given thee to give? +Profitless usurer why dost thou use +So great a sum of sums yet canst not live? +For having traffic with thy self alone, +Thou of thy self thy sweet self dost deceive, +Then how when nature calls thee to be gone, +What acceptable audit canst thou leave? +Thy unused beauty must be tombed with thee, +Which used lives th' executor to be. + +Those hours that with gentle work did frame +The lovely gaze where every eye doth dwell +Will play the tyrants to the very same, +And that unfair which fairly doth excel: +For never-resting time leads summer on +To hideous winter and confounds him there, +Sap checked with frost and lusty leaves quite gone, +Beauty o'er-snowed and bareness every where: +Then were not summer's distillation left +A liquid prisoner pent in walls of glass, +Beauty's effect with beauty were bereft, +Nor it nor no remembrance what it was. +But flowers distilled though they with winter meet, +Leese but their show, their substance still lives sweet. + +Then let not winter's ragged hand deface, +In thee thy summer ere thou be distilled: +Make sweet some vial; treasure thou some place, +With beauty's treasure ere it be self-killed: +That use is not forbidden usury, +Which happies those that pay the willing loan; +That's for thy self to breed another thee, +Or ten times happier be it ten for one, +Ten times thy self were happier than thou art, +If ten of thine ten times refigured thee: +Then what could death do if thou shouldst depart, +Leaving thee living in posterity? +Be not self-willed for thou art much too fair, +To be death's conquest and make worms thine heir. + +Lo in the orient when the gracious light +Lifts up his burning head, each under eye +Doth homage to his new-appearing sight, +Serving with looks his sacred majesty, +And having climbed the steep-up heavenly hill, +Resembling strong youth in his middle age, +Yet mortal looks adore his beauty still, +Attending on his golden pilgrimage: +But when from highmost pitch with weary car, +Like feeble age he reeleth from the day, +The eyes (fore duteous) now converted are +From his low tract and look another way: +So thou, thy self out-going in thy noon: +Unlooked on diest unless thou get a son. + +Music to hear, why hear'st thou music sadly? +Sweets with sweets war not, joy delights in joy: +Why lov'st thou that which thou receiv'st not gladly, +Or else receiv'st with pleasure thine annoy? +If the true concord of well-tuned sounds, +By unions married do offend thine ear, +They do but sweetly chide thee, who confounds +In singleness the parts that thou shouldst bear: +Mark how one string sweet husband to another, +Strikes each in each by mutual ordering; +Resembling sire, and child, and happy mother, +Who all in one, one pleasing note do sing: +Whose speechless song being many, seeming one, +Sings this to thee, 'Thou single wilt prove none'. + +Is it for fear to wet a widow's eye, +That thou consum'st thy self in single life? +Ah, if thou issueless shalt hap to die, +The world will wail thee like a makeless wife, +The world will be thy widow and still weep, +That thou no form of thee hast left behind, +When every private widow well may keep, +By children's eyes, her husband's shape in mind: +Look what an unthrift in the world doth spend +Shifts but his place, for still the world enjoys it; +But beauty's waste hath in the world an end, +And kept unused the user so destroys it: +No love toward others in that bosom sits +That on himself such murd'rous shame commits. + +For shame deny that thou bear'st love to any +Who for thy self art so unprovident. +Grant if thou wilt, thou art beloved of many, +But that thou none lov'st is most evident: +For thou art so possessed with murd'rous hate, +That 'gainst thy self thou stick'st not to conspire, +Seeking that beauteous roof to ruinate +Which to repair should be thy chief desire: +O change thy thought, that I may change my mind, +Shall hate be fairer lodged than gentle love? +Be as thy presence is gracious and kind, +Or to thy self at least kind-hearted prove, +Make thee another self for love of me, +That beauty still may live in thine or thee. + +As fast as thou shalt wane so fast thou grow'st, +In one of thine, from that which thou departest, +And that fresh blood which youngly thou bestow'st, +Thou mayst call thine, when thou from youth convertest, +Herein lives wisdom, beauty, and increase, +Without this folly, age, and cold decay, +If all were minded so, the times should cease, +And threescore year would make the world away: +Let those whom nature hath not made for store, +Harsh, featureless, and rude, barrenly perish: +Look whom she best endowed, she gave thee more; +Which bounteous gift thou shouldst in bounty cherish: +She carved thee for her seal, and meant thereby, +Thou shouldst print more, not let that copy die. + +When I do count the clock that tells the time, +And see the brave day sunk in hideous night, +When I behold the violet past prime, +And sable curls all silvered o'er with white: +When lofty trees I see barren of leaves, +Which erst from heat did canopy the herd +And summer's green all girded up in sheaves +Borne on the bier with white and bristly beard: +Then of thy beauty do I question make +That thou among the wastes of time must go, +Since sweets and beauties do themselves forsake, +And die as fast as they see others grow, +And nothing 'gainst Time's scythe can make defence +Save breed to brave him, when he takes thee hence. + +O that you were your self, but love you are +No longer yours, than you your self here live, +Against this coming end you should prepare, +And your sweet semblance to some other give. +So should that beauty which you hold in lease +Find no determination, then you were +Your self again after your self's decease, +When your sweet issue your sweet form should bear. +Who lets so fair a house fall to decay, +Which husbandry in honour might uphold, +Against the stormy gusts of winter's day +And barren rage of death's eternal cold? +O none but unthrifts, dear my love you know, +You had a father, let your son say so. + +Not from the stars do I my judgement pluck, +And yet methinks I have astronomy, +But not to tell of good, or evil luck, +Of plagues, of dearths, or seasons' quality, +Nor can I fortune to brief minutes tell; +Pointing to each his thunder, rain and wind, +Or say with princes if it shall go well +By oft predict that I in heaven find. +But from thine eyes my knowledge I derive, +And constant stars in them I read such art +As truth and beauty shall together thrive +If from thy self, to store thou wouldst convert: +Or else of thee this I prognosticate, +Thy end is truth's and beauty's doom and date. + +When I consider every thing that grows +Holds in perfection but a little moment. +That this huge stage presenteth nought but shows +Whereon the stars in secret influence comment. +When I perceive that men as plants increase, +Cheered and checked even by the self-same sky: +Vaunt in their youthful sap, at height decrease, +And wear their brave state out of memory. +Then the conceit of this inconstant stay, +Sets you most rich in youth before my sight, +Where wasteful time debateth with decay +To change your day of youth to sullied night, +And all in war with Time for love of you, +As he takes from you, I engraft you new. + +But wherefore do not you a mightier way +Make war upon this bloody tyrant Time? +And fortify your self in your decay +With means more blessed than my barren rhyme? +Now stand you on the top of happy hours, +And many maiden gardens yet unset, +With virtuous wish would bear you living flowers, +Much liker than your painted counterfeit: +So should the lines of life that life repair +Which this (Time's pencil) or my pupil pen +Neither in inward worth nor outward fair +Can make you live your self in eyes of men. +To give away your self, keeps your self still, +And you must live drawn by your own sweet skill. + +Who will believe my verse in time to come +If it were filled with your most high deserts? +Though yet heaven knows it is but as a tomb +Which hides your life, and shows not half your parts: +If I could write the beauty of your eyes, +And in fresh numbers number all your graces, +The age to come would say this poet lies, +Such heavenly touches ne'er touched earthly faces. +So should my papers (yellowed with their age) +Be scorned, like old men of less truth than tongue, +And your true rights be termed a poet's rage, +And stretched metre of an antique song. +But were some child of yours alive that time, +You should live twice in it, and in my rhyme. + +Shall I compare thee to a summer's day? +Thou art more lovely and more temperate: +Rough winds do shake the darling buds of May, +And summer's lease hath all too short a date: +Sometime too hot the eye of heaven shines, +And often is his gold complexion dimmed, +And every fair from fair sometime declines, +By chance, or nature's changing course untrimmed: +But thy eternal summer shall not fade, +Nor lose possession of that fair thou ow'st, +Nor shall death brag thou wand'rest in his shade, +When in eternal lines to time thou grow'st, +So long as men can breathe or eyes can see, +So long lives this, and this gives life to thee. + +Devouring Time blunt thou the lion's paws, +And make the earth devour her own sweet brood, +Pluck the keen teeth from the fierce tiger's jaws, +And burn the long-lived phoenix, in her blood, +Make glad and sorry seasons as thou fleet'st, +And do whate'er thou wilt swift-footed Time +To the wide world and all her fading sweets: +But I forbid thee one most heinous crime, +O carve not with thy hours my love's fair brow, +Nor draw no lines there with thine antique pen, +Him in thy course untainted do allow, +For beauty's pattern to succeeding men. +Yet do thy worst old Time: despite thy wrong, +My love shall in my verse ever live young. + +A woman's face with nature's own hand painted, +Hast thou the master mistress of my passion, +A woman's gentle heart but not acquainted +With shifting change as is false women's fashion, +An eye more bright than theirs, less false in rolling: +Gilding the object whereupon it gazeth, +A man in hue all hues in his controlling, +Which steals men's eyes and women's souls amazeth. +And for a woman wert thou first created, +Till nature as she wrought thee fell a-doting, +And by addition me of thee defeated, +By adding one thing to my purpose nothing. +But since she pricked thee out for women's pleasure, +Mine be thy love and thy love's use their treasure. + +So is it not with me as with that muse, +Stirred by a painted beauty to his verse, +Who heaven it self for ornament doth use, +And every fair with his fair doth rehearse, +Making a couplement of proud compare +With sun and moon, with earth and sea's rich gems: +With April's first-born flowers and all things rare, +That heaven's air in this huge rondure hems. +O let me true in love but truly write, +And then believe me, my love is as fair, +As any mother's child, though not so bright +As those gold candles fixed in heaven's air: +Let them say more that like of hearsay well, +I will not praise that purpose not to sell. + +My glass shall not persuade me I am old, +So long as youth and thou are of one date, +But when in thee time's furrows I behold, +Then look I death my days should expiate. +For all that beauty that doth cover thee, +Is but the seemly raiment of my heart, +Which in thy breast doth live, as thine in me, +How can I then be elder than thou art? +O therefore love be of thyself so wary, +As I not for my self, but for thee will, +Bearing thy heart which I will keep so chary +As tender nurse her babe from faring ill. +Presume not on thy heart when mine is slain, +Thou gav'st me thine not to give back again. + +As an unperfect actor on the stage, +Who with his fear is put beside his part, +Or some fierce thing replete with too much rage, +Whose strength's abundance weakens his own heart; +So I for fear of trust, forget to say, +The perfect ceremony of love's rite, +And in mine own love's strength seem to decay, +O'ercharged with burthen of mine own love's might: +O let my looks be then the eloquence, +And dumb presagers of my speaking breast, +Who plead for love, and look for recompense, +More than that tongue that more hath more expressed. +O learn to read what silent love hath writ, +To hear with eyes belongs to love's fine wit. + +Mine eye hath played the painter and hath stelled, +Thy beauty's form in table of my heart, +My body is the frame wherein 'tis held, +And perspective it is best painter's art. +For through the painter must you see his skill, +To find where your true image pictured lies, +Which in my bosom's shop is hanging still, +That hath his windows glazed with thine eyes: +Now see what good turns eyes for eyes have done, +Mine eyes have drawn thy shape, and thine for me +Are windows to my breast, where-through the sun +Delights to peep, to gaze therein on thee; +Yet eyes this cunning want to grace their art, +They draw but what they see, know not the heart. + +Let those who are in favour with their stars, +Of public honour and proud titles boast, +Whilst I whom fortune of such triumph bars +Unlooked for joy in that I honour most; +Great princes' favourites their fair leaves spread, +But as the marigold at the sun's eye, +And in themselves their pride lies buried, +For at a frown they in their glory die. +The painful warrior famoused for fight, +After a thousand victories once foiled, +Is from the book of honour razed quite, +And all the rest forgot for which he toiled: +Then happy I that love and am beloved +Where I may not remove nor be removed. + +Lord of my love, to whom in vassalage +Thy merit hath my duty strongly knit; +To thee I send this written embassage +To witness duty, not to show my wit. +Duty so great, which wit so poor as mine +May make seem bare, in wanting words to show it; +But that I hope some good conceit of thine +In thy soul's thought (all naked) will bestow it: +Till whatsoever star that guides my moving, +Points on me graciously with fair aspect, +And puts apparel on my tattered loving, +To show me worthy of thy sweet respect, +Then may I dare to boast how I do love thee, +Till then, not show my head where thou mayst prove me. + +Weary with toil, I haste me to my bed, +The dear respose for limbs with travel tired, +But then begins a journey in my head +To work my mind, when body's work's expired. +For then my thoughts (from far where I abide) +Intend a zealous pilgrimage to thee, +And keep my drooping eyelids open wide, +Looking on darkness which the blind do see. +Save that my soul's imaginary sight +Presents thy shadow to my sightless view, +Which like a jewel (hung in ghastly night) +Makes black night beauteous, and her old face new. +Lo thus by day my limbs, by night my mind, +For thee, and for my self, no quiet find. + +How can I then return in happy plight +That am debarred the benefit of rest? +When day's oppression is not eased by night, +But day by night and night by day oppressed. +And each (though enemies to either's reign) +Do in consent shake hands to torture me, +The one by toil, the other to complain +How far I toil, still farther off from thee. +I tell the day to please him thou art bright, +And dost him grace when clouds do blot the heaven: +So flatter I the swart-complexioned night, +When sparkling stars twire not thou gild'st the even. +But day doth daily draw my sorrows longer, +And night doth nightly make grief's length seem stronger + +When in disgrace with Fortune and men's eyes, +I all alone beweep my outcast state, +And trouble deaf heaven with my bootless cries, +And look upon my self and curse my fate, +Wishing me like to one more rich in hope, +Featured like him, like him with friends possessed, +Desiring this man's art, and that man's scope, +With what I most enjoy contented least, +Yet in these thoughts my self almost despising, +Haply I think on thee, and then my state, +(Like to the lark at break of day arising +From sullen earth) sings hymns at heaven's gate, +For thy sweet love remembered such wealth brings, +That then I scorn to change my state with kings. + +When to the sessions of sweet silent thought, +I summon up remembrance of things past, +I sigh the lack of many a thing I sought, +And with old woes new wail my dear time's waste: +Then can I drown an eye (unused to flow) +For precious friends hid in death's dateless night, +And weep afresh love's long since cancelled woe, +And moan th' expense of many a vanished sight. +Then can I grieve at grievances foregone, +And heavily from woe to woe tell o'er +The sad account of fore-bemoaned moan, +Which I new pay as if not paid before. +But if the while I think on thee (dear friend) +All losses are restored, and sorrows end. + +Thy bosom is endeared with all hearts, +Which I by lacking have supposed dead, +And there reigns love and all love's loving parts, +And all those friends which I thought buried. +How many a holy and obsequious tear +Hath dear religious love stol'n from mine eye, +As interest of the dead, which now appear, +But things removed that hidden in thee lie. +Thou art the grave where buried love doth live, +Hung with the trophies of my lovers gone, +Who all their parts of me to thee did give, +That due of many, now is thine alone. +Their images I loved, I view in thee, +And thou (all they) hast all the all of me. + +If thou survive my well-contented day, +When that churl death my bones with dust shall cover +And shalt by fortune once more re-survey +These poor rude lines of thy deceased lover: +Compare them with the bett'ring of the time, +And though they be outstripped by every pen, +Reserve them for my love, not for their rhyme, +Exceeded by the height of happier men. +O then vouchsafe me but this loving thought, +'Had my friend's Muse grown with this growing age, +A dearer birth than this his love had brought +To march in ranks of better equipage: +But since he died and poets better prove, +Theirs for their style I'll read, his for his love'. + +Full many a glorious morning have I seen, +Flatter the mountain tops with sovereign eye, +Kissing with golden face the meadows green; +Gilding pale streams with heavenly alchemy: +Anon permit the basest clouds to ride, +With ugly rack on his celestial face, +And from the forlorn world his visage hide +Stealing unseen to west with this disgrace: +Even so my sun one early morn did shine, +With all triumphant splendour on my brow, +But out alack, he was but one hour mine, +The region cloud hath masked him from me now. +Yet him for this, my love no whit disdaineth, +Suns of the world may stain, when heaven's sun staineth. + +Why didst thou promise such a beauteous day, +And make me travel forth without my cloak, +To let base clouds o'ertake me in my way, +Hiding thy brav'ry in their rotten smoke? +'Tis not enough that through the cloud thou break, +To dry the rain on my storm-beaten face, +For no man well of such a salve can speak, +That heals the wound, and cures not the disgrace: +Nor can thy shame give physic to my grief, +Though thou repent, yet I have still the loss, +Th' offender's sorrow lends but weak relief +To him that bears the strong offence's cross. +Ah but those tears are pearl which thy love sheds, +And they are rich, and ransom all ill deeds. + + + +No more be grieved at that which thou hast done, +Roses have thorns, and silver fountains mud, +Clouds and eclipses stain both moon and sun, +And loathsome canker lives in sweetest bud. +All men make faults, and even I in this, +Authorizing thy trespass with compare, +My self corrupting salving thy amiss, +Excusing thy sins more than thy sins are: +For to thy sensual fault I bring in sense, +Thy adverse party is thy advocate, +And 'gainst my self a lawful plea commence: +Such civil war is in my love and hate, +That I an accessary needs must be, +To that sweet thief which sourly robs from me. + +Let me confess that we two must be twain, +Although our undivided loves are one: +So shall those blots that do with me remain, +Without thy help, by me be borne alone. +In our two loves there is but one respect, +Though in our lives a separable spite, +Which though it alter not love's sole effect, +Yet doth it steal sweet hours from love's delight. +I may not evermore acknowledge thee, +Lest my bewailed guilt should do thee shame, +Nor thou with public kindness honour me, +Unless thou take that honour from thy name: +But do not so, I love thee in such sort, +As thou being mine, mine is thy good report. + +As a decrepit father takes delight, +To see his active child do deeds of youth, +So I, made lame by Fortune's dearest spite +Take all my comfort of thy worth and truth. +For whether beauty, birth, or wealth, or wit, +Or any of these all, or all, or more +Entitled in thy parts, do crowned sit, +I make my love engrafted to this store: +So then I am not lame, poor, nor despised, +Whilst that this shadow doth such substance give, +That I in thy abundance am sufficed, +And by a part of all thy glory live: +Look what is best, that best I wish in thee, +This wish I have, then ten times happy me. + +How can my muse want subject to invent +While thou dost breathe that pour'st into my verse, +Thine own sweet argument, too excellent, +For every vulgar paper to rehearse? +O give thy self the thanks if aught in me, +Worthy perusal stand against thy sight, +For who's so dumb that cannot write to thee, +When thou thy self dost give invention light? +Be thou the tenth Muse, ten times more in worth +Than those old nine which rhymers invocate, +And he that calls on thee, let him bring forth +Eternal numbers to outlive long date. +If my slight muse do please these curious days, +The pain be mine, but thine shall be the praise. + +O how thy worth with manners may I sing, +When thou art all the better part of me? +What can mine own praise to mine own self bring: +And what is't but mine own when I praise thee? +Even for this, let us divided live, +And our dear love lose name of single one, +That by this separation I may give: +That due to thee which thou deserv'st alone: +O absence what a torment wouldst thou prove, +Were it not thy sour leisure gave sweet leave, +To entertain the time with thoughts of love, +Which time and thoughts so sweetly doth deceive. +And that thou teachest how to make one twain, +By praising him here who doth hence remain. + +Take all my loves, my love, yea take them all, +What hast thou then more than thou hadst before? +No love, my love, that thou mayst true love call, +All mine was thine, before thou hadst this more: +Then if for my love, thou my love receivest, +I cannot blame thee, for my love thou usest, +But yet be blamed, if thou thy self deceivest +By wilful taste of what thy self refusest. +I do forgive thy robbery gentle thief +Although thou steal thee all my poverty: +And yet love knows it is a greater grief +To bear greater wrong, than hate's known injury. +Lascivious grace, in whom all ill well shows, +Kill me with spites yet we must not be foes. + +Those pretty wrongs that liberty commits, +When I am sometime absent from thy heart, +Thy beauty, and thy years full well befits, +For still temptation follows where thou art. +Gentle thou art, and therefore to be won, +Beauteous thou art, therefore to be assailed. +And when a woman woos, what woman's son, +Will sourly leave her till he have prevailed? +Ay me, but yet thou mightst my seat forbear, +And chide thy beauty, and thy straying youth, +Who lead thee in their riot even there +Where thou art forced to break a twofold truth: +Hers by thy beauty tempting her to thee, +Thine by thy beauty being false to me. + +That thou hast her it is not all my grief, +And yet it may be said I loved her dearly, +That she hath thee is of my wailing chief, +A loss in love that touches me more nearly. +Loving offenders thus I will excuse ye, +Thou dost love her, because thou know'st I love her, +And for my sake even so doth she abuse me, +Suff'ring my friend for my sake to approve her. +If I lose thee, my loss is my love's gain, +And losing her, my friend hath found that loss, +Both find each other, and I lose both twain, +And both for my sake lay on me this cross, +But here's the joy, my friend and I are one, +Sweet flattery, then she loves but me alone. + +When most I wink then do mine eyes best see, +For all the day they view things unrespected, +But when I sleep, in dreams they look on thee, +And darkly bright, are bright in dark directed. +Then thou whose shadow shadows doth make bright +How would thy shadow's form, form happy show, +To the clear day with thy much clearer light, +When to unseeing eyes thy shade shines so! +How would (I say) mine eyes be blessed made, +By looking on thee in the living day, +When in dead night thy fair imperfect shade, +Through heavy sleep on sightless eyes doth stay! +All days are nights to see till I see thee, +And nights bright days when dreams do show thee me. + +If the dull substance of my flesh were thought, +Injurious distance should not stop my way, +For then despite of space I would be brought, +From limits far remote, where thou dost stay, +No matter then although my foot did stand +Upon the farthest earth removed from thee, +For nimble thought can jump both sea and land, +As soon as think the place where he would be. +But ah, thought kills me that I am not thought +To leap large lengths of miles when thou art gone, +But that so much of earth and water wrought, +I must attend, time's leisure with my moan. +Receiving nought by elements so slow, +But heavy tears, badges of either's woe. + +The other two, slight air, and purging fire, +Are both with thee, wherever I abide, +The first my thought, the other my desire, +These present-absent with swift motion slide. +For when these quicker elements are gone +In tender embassy of love to thee, +My life being made of four, with two alone, +Sinks down to death, oppressed with melancholy. +Until life's composition be recured, +By those swift messengers returned from thee, +Who even but now come back again assured, +Of thy fair health, recounting it to me. +This told, I joy, but then no longer glad, +I send them back again and straight grow sad. + +Mine eye and heart are at a mortal war, +How to divide the conquest of thy sight, +Mine eye, my heart thy picture's sight would bar, +My heart, mine eye the freedom of that right, +My heart doth plead that thou in him dost lie, +(A closet never pierced with crystal eyes) +But the defendant doth that plea deny, +And says in him thy fair appearance lies. +To side this title is impanelled +A quest of thoughts, all tenants to the heart, +And by their verdict is determined +The clear eye's moiety, and the dear heart's part. +As thus, mine eye's due is thy outward part, +And my heart's right, thy inward love of heart. + +Betwixt mine eye and heart a league is took, +And each doth good turns now unto the other, +When that mine eye is famished for a look, +Or heart in love with sighs himself doth smother; +With my love's picture then my eye doth feast, +And to the painted banquet bids my heart: +Another time mine eye is my heart's guest, +And in his thoughts of love doth share a part. +So either by thy picture or my love, +Thy self away, art present still with me, +For thou not farther than my thoughts canst move, +And I am still with them, and they with thee. +Or if they sleep, thy picture in my sight +Awakes my heart, to heart's and eye's delight. + +How careful was I when I took my way, +Each trifle under truest bars to thrust, +That to my use it might unused stay +From hands of falsehood, in sure wards of trust! +But thou, to whom my jewels trifles are, +Most worthy comfort, now my greatest grief, +Thou best of dearest, and mine only care, +Art left the prey of every vulgar thief. +Thee have I not locked up in any chest, +Save where thou art not, though I feel thou art, +Within the gentle closure of my breast, +From whence at pleasure thou mayst come and part, +And even thence thou wilt be stol'n I fear, +For truth proves thievish for a prize so dear. + +Against that time (if ever that time come) +When I shall see thee frown on my defects, +When as thy love hath cast his utmost sum, +Called to that audit by advised respects, +Against that time when thou shalt strangely pass, +And scarcely greet me with that sun thine eye, +When love converted from the thing it was +Shall reasons find of settled gravity; +Against that time do I ensconce me here +Within the knowledge of mine own desert, +And this my hand, against my self uprear, +To guard the lawful reasons on thy part, +To leave poor me, thou hast the strength of laws, +Since why to love, I can allege no cause. + +How heavy do I journey on the way, +When what I seek (my weary travel's end) +Doth teach that case and that repose to say +'Thus far the miles are measured from thy friend.' +The beast that bears me, tired with my woe, +Plods dully on, to bear that weight in me, +As if by some instinct the wretch did know +His rider loved not speed being made from thee: +The bloody spur cannot provoke him on, +That sometimes anger thrusts into his hide, +Which heavily he answers with a groan, +More sharp to me than spurring to his side, +For that same groan doth put this in my mind, +My grief lies onward and my joy behind. + +Thus can my love excuse the slow offence, +Of my dull bearer, when from thee I speed, +From where thou art, why should I haste me thence? +Till I return of posting is no need. +O what excuse will my poor beast then find, +When swift extremity can seem but slow? +Then should I spur though mounted on the wind, +In winged speed no motion shall I know, +Then can no horse with my desire keep pace, +Therefore desire (of perfect'st love being made) +Shall neigh (no dull flesh) in his fiery race, +But love, for love, thus shall excuse my jade, +Since from thee going, he went wilful-slow, +Towards thee I'll run, and give him leave to go. + +So am I as the rich whose blessed key, +Can bring him to his sweet up-locked treasure, +The which he will not every hour survey, +For blunting the fine point of seldom pleasure. +Therefore are feasts so solemn and so rare, +Since seldom coming in that long year set, +Like stones of worth they thinly placed are, +Or captain jewels in the carcanet. +So is the time that keeps you as my chest +Or as the wardrobe which the robe doth hide, +To make some special instant special-blest, +By new unfolding his imprisoned pride. +Blessed are you whose worthiness gives scope, +Being had to triumph, being lacked to hope. + +What is your substance, whereof are you made, +That millions of strange shadows on you tend? +Since every one, hath every one, one shade, +And you but one, can every shadow lend: +Describe Adonis and the counterfeit, +Is poorly imitated after you, +On Helen's cheek all art of beauty set, +And you in Grecian tires are painted new: +Speak of the spring, and foison of the year, +The one doth shadow of your beauty show, +The other as your bounty doth appear, +And you in every blessed shape we know. +In all external grace you have some part, +But you like none, none you for constant heart. + +O how much more doth beauty beauteous seem, +By that sweet ornament which truth doth give! +The rose looks fair, but fairer we it deem +For that sweet odour, which doth in it live: +The canker blooms have full as deep a dye, +As the perfumed tincture of the roses, +Hang on such thorns, and play as wantonly, +When summer's breath their masked buds discloses: +But for their virtue only is their show, +They live unwooed, and unrespected fade, +Die to themselves. Sweet roses do not so, +Of their sweet deaths, are sweetest odours made: +And so of you, beauteous and lovely youth, +When that shall vade, by verse distills your truth. + +Not marble, nor the gilded monuments +Of princes shall outlive this powerful rhyme, +But you shall shine more bright in these contents +Than unswept stone, besmeared with sluttish time. +When wasteful war shall statues overturn, +And broils root out the work of masonry, +Nor Mars his sword, nor war's quick fire shall burn: +The living record of your memory. +'Gainst death, and all-oblivious enmity +Shall you pace forth, your praise shall still find room, +Even in the eyes of all posterity +That wear this world out to the ending doom. +So till the judgment that your self arise, +You live in this, and dwell in lovers' eyes. + +Sweet love renew thy force, be it not said +Thy edge should blunter be than appetite, +Which but to-day by feeding is allayed, +To-morrow sharpened in his former might. +So love be thou, although to-day thou fill +Thy hungry eyes, even till they wink with fulness, +To-morrow see again, and do not kill +The spirit of love, with a perpetual dulness: +Let this sad interim like the ocean be +Which parts the shore, where two contracted new, +Come daily to the banks, that when they see: +Return of love, more blest may be the view. +Or call it winter, which being full of care, +Makes summer's welcome, thrice more wished, more rare. + +Being your slave what should I do but tend, +Upon the hours, and times of your desire? +I have no precious time at all to spend; +Nor services to do till you require. +Nor dare I chide the world-without-end hour, +Whilst I (my sovereign) watch the clock for you, +Nor think the bitterness of absence sour, +When you have bid your servant once adieu. +Nor dare I question with my jealous thought, +Where you may be, or your affairs suppose, +But like a sad slave stay and think of nought +Save where you are, how happy you make those. +So true a fool is love, that in your will, +(Though you do any thing) he thinks no ill. + +That god forbid, that made me first your slave, +I should in thought control your times of pleasure, +Or at your hand th' account of hours to crave, +Being your vassal bound to stay your leisure. +O let me suffer (being at your beck) +Th' imprisoned absence of your liberty, +And patience tame to sufferance bide each check, +Without accusing you of injury. +Be where you list, your charter is so strong, +That you your self may privilage your time +To what you will, to you it doth belong, +Your self to pardon of self-doing crime. +I am to wait, though waiting so be hell, +Not blame your pleasure be it ill or well. + +If there be nothing new, but that which is, +Hath been before, how are our brains beguiled, +Which labouring for invention bear amis +The second burthen of a former child! +O that record could with a backward look, +Even of five hundred courses of the sun, +Show me your image in some antique book, +Since mind at first in character was done. +That I might see what the old world could say, +To this composed wonder of your frame, +Whether we are mended, or whether better they, +Or whether revolution be the same. +O sure I am the wits of former days, +To subjects worse have given admiring praise. + +Like as the waves make towards the pebbled shore, +So do our minutes hasten to their end, +Each changing place with that which goes before, +In sequent toil all forwards do contend. +Nativity once in the main of light, +Crawls to maturity, wherewith being crowned, +Crooked eclipses 'gainst his glory fight, +And Time that gave, doth now his gift confound. +Time doth transfix the flourish set on youth, +And delves the parallels in beauty's brow, +Feeds on the rarities of nature's truth, +And nothing stands but for his scythe to mow. +And yet to times in hope, my verse shall stand +Praising thy worth, despite his cruel hand. + +Is it thy will, thy image should keep open +My heavy eyelids to the weary night? +Dost thou desire my slumbers should be broken, +While shadows like to thee do mock my sight? +Is it thy spirit that thou send'st from thee +So far from home into my deeds to pry, +To find out shames and idle hours in me, +The scope and tenure of thy jealousy? +O no, thy love though much, is not so great, +It is my love that keeps mine eye awake, +Mine own true love that doth my rest defeat, +To play the watchman ever for thy sake. +For thee watch I, whilst thou dost wake elsewhere, +From me far off, with others all too near. + +Sin of self-love possesseth all mine eye, +And all my soul, and all my every part; +And for this sin there is no remedy, +It is so grounded inward in my heart. +Methinks no face so gracious is as mine, +No shape so true, no truth of such account, +And for my self mine own worth do define, +As I all other in all worths surmount. +But when my glass shows me my self indeed +beated and chopt with tanned antiquity, +Mine own self-love quite contrary I read: +Self, so self-loving were iniquity. +'Tis thee (my self) that for my self I praise, +Painting my age with beauty of thy days. + +Against my love shall be as I am now +With Time's injurious hand crushed and o'erworn, +When hours have drained his blood and filled his brow +With lines and wrinkles, when his youthful morn +Hath travelled on to age's steepy night, +And all those beauties whereof now he's king +Are vanishing, or vanished out of sight, +Stealing away the treasure of his spring: +For such a time do I now fortify +Against confounding age's cruel knife, +That he shall never cut from memory +My sweet love's beauty, though my lover's life. +His beauty shall in these black lines be seen, +And they shall live, and he in them still green. + +When I have seen by Time's fell hand defaced +The rich-proud cost of outworn buried age, +When sometime lofty towers I see down-rased, +And brass eternal slave to mortal rage. +When I have seen the hungry ocean gain +Advantage on the kingdom of the shore, +And the firm soil win of the watery main, +Increasing store with loss, and loss with store. +When I have seen such interchange of State, +Or state it self confounded, to decay, +Ruin hath taught me thus to ruminate +That Time will come and take my love away. +This thought is as a death which cannot choose +But weep to have, that which it fears to lose. + +Since brass, nor stone, nor earth, nor boundless sea, +But sad mortality o'ersways their power, +How with this rage shall beauty hold a plea, +Whose action is no stronger than a flower? +O how shall summer's honey breath hold out, +Against the wrackful siege of batt'ring days, +When rocks impregnable are not so stout, +Nor gates of steel so strong but time decays? +O fearful meditation, where alack, +Shall Time's best jewel from Time's chest lie hid? +Or what strong hand can hold his swift foot back, +Or who his spoil of beauty can forbid? +O none, unless this miracle have might, +That in black ink my love may still shine bright. + +Tired with all these for restful death I cry, +As to behold desert a beggar born, +And needy nothing trimmed in jollity, +And purest faith unhappily forsworn, +And gilded honour shamefully misplaced, +And maiden virtue rudely strumpeted, +And right perfection wrongfully disgraced, +And strength by limping sway disabled +And art made tongue-tied by authority, +And folly (doctor-like) controlling skill, +And simple truth miscalled simplicity, +And captive good attending captain ill. +Tired with all these, from these would I be gone, +Save that to die, I leave my love alone. + +Ah wherefore with infection should he live, +And with his presence grace impiety, +That sin by him advantage should achieve, +And lace it self with his society? +Why should false painting imitate his cheek, +And steal dead seeming of his living hue? +Why should poor beauty indirectly seek, +Roses of shadow, since his rose is true? +Why should he live, now nature bankrupt is, +Beggared of blood to blush through lively veins, +For she hath no exchequer now but his, +And proud of many, lives upon his gains? +O him she stores, to show what wealth she had, +In days long since, before these last so bad. + +Thus is his cheek the map of days outworn, +When beauty lived and died as flowers do now, +Before these bastard signs of fair were born, +Or durst inhabit on a living brow: +Before the golden tresses of the dead, +The right of sepulchres, were shorn away, +To live a second life on second head, +Ere beauty's dead fleece made another gay: +In him those holy antique hours are seen, +Without all ornament, it self and true, +Making no summer of another's green, +Robbing no old to dress his beauty new, +And him as for a map doth Nature store, +To show false Art what beauty was of yore. + +Those parts of thee that the world's eye doth view, +Want nothing that the thought of hearts can mend: +All tongues (the voice of souls) give thee that due, +Uttering bare truth, even so as foes commend. +Thy outward thus with outward praise is crowned, +But those same tongues that give thee so thine own, +In other accents do this praise confound +By seeing farther than the eye hath shown. +They look into the beauty of thy mind, +And that in guess they measure by thy deeds, +Then churls their thoughts (although their eyes were kind) +To thy fair flower add the rank smell of weeds: +But why thy odour matcheth not thy show, +The soil is this, that thou dost common grow. + + + +That thou art blamed shall not be thy defect, +For slander's mark was ever yet the fair, +The ornament of beauty is suspect, +A crow that flies in heaven's sweetest air. +So thou be good, slander doth but approve, +Thy worth the greater being wooed of time, +For canker vice the sweetest buds doth love, +And thou present'st a pure unstained prime. +Thou hast passed by the ambush of young days, +Either not assailed, or victor being charged, +Yet this thy praise cannot be so thy praise, +To tie up envy, evermore enlarged, +If some suspect of ill masked not thy show, +Then thou alone kingdoms of hearts shouldst owe. + + + +No longer mourn for me when I am dead, +Than you shall hear the surly sullen bell +Give warning to the world that I am fled +From this vile world with vilest worms to dwell: +Nay if you read this line, remember not, +The hand that writ it, for I love you so, +That I in your sweet thoughts would be forgot, +If thinking on me then should make you woe. +O if (I say) you look upon this verse, +When I (perhaps) compounded am with clay, +Do not so much as my poor name rehearse; +But let your love even with my life decay. +Lest the wise world should look into your moan, +And mock you with me after I am gone. + + + +O lest the world should task you to recite, +What merit lived in me that you should love +After my death (dear love) forget me quite, +For you in me can nothing worthy prove. +Unless you would devise some virtuous lie, +To do more for me than mine own desert, +And hang more praise upon deceased I, +Than niggard truth would willingly impart: +O lest your true love may seem false in this, +That you for love speak well of me untrue, +My name be buried where my body is, +And live no more to shame nor me, nor you. +For I am shamed by that which I bring forth, +And so should you, to love things nothing worth. + + + +That time of year thou mayst in me behold, +When yellow leaves, or none, or few do hang +Upon those boughs which shake against the cold, +Bare ruined choirs, where late the sweet birds sang. +In me thou seest the twilight of such day, +As after sunset fadeth in the west, +Which by and by black night doth take away, +Death's second self that seals up all in rest. +In me thou seest the glowing of such fire, +That on the ashes of his youth doth lie, +As the death-bed, whereon it must expire, +Consumed with that which it was nourished by. +This thou perceiv'st, which makes thy love more strong, +To love that well, which thou must leave ere long. + + + +But be contented when that fell arrest, +Without all bail shall carry me away, +My life hath in this line some interest, +Which for memorial still with thee shall stay. +When thou reviewest this, thou dost review, +The very part was consecrate to thee, +The earth can have but earth, which is his due, +My spirit is thine the better part of me, +So then thou hast but lost the dregs of life, +The prey of worms, my body being dead, +The coward conquest of a wretch's knife, +Too base of thee to be remembered, +The worth of that, is that which it contains, +And that is this, and this with thee remains. + + + +So are you to my thoughts as food to life, +Or as sweet-seasoned showers are to the ground; +And for the peace of you I hold such strife +As 'twixt a miser and his wealth is found. +Now proud as an enjoyer, and anon +Doubting the filching age will steal his treasure, +Now counting best to be with you alone, +Then bettered that the world may see my pleasure, +Sometime all full with feasting on your sight, +And by and by clean starved for a look, +Possessing or pursuing no delight +Save what is had, or must from you be took. +Thus do I pine and surfeit day by day, +Or gluttoning on all, or all away. + + + +Why is my verse so barren of new pride? +So far from variation or quick change? +Why with the time do I not glance aside +To new-found methods, and to compounds strange? +Why write I still all one, ever the same, +And keep invention in a noted weed, +That every word doth almost tell my name, +Showing their birth, and where they did proceed? +O know sweet love I always write of you, +And you and love are still my argument: +So all my best is dressing old words new, +Spending again what is already spent: +For as the sun is daily new and old, +So is my love still telling what is told. + + + +Thy glass will show thee how thy beauties wear, +Thy dial how thy precious minutes waste, +These vacant leaves thy mind's imprint will bear, +And of this book, this learning mayst thou taste. +The wrinkles which thy glass will truly show, +Of mouthed graves will give thee memory, +Thou by thy dial's shady stealth mayst know, +Time's thievish progress to eternity. +Look what thy memory cannot contain, +Commit to these waste blanks, and thou shalt find +Those children nursed, delivered from thy brain, +To take a new acquaintance of thy mind. +These offices, so oft as thou wilt look, +Shall profit thee, and much enrich thy book. + + + +So oft have I invoked thee for my muse, +And found such fair assistance in my verse, +As every alien pen hath got my use, +And under thee their poesy disperse. +Thine eyes, that taught the dumb on high to sing, +And heavy ignorance aloft to fly, +Have added feathers to the learned's wing, +And given grace a double majesty. +Yet be most proud of that which I compile, +Whose influence is thine, and born of thee, +In others' works thou dost but mend the style, +And arts with thy sweet graces graced be. +But thou art all my art, and dost advance +As high as learning, my rude ignorance. + + + +Whilst I alone did call upon thy aid, +My verse alone had all thy gentle grace, +But now my gracious numbers are decayed, +And my sick muse doth give an other place. +I grant (sweet love) thy lovely argument +Deserves the travail of a worthier pen, +Yet what of thee thy poet doth invent, +He robs thee of, and pays it thee again, +He lends thee virtue, and he stole that word, +From thy behaviour, beauty doth he give +And found it in thy cheek: he can afford +No praise to thee, but what in thee doth live. +Then thank him not for that which he doth say, +Since what he owes thee, thou thy self dost pay. + + + +O how I faint when I of you do write, +Knowing a better spirit doth use your name, +And in the praise thereof spends all his might, +To make me tongue-tied speaking of your fame. +But since your worth (wide as the ocean is) +The humble as the proudest sail doth bear, +My saucy bark (inferior far to his) +On your broad main doth wilfully appear. +Your shallowest help will hold me up afloat, +Whilst he upon your soundless deep doth ride, +Or (being wrecked) I am a worthless boat, +He of tall building, and of goodly pride. +Then if he thrive and I be cast away, +The worst was this, my love was my decay. + + + +Or I shall live your epitaph to make, +Or you survive when I in earth am rotten, +From hence your memory death cannot take, +Although in me each part will be forgotten. +Your name from hence immortal life shall have, +Though I (once gone) to all the world must die, +The earth can yield me but a common grave, +When you entombed in men's eyes shall lie, +Your monument shall be my gentle verse, +Which eyes not yet created shall o'er-read, +And tongues to be, your being shall rehearse, +When all the breathers of this world are dead, +You still shall live (such virtue hath my pen) +Where breath most breathes, even in the mouths of men. + + + +I grant thou wert not married to my muse, +And therefore mayst without attaint o'erlook +The dedicated words which writers use +Of their fair subject, blessing every book. +Thou art as fair in knowledge as in hue, +Finding thy worth a limit past my praise, +And therefore art enforced to seek anew, +Some fresher stamp of the time-bettering days. +And do so love, yet when they have devised, +What strained touches rhetoric can lend, +Thou truly fair, wert truly sympathized, +In true plain words, by thy true-telling friend. +And their gross painting might be better used, +Where cheeks need blood, in thee it is abused. + + + +I never saw that you did painting need, +And therefore to your fair no painting set, +I found (or thought I found) you did exceed, +That barren tender of a poet's debt: +And therefore have I slept in your report, +That you your self being extant well might show, +How far a modern quill doth come too short, +Speaking of worth, what worth in you doth grow. +This silence for my sin you did impute, +Which shall be most my glory being dumb, +For I impair not beauty being mute, +When others would give life, and bring a tomb. +There lives more life in one of your fair eyes, +Than both your poets can in praise devise. + + + +Who is it that says most, which can say more, +Than this rich praise, that you alone, are you? +In whose confine immured is the store, +Which should example where your equal grew. +Lean penury within that pen doth dwell, +That to his subject lends not some small glory, +But he that writes of you, if he can tell, +That you are you, so dignifies his story. +Let him but copy what in you is writ, +Not making worse what nature made so clear, +And such a counterpart shall fame his wit, +Making his style admired every where. +You to your beauteous blessings add a curse, +Being fond on praise, which makes your praises worse. + + + +My tongue-tied muse in manners holds her still, +While comments of your praise richly compiled, +Reserve their character with golden quill, +And precious phrase by all the Muses filed. +I think good thoughts, whilst other write good words, +And like unlettered clerk still cry Amen, +To every hymn that able spirit affords, +In polished form of well refined pen. +Hearing you praised, I say 'tis so, 'tis true, +And to the most of praise add something more, +But that is in my thought, whose love to you +(Though words come hindmost) holds his rank before, +Then others, for the breath of words respect, +Me for my dumb thoughts, speaking in effect. + + + +Was it the proud full sail of his great verse, +Bound for the prize of (all too precious) you, +That did my ripe thoughts in my brain inhearse, +Making their tomb the womb wherein they grew? +Was it his spirit, by spirits taught to write, +Above a mortal pitch, that struck me dead? +No, neither he, nor his compeers by night +Giving him aid, my verse astonished. +He nor that affable familiar ghost +Which nightly gulls him with intelligence, +As victors of my silence cannot boast, +I was not sick of any fear from thence. +But when your countenance filled up his line, +Then lacked I matter, that enfeebled mine. + + + +Farewell! thou art too dear for my possessing, +And like enough thou know'st thy estimate, +The charter of thy worth gives thee releasing: +My bonds in thee are all determinate. +For how do I hold thee but by thy granting, +And for that riches where is my deserving? +The cause of this fair gift in me is wanting, +And so my patent back again is swerving. +Thy self thou gav'st, thy own worth then not knowing, +Or me to whom thou gav'st it, else mistaking, +So thy great gift upon misprision growing, +Comes home again, on better judgement making. +Thus have I had thee as a dream doth flatter, +In sleep a king, but waking no such matter. + + + +When thou shalt be disposed to set me light, +And place my merit in the eye of scorn, +Upon thy side, against my self I'll fight, +And prove thee virtuous, though thou art forsworn: +With mine own weakness being best acquainted, +Upon thy part I can set down a story +Of faults concealed, wherein I am attainted: +That thou in losing me, shalt win much glory: +And I by this will be a gainer too, +For bending all my loving thoughts on thee, +The injuries that to my self I do, +Doing thee vantage, double-vantage me. +Such is my love, to thee I so belong, +That for thy right, my self will bear all wrong. + + + +Say that thou didst forsake me for some fault, +And I will comment upon that offence, +Speak of my lameness, and I straight will halt: +Against thy reasons making no defence. +Thou canst not (love) disgrace me half so ill, +To set a form upon desired change, +As I'll my self disgrace, knowing thy will, +I will acquaintance strangle and look strange: +Be absent from thy walks and in my tongue, +Thy sweet beloved name no more shall dwell, +Lest I (too much profane) should do it wronk: +And haply of our old acquaintance tell. +For thee, against my self I'll vow debate, +For I must ne'er love him whom thou dost hate. + + + +Then hate me when thou wilt, if ever, now, +Now while the world is bent my deeds to cross, +join with the spite of fortune, make me bow, +And do not drop in for an after-loss: +Ah do not, when my heart hath 'scaped this sorrow, +Come in the rearward of a conquered woe, +Give not a windy night a rainy morrow, +To linger out a purposed overthrow. +If thou wilt leave me, do not leave me last, +When other petty griefs have done their spite, +But in the onset come, so shall I taste +At first the very worst of fortune's might. +And other strains of woe, which now seem woe, +Compared with loss of thee, will not seem so. + + + +Some glory in their birth, some in their skill, +Some in their wealth, some in their body's force, +Some in their garments though new-fangled ill: +Some in their hawks and hounds, some in their horse. +And every humour hath his adjunct pleasure, +Wherein it finds a joy above the rest, +But these particulars are not my measure, +All these I better in one general best. +Thy love is better than high birth to me, +Richer than wealth, prouder than garments' costs, +Of more delight than hawks and horses be: +And having thee, of all men's pride I boast. +Wretched in this alone, that thou mayst take, +All this away, and me most wretchcd make. + + + +But do thy worst to steal thy self away, +For term of life thou art assured mine, +And life no longer than thy love will stay, +For it depends upon that love of thine. +Then need I not to fear the worst of wrongs, +When in the least of them my life hath end, +I see, a better state to me belongs +Than that, which on thy humour doth depend. +Thou canst not vex me with inconstant mind, +Since that my life on thy revolt doth lie, +O what a happy title do I find, +Happy to have thy love, happy to die! +But what's so blessed-fair that fears no blot? +Thou mayst be false, and yet I know it not. + + + +So shall I live, supposing thou art true, +Like a deceived husband, so love's face, +May still seem love to me, though altered new: +Thy looks with me, thy heart in other place. +For there can live no hatred in thine eye, +Therefore in that I cannot know thy change, +In many's looks, the false heart's history +Is writ in moods and frowns and wrinkles strange. +But heaven in thy creation did decree, +That in thy face sweet love should ever dwell, +Whate'er thy thoughts, or thy heart's workings be, +Thy looks should nothing thence, but sweetness tell. +How like Eve's apple doth thy beauty grow, +If thy sweet virtue answer not thy show. + + + +They that have power to hurt, and will do none, +That do not do the thing, they most do show, +Who moving others, are themselves as stone, +Unmoved, cold, and to temptation slow: +They rightly do inherit heaven's graces, +And husband nature's riches from expense, +Tibey are the lords and owners of their faces, +Others, but stewards of their excellence: +The summer's flower is to the summer sweet, +Though to it self, it only live and die, +But if that flower with base infection meet, +The basest weed outbraves his dignity: +For sweetest things turn sourest by their deeds, +Lilies that fester, smell far worse than weeds. + + + +How sweet and lovely dost thou make the shame, +Which like a canker in the fragrant rose, +Doth spot the beauty of thy budding name! +O in what sweets dost thou thy sins enclose! +That tongue that tells the story of thy days, +(Making lascivious comments on thy sport) +Cannot dispraise, but in a kind of praise, +Naming thy name, blesses an ill report. +O what a mansion have those vices got, +Which for their habitation chose out thee, +Where beauty's veil doth cover every blot, +And all things turns to fair, that eyes can see! +Take heed (dear heart) of this large privilege, +The hardest knife ill-used doth lose his edge. + + + +Some say thy fault is youth, some wantonness, +Some say thy grace is youth and gentle sport, +Both grace and faults are loved of more and less: +Thou mak'st faults graces, that to thee resort: +As on the finger of a throned queen, +The basest jewel will be well esteemed: +So are those errors that in thee are seen, +To truths translated, and for true things deemed. +How many lambs might the stern wolf betray, +If like a lamb he could his looks translate! +How many gazers mightst thou lead away, +if thou wouldst use the strength of all thy state! +But do not so, I love thee in such sort, +As thou being mine, mine is thy good report. + + + +How like a winter hath my absence been +From thee, the pleasure of the fleeting year! +What freezings have I felt, what dark days seen! +What old December's bareness everywhere! +And yet this time removed was summer's time, +The teeming autumn big with rich increase, +Bearing the wanton burden of the prime, +Like widowed wombs after their lords' decease: +Yet this abundant issue seemed to me +But hope of orphans, and unfathered fruit, +For summer and his pleasures wait on thee, +And thou away, the very birds are mute. +Or if they sing, 'tis with so dull a cheer, +That leaves look pale, dreading the winter's near. + + + +From you have I been absent in the spring, +When proud-pied April (dressed in all his trim) +Hath put a spirit of youth in every thing: +That heavy Saturn laughed and leaped with him. +Yet nor the lays of birds, nor the sweet smell +Of different flowers in odour and in hue, +Could make me any summer's story tell: +Or from their proud lap pluck them where they grew: +Nor did I wonder at the lily's white, +Nor praise the deep vermilion in the rose, +They were but sweet, but figures of delight: +Drawn after you, you pattern of all those. +Yet seemed it winter still, and you away, +As with your shadow I with these did play. + + + +The forward violet thus did I chide, +Sweet thief, whence didst thou steal thy sweet that smells, +If not from my love's breath? The purple pride +Which on thy soft check for complexion dwells, +In my love's veins thou hast too grossly dyed. +The lily I condemned for thy hand, +And buds of marjoram had stol'n thy hair, +The roses fearfully on thorns did stand, +One blushing shame, another white despair: +A third nor red, nor white, had stol'n of both, +And to his robbery had annexed thy breath, +But for his theft in pride of all his growth +A vengeful canker eat him up to death. +More flowers I noted, yet I none could see, +But sweet, or colour it had stol'n from thee. + + + +Where art thou Muse that thou forget'st so long, +To speak of that which gives thee all thy might? +Spend'st thou thy fury on some worthless song, +Darkening thy power to lend base subjects light? +Return forgetful Muse, and straight redeem, +In gentle numbers time so idly spent, +Sing to the ear that doth thy lays esteem, +And gives thy pen both skill and argument. +Rise resty Muse, my love's sweet face survey, +If time have any wrinkle graven there, +If any, be a satire to decay, +And make time's spoils despised everywhere. +Give my love fame faster than Time wastes life, +So thou prevent'st his scythe, and crooked knife. + + + +O truant Muse what shall be thy amends, +For thy neglect of truth in beauty dyed? +Both truth and beauty on my love depends: +So dost thou too, and therein dignified: +Make answer Muse, wilt thou not haply say, +'Truth needs no colour with his colour fixed, +Beauty no pencil, beauty's truth to lay: +But best is best, if never intermixed'? +Because he needs no praise, wilt thou be dumb? +Excuse not silence so, for't lies in thee, +To make him much outlive a gilded tomb: +And to be praised of ages yet to be. +Then do thy office Muse, I teach thee how, +To make him seem long hence, as he shows now. + + + +My love is strengthened though more weak in seeming, +I love not less, though less the show appear, +That love is merchandized, whose rich esteeming, +The owner's tongue doth publish every where. +Our love was new, and then but in the spring, +When I was wont to greet it with my lays, +As Philomel in summer's front doth sing, +And stops her pipe in growth of riper days: +Not that the summer is less pleasant now +Than when her mournful hymns did hush the night, +But that wild music burthens every bough, +And sweets grown common lose their dear delight. +Therefore like her, I sometime hold my tongue: +Because I would not dull you with my song. + + + +Alack what poverty my muse brings forth, +That having such a scope to show her pride, +The argument all bare is of more worth +Than when it hath my added praise beside. +O blame me not if I no more can write! +Look in your glass and there appears a face, +That over-goes my blunt invention quite, +Dulling my lines, and doing me disgrace. +Were it not sinful then striving to mend, +To mar the subject that before was well? +For to no other pass my verses tend, +Than of your graces and your gifts to tell. +And more, much more than in my verse can sit, +Your own glass shows you, when you look in it. + + + +To me fair friend you never can be old, +For as you were when first your eye I eyed, +Such seems your beauty still: three winters cold, +Have from the forests shook three summers' pride, +Three beauteous springs to yellow autumn turned, +In process of the seasons have I seen, +Three April perfumes in three hot Junes burned, +Since first I saw you fresh which yet are green. +Ah yet doth beauty like a dial hand, +Steal from his figure, and no pace perceived, +So your sweet hue, which methinks still doth stand +Hath motion, and mine eye may be deceived. +For fear of which, hear this thou age unbred, +Ere you were born was beauty's summer dead. + + + +Let not my love be called idolatry, +Nor my beloved as an idol show, +Since all alike my songs and praises be +To one, of one, still such, and ever so. +Kind is my love to-day, to-morrow kind, +Still constant in a wondrous excellence, +Therefore my verse to constancy confined, +One thing expressing, leaves out difference. +Fair, kind, and true, is all my argument, +Fair, kind, and true, varying to other words, +And in this change is my invention spent, +Three themes in one, which wondrous scope affords. +Fair, kind, and true, have often lived alone. +Which three till now, never kept seat in one. + + + +When in the chronicle of wasted time, +I see descriptions of the fairest wights, +And beauty making beautiful old rhyme, +In praise of ladies dead, and lovely knights, +Then in the blazon of sweet beauty's best, +Of hand, of foot, of lip, of eye, of brow, +I see their antique pen would have expressed, +Even such a beauty as you master now. +So all their praises are but prophecies +Of this our time, all you prefiguring, +And for they looked but with divining eyes, +They had not skill enough your worth to sing: +For we which now behold these present days, +Have eyes to wonder, but lack tongues to praise. + + + +Not mine own fears, nor the prophetic soul, +Of the wide world, dreaming on things to come, +Can yet the lease of my true love control, +Supposed as forfeit to a confined doom. +The mortal moon hath her eclipse endured, +And the sad augurs mock their own presage, +Incertainties now crown themselves assured, +And peace proclaims olives of endless age. +Now with the drops of this most balmy time, +My love looks fresh, and death to me subscribes, +Since spite of him I'll live in this poor rhyme, +While he insults o'er dull and speechless tribes. +And thou in this shalt find thy monument, +When tyrants' crests and tombs of brass are spent. + + + +What's in the brain that ink may character, +Which hath not figured to thee my true spirit, +What's new to speak, what now to register, +That may express my love, or thy dear merit? +Nothing sweet boy, but yet like prayers divine, +I must each day say o'er the very same, +Counting no old thing old, thou mine, I thine, +Even as when first I hallowed thy fair name. +So that eternal love in love's fresh case, +Weighs not the dust and injury of age, +Nor gives to necessary wrinkles place, +But makes antiquity for aye his page, +Finding the first conceit of love there bred, +Where time and outward form would show it dead. + + + +O never say that I was false of heart, +Though absence seemed my flame to qualify, +As easy might I from my self depart, +As from my soul which in thy breast doth lie: +That is my home of love, if I have ranged, +Like him that travels I return again, +Just to the time, not with the time exchanged, +So that my self bring water for my stain, +Never believe though in my nature reigned, +All frailties that besiege all kinds of blood, +That it could so preposterously be stained, +To leave for nothing all thy sum of good: +For nothing this wide universe I call, +Save thou my rose, in it thou art my all. + + + +Alas 'tis true, I have gone here and there, +And made my self a motley to the view, +Gored mine own thoughts, sold cheap what is most dear, +Made old offences of affections new. +Most true it is, that I have looked on truth +Askance and strangely: but by all above, +These blenches gave my heart another youth, +And worse essays proved thee my best of love. +Now all is done, have what shall have no end, +Mine appetite I never more will grind +On newer proof, to try an older friend, +A god in love, to whom I am confined. +Then give me welcome, next my heaven the best, +Even to thy pure and most most loving breast. + + + +O for my sake do you with Fortune chide, +The guilty goddess of my harmful deeds, +That did not better for my life provide, +Than public means which public manners breeds. +Thence comes it that my name receives a brand, +And almost thence my nature is subdued +To what it works in, like the dyer's hand: +Pity me then, and wish I were renewed, +Whilst like a willing patient I will drink, +Potions of eisel 'gainst my strong infection, +No bitterness that I will bitter think, +Nor double penance to correct correction. +Pity me then dear friend, and I assure ye, +Even that your pity is enough to cure me. + + + +Your love and pity doth th' impression fill, +Which vulgar scandal stamped upon my brow, +For what care I who calls me well or ill, +So you o'er-green my bad, my good allow? +You are my all the world, and I must strive, +To know my shames and praises from your tongue, +None else to me, nor I to none alive, +That my steeled sense or changes right or wrong. +In so profound abysm I throw all care +Of others' voices, that my adder's sense, +To critic and to flatterer stopped are: +Mark how with my neglect I do dispense. +You are so strongly in my purpose bred, +That all the world besides methinks are dead. + + + +Since I left you, mine eye is in my mind, +And that which governs me to go about, +Doth part his function, and is partly blind, +Seems seeing, but effectually is out: +For it no form delivers to the heart +Of bird, of flower, or shape which it doth latch, +Of his quick objects hath the mind no part, +Nor his own vision holds what it doth catch: +For if it see the rud'st or gentlest sight, +The most sweet favour or deformed'st creature, +The mountain, or the sea, the day, or night: +The crow, or dove, it shapes them to your feature. +Incapable of more, replete with you, +My most true mind thus maketh mine untrue. + + + +Or whether doth my mind being crowned with you +Drink up the monarch's plague this flattery? +Or whether shall I say mine eye saith true, +And that your love taught it this alchemy? +To make of monsters, and things indigest, +Such cherubins as your sweet self resemble, +Creating every bad a perfect best +As fast as objects to his beams assemble: +O 'tis the first, 'tis flattery in my seeing, +And my great mind most kingly drinks it up, +Mine eye well knows what with his gust is 'greeing, +And to his palate doth prepare the cup. +If it be poisoned, 'tis the lesser sin, +That mine eye loves it and doth first begin. + + + +Those lines that I before have writ do lie, +Even those that said I could not love you dearer, +Yet then my judgment knew no reason why, +My most full flame should afterwards burn clearer, +But reckoning time, whose millioned accidents +Creep in 'twixt vows, and change decrees of kings, +Tan sacred beauty, blunt the sharp'st intents, +Divert strong minds to the course of alt'ring things: +Alas why fearing of time's tyranny, +Might I not then say 'Now I love you best,' +When I was certain o'er incertainty, +Crowning the present, doubting of the rest? +Love is a babe, then might I not say so +To give full growth to that which still doth grow. + + + +Let me not to the marriage of true minds +Admit impediments, love is not love +Which alters when it alteration finds, +Or bends with the remover to remove. +O no, it is an ever-fixed mark +That looks on tempests and is never shaken; +It is the star to every wand'ring bark, +Whose worth's unknown, although his height be taken. +Love's not Time's fool, though rosy lips and cheeks +Within his bending sickle's compass come, +Love alters not with his brief hours and weeks, +But bears it out even to the edge of doom: +If this be error and upon me proved, +I never writ, nor no man ever loved. + + + +Accuse me thus, that I have scanted all, +Wherein I should your great deserts repay, +Forgot upon your dearest love to call, +Whereto all bonds do tie me day by day, +That I have frequent been with unknown minds, +And given to time your own dear-purchased right, +That I have hoisted sail to all the winds +Which should transport me farthest from your sight. +Book both my wilfulness and errors down, +And on just proof surmise, accumulate, +Bring me within the level of your frown, +But shoot not at me in your wakened hate: +Since my appeal says I did strive to prove +The constancy and virtue of your love. + + + +Like as to make our appetite more keen +With eager compounds we our palate urge, +As to prevent our maladies unseen, +We sicken to shun sickness when we purge. +Even so being full of your ne'er-cloying sweetness, +To bitter sauces did I frame my feeding; +And sick of welfare found a kind of meetness, +To be diseased ere that there was true needing. +Thus policy in love t' anticipate +The ills that were not, grew to faults assured, +And brought to medicine a healthful state +Which rank of goodness would by ill be cured. +But thence I learn and find the lesson true, +Drugs poison him that so feil sick of you. + + + +What potions have I drunk of Siren tears +Distilled from limbecks foul as hell within, +Applying fears to hopes, and hopes to fears, +Still losing when I saw my self to win! +What wretched errors hath my heart committed, +Whilst it hath thought it self so blessed never! +How have mine eyes out of their spheres been fitted +In the distraction of this madding fever! +O benefit of ill, now I find true +That better is, by evil still made better. +And ruined love when it is built anew +Grows fairer than at first, more strong, far greater. +So I return rebuked to my content, +And gain by ills thrice more than I have spent. + + + +That you were once unkind befriends me now, +And for that sorrow, which I then did feel, +Needs must I under my transgression bow, +Unless my nerves were brass or hammered steel. +For if you were by my unkindness shaken +As I by yours, y'have passed a hell of time, +And I a tyrant have no leisure taken +To weigh how once I suffered in your crime. +O that our night of woe might have remembered +My deepest sense, how hard true sorrow hits, +And soon to you, as you to me then tendered +The humble salve, which wounded bosoms fits! +But that your trespass now becomes a fee, +Mine ransoms yours, and yours must ransom me. + + + +'Tis better to be vile than vile esteemed, +When not to be, receives reproach of being, +And the just pleasure lost, which is so deemed, +Not by our feeling, but by others' seeing. +For why should others' false adulterate eyes +Give salutation to my sportive blood? +Or on my frailties why are frailer spies, +Which in their wills count bad what I think good? +No, I am that I am, and they that level +At my abuses, reckon up their own, +I may be straight though they themselves be bevel; +By their rank thoughts, my deeds must not be shown +Unless this general evil they maintain, +All men are bad and in their badness reign. + + + +Thy gift, thy tables, are within my brain +Full charactered with lasting memory, +Which shall above that idle rank remain +Beyond all date even to eternity. +Or at the least, so long as brain and heart +Have faculty by nature to subsist, +Till each to razed oblivion yield his part +Of thee, thy record never can be missed: +That poor retention could not so much hold, +Nor need I tallies thy dear love to score, +Therefore to give them from me was I bold, +To trust those tables that receive thee more: +To keep an adjunct to remember thee +Were to import forgetfulness in me. + + + +No! Time, thou shalt not boast that I do change, +Thy pyramids built up with newer might +To me are nothing novel, nothing strange, +They are but dressings Of a former sight: +Our dates are brief, and therefore we admire, +What thou dost foist upon us that is old, +And rather make them born to our desire, +Than think that we before have heard them told: +Thy registers and thee I both defy, +Not wond'ring at the present, nor the past, +For thy records, and what we see doth lie, +Made more or less by thy continual haste: +This I do vow and this shall ever be, +I will be true despite thy scythe and thee. + + + +If my dear love were but the child of state, +It might for Fortune's bastard be unfathered, +As subject to time's love or to time's hate, +Weeds among weeds, or flowers with flowers gathered. +No it was builded far from accident, +It suffers not in smiling pomp, nor falls +Under the blow of thralled discontent, +Whereto th' inviting time our fashion calls: +It fears not policy that heretic, +Which works on leases of short-numbered hours, +But all alone stands hugely politic, +That it nor grows with heat, nor drowns with showers. +To this I witness call the fools of time, +Which die for goodness, who have lived for crime. + + + +Were't aught to me I bore the canopy, +With my extern the outward honouring, +Or laid great bases for eternity, +Which proves more short than waste or ruining? +Have I not seen dwellers on form and favour +Lose all, and more by paying too much rent +For compound sweet; forgoing simple savour, +Pitiful thrivers in their gazing spent? +No, let me be obsequious in thy heart, +And take thou my oblation, poor but free, +Which is not mixed with seconds, knows no art, +But mutual render, only me for thee. +Hence, thou suborned informer, a true soul +When most impeached, stands least in thy control. + + + +O thou my lovely boy who in thy power, +Dost hold Time's fickle glass his fickle hour: +Who hast by waning grown, and therein show'st, +Thy lovers withering, as thy sweet self grow'st. +If Nature (sovereign mistress over wrack) +As thou goest onwards still will pluck thee back, +She keeps thee to this purpose, that her skill +May time disgrace, and wretched minutes kill. +Yet fear her O thou minion of her pleasure, +She may detain, but not still keep her treasure! +Her audit (though delayed) answered must be, +And her quietus is to render thee. + + + +In the old age black was not counted fair, +Or if it were it bore not beauty's name: +But now is black beauty's successive heir, +And beauty slandered with a bastard shame, +For since each hand hath put on nature's power, +Fairing the foul with art's false borrowed face, +Sweet beauty hath no name no holy bower, +But is profaned, if not lives in disgrace. +Therefore my mistress' eyes are raven black, +Her eyes so suited, and they mourners seem, +At such who not born fair no beauty lack, +Slandering creation with a false esteem, +Yet so they mourn becoming of their woe, +That every tongue says beauty should look so. + + + +How oft when thou, my music, music play'st, +Upon that blessed wood whose motion sounds +With thy sweet fingers when thou gently sway'st +The wiry concord that mine ear confounds, +Do I envy those jacks that nimble leap, +To kiss the tender inward of thy hand, +Whilst my poor lips which should that harvest reap, +At the wood's boldness by thee blushing stand. +To be so tickled they would change their state +And situation with those dancing chips, +O'er whom thy fingers walk with gentle gait, +Making dead wood more blest than living lips, +Since saucy jacks so happy are in this, +Give them thy fingers, me thy lips to kiss. + + + +Th' expense of spirit in a waste of shame +Is lust in action, and till action, lust +Is perjured, murd'rous, bloody full of blame, +Savage, extreme, rude, cruel, not to trust, +Enjoyed no sooner but despised straight, +Past reason hunted, and no sooner had +Past reason hated as a swallowed bait, +On purpose laid to make the taker mad. +Mad in pursuit and in possession so, +Had, having, and in quest, to have extreme, +A bliss in proof and proved, a very woe, +Before a joy proposed behind a dream. +All this the world well knows yet none knows well, +To shun the heaven that leads men to this hell. + + + +My mistress' eyes are nothing like the sun, +Coral is far more red, than her lips red, +If snow be white, why then her breasts are dun: +If hairs be wires, black wires grow on her head: +I have seen roses damasked, red and white, +But no such roses see I in her cheeks, +And in some perfumes is there more delight, +Than in the breath that from my mistress reeks. +I love to hear her speak, yet well I know, +That music hath a far more pleasing sound: +I grant I never saw a goddess go, +My mistress when she walks treads on the ground. +And yet by heaven I think my love as rare, +As any she belied with false compare. + + + +Thou art as tyrannous, so as thou art, +As those whose beauties proudly make them cruel; +For well thou know'st to my dear doting heart +Thou art the fairest and most precious jewel. +Yet in good faith some say that thee behold, +Thy face hath not the power to make love groan; +To say they err, I dare not be so bold, +Although I swear it to my self alone. +And to be sure that is not false I swear, +A thousand groans but thinking on thy face, +One on another's neck do witness bear +Thy black is fairest in my judgment's place. +In nothing art thou black save in thy deeds, +And thence this slander as I think proceeds. + + + +Thine eyes I love, and they as pitying me, +Knowing thy heart torment me with disdain, +Have put on black, and loving mourners be, +Looking with pretty ruth upon my pain. +And truly not the morning sun of heaven +Better becomes the grey cheeks of the east, +Nor that full star that ushers in the even +Doth half that glory to the sober west +As those two mourning eyes become thy face: +O let it then as well beseem thy heart +To mourn for me since mourning doth thee grace, +And suit thy pity like in every part. +Then will I swear beauty herself is black, +And all they foul that thy complexion lack. + + + +Beshrew that heart that makes my heart to groan +For that deep wound it gives my friend and me; +Is't not enough to torture me alone, +But slave to slavery my sweet'st friend must be? +Me from my self thy cruel eye hath taken, +And my next self thou harder hast engrossed, +Of him, my self, and thee I am forsaken, +A torment thrice three-fold thus to be crossed: +Prison my heart in thy steel bosom's ward, +But then my friend's heart let my poor heart bail, +Whoe'er keeps me, let my heart be his guard, +Thou canst not then use rigour in my gaol. +And yet thou wilt, for I being pent in thee, +Perforce am thine and all that is in me. + + + +So now I have confessed that he is thine, +And I my self am mortgaged to thy will, +My self I'll forfeit, so that other mine, +Thou wilt restore to be my comfort still: +But thou wilt not, nor he will not be free, +For thou art covetous, and he is kind, +He learned but surety-like to write for me, +Under that bond that him as fist doth bind. +The statute of thy beauty thou wilt take, +Thou usurer that put'st forth all to use, +And sue a friend, came debtor for my sake, +So him I lose through my unkind abuse. +Him have I lost, thou hast both him and me, +He pays the whole, and yet am I not free. + + + +Whoever hath her wish, thou hast thy will, +And 'Will' to boot, and 'Will' in over-plus, +More than enough am I that vex thee still, +To thy sweet will making addition thus. +Wilt thou whose will is large and spacious, +Not once vouchsafe to hide my will in thine? +Shall will in others seem right gracious, +And in my will no fair acceptance shine? +The sea all water, yet receives rain still, +And in abundance addeth to his store, +So thou being rich in will add to thy will +One will of mine to make thy large will more. +Let no unkind, no fair beseechers kill, +Think all but one, and me in that one 'Will.' + + + +If thy soul check thee that I come so near, +Swear to thy blind soul that I was thy 'Will', +And will thy soul knows is admitted there, +Thus far for love, my love-suit sweet fulfil. +'Will', will fulfil the treasure of thy love, +Ay, fill it full with wills, and my will one, +In things of great receipt with case we prove, +Among a number one is reckoned none. +Then in the number let me pass untold, +Though in thy store's account I one must be, +For nothing hold me, so it please thee hold, +That nothing me, a something sweet to thee. +Make but my name thy love, and love that still, +And then thou lov'st me for my name is Will. + + + +Thou blind fool Love, what dost thou to mine eyes, +That they behold and see not what they see? +They know what beauty is, see where it lies, +Yet what the best is, take the worst to be. +If eyes corrupt by over-partial looks, +Be anchored in the bay where all men ride, +Why of eyes' falsehood hast thou forged hooks, +Whereto the judgment of my heart is tied? +Why should my heart think that a several plot, +Which my heart knows the wide world's common place? +Or mine eyes seeing this, say this is not +To put fair truth upon so foul a face? +In things right true my heart and eyes have erred, +And to this false plague are they now transferred. + + + +When my love swears that she is made of truth, +I do believe her though I know she lies, +That she might think me some untutored youth, +Unlearned in the world's false subtleties. +Thus vainly thinking that she thinks me young, +Although she knows my days are past the best, +Simply I credit her false-speaking tongue, +On both sides thus is simple truth suppressed: +But wherefore says she not she is unjust? +And wherefore say not I that I am old? +O love's best habit is in seeming trust, +And age in love, loves not to have years told. +Therefore I lie with her, and she with me, +And in our faults by lies we flattered be. + + + +O call not me to justify the wrong, +That thy unkindness lays upon my heart, +Wound me not with thine eye but with thy tongue, +Use power with power, and slay me not by art, +Tell me thou lov'st elsewhere; but in my sight, +Dear heart forbear to glance thine eye aside, +What need'st thou wound with cunning when thy might +Is more than my o'erpressed defence can bide? +Let me excuse thee, ah my love well knows, +Her pretty looks have been mine enemies, +And therefore from my face she turns my foes, +That they elsewhere might dart their injuries: +Yet do not so, but since I am near slain, +Kill me outright with looks, and rid my pain. + + + +Be wise as thou art cruel, do not press +My tongue-tied patience with too much disdain: +Lest sorrow lend me words and words express, +The manner of my pity-wanting pain. +If I might teach thee wit better it were, +Though not to love, yet love to tell me so, +As testy sick men when their deaths be near, +No news but health from their physicians know. +For if I should despair I should grow mad, +And in my madness might speak ill of thee, +Now this ill-wresting world is grown so bad, +Mad slanderers by mad ears believed be. +That I may not be so, nor thou belied, +Bear thine eyes straight, though thy proud heart go wide. + + + +In faith I do not love thee with mine eyes, +For they in thee a thousand errors note, +But 'tis my heart that loves what they despise, +Who in despite of view is pleased to dote. +Nor are mine cars with thy tongue's tune delighted, +Nor tender feeling to base touches prone, +Nor taste, nor smell, desire to be invited +To any sensual feast with thee alone: +But my five wits, nor my five senses can +Dissuade one foolish heart from serving thee, +Who leaves unswayed the likeness of a man, +Thy proud heart's slave and vassal wretch to be: +Only my plague thus far I count my gain, +That she that makes me sin, awards me pain. + + + +Love is my sin, and thy dear virtue hate, +Hate of my sin, grounded on sinful loving, +O but with mine, compare thou thine own state, +And thou shalt find it merits not reproving, +Or if it do, not from those lips of thine, +That have profaned their scarlet ornaments, +And sealed false bonds of love as oft as mine, +Robbed others' beds' revenues of their rents. +Be it lawful I love thee as thou lov'st those, +Whom thine eyes woo as mine importune thee, +Root pity in thy heart that when it grows, +Thy pity may deserve to pitied be. +If thou dost seek to have what thou dost hide, +By self-example mayst thou be denied. + + + +Lo as a careful huswife runs to catch, +One of her feathered creatures broke away, +Sets down her babe and makes all swift dispatch +In pursuit of the thing she would have stay: +Whilst her neglected child holds her in chase, +Cries to catch her whose busy care is bent, +To follow that which flies before her face: +Not prizing her poor infant's discontent; +So run'st thou after that which flies from thee, +Whilst I thy babe chase thee afar behind, +But if thou catch thy hope turn back to me: +And play the mother's part, kiss me, be kind. +So will I pray that thou mayst have thy Will, +If thou turn back and my loud crying still. + + + +Two loves I have of comfort and despair, +Which like two spirits do suggest me still, +The better angel is a man right fair: +The worser spirit a woman coloured ill. +To win me soon to hell my female evil, +Tempteth my better angel from my side, +And would corrupt my saint to be a devil: +Wooing his purity with her foul pride. +And whether that my angel be turned fiend, +Suspect I may, yet not directly tell, +But being both from me both to each friend, +I guess one angel in another's hell. +Yet this shall I ne'er know but live in doubt, +Till my bad angel fire my good one out. + + + +Those lips that Love's own hand did make, +Breathed forth the sound that said 'I hate', +To me that languished for her sake: +But when she saw my woeful state, +Straight in her heart did mercy come, +Chiding that tongue that ever sweet, +Was used in giving gentle doom: +And taught it thus anew to greet: +'I hate' she altered with an end, +That followed it as gentle day, +Doth follow night who like a fiend +From heaven to hell is flown away. +'I hate', from hate away she threw, +And saved my life saying 'not you'. + +Poor soul the centre of my sinful earth, +My sinful earth these rebel powers array, +Why dost thou pine within and suffer dearth +Painting thy outward walls so costly gay? +Why so large cost having so short a lease, +Dost thou upon thy fading mansion spend? +Shall worms inheritors of this excess +Eat up thy charge? is this thy body's end? +Then soul live thou upon thy servant's loss, +And let that pine to aggravate thy store; +Buy terms divine in selling hours of dross; +Within be fed, without be rich no more, +So shall thou feed on death, that feeds on men, +And death once dead, there's no more dying then. + +My love is as a fever longing still, +For that which longer nurseth the disease, +Feeding on that which doth preserve the ill, +Th' uncertain sickly appetite to please: +My reason the physician to my love, +Angry that his prescriptions are not kept +Hath left me, and I desperate now approve, +Desire is death, which physic did except. +Past cure I am, now reason is past care, +And frantic-mad with evermore unrest, +My thoughts and my discourse as mad men's are, +At random from the truth vainly expressed. +For I have sworn thee fair, and thought thee bright, +Who art as black as hell, as dark as night. + +O me! what eyes hath love put in my head, +Which have no correspondence with true sight, +Or if they have, where is my judgment fled, +That censures falsely what they see aright? +If that be fair whereon my false eyes dote, +What means the world to say it is not so? +If it be not, then love doth well denote, +Love's eye is not so true as all men's: no, +How can it? O how can love's eye be true, +That is so vexed with watching and with tears? +No marvel then though I mistake my view, +The sun it self sees not, till heaven clears. +O cunning love, with tears thou keep'st me blind, +Lest eyes well-seeing thy foul faults should find. + +Canst thou O cruel, say I love thee not, +When I against my self with thee partake? +Do I not think on thee when I forgot +Am of my self, all-tyrant, for thy sake? +Who hateth thee that I do call my friend, +On whom frown'st thou that I do fawn upon, +Nay if thou lour'st on me do I not spend +Revenge upon my self with present moan? +What merit do I in my self respect, +That is so proud thy service to despise, +When all my best doth worship thy defect, +Commanded by the motion of thine eyes? +But love hate on for now I know thy mind, +Those that can see thou lov'st, and I am blind. + +O from what power hast thou this powerful might, +With insufficiency my heart to sway, +To make me give the lie to my true sight, +And swear that brightness doth not grace the day? +Whence hast thou this becoming of things ill, +That in the very refuse of thy deeds, +There is such strength and warrantise of skill, +That in my mind thy worst all best exceeds? +Who taught thee how to make me love thee more, +The more I hear and see just cause of hate? +O though I love what others do abhor, +With others thou shouldst not abhor my state. +If thy unworthiness raised love in me, +More worthy I to be beloved of thee. + +Love is too young to know what conscience is, +Yet who knows not conscience is born of love? +Then gentle cheater urge not my amiss, +Lest guilty of my faults thy sweet self prove. +For thou betraying me, I do betray +My nobler part to my gross body's treason, +My soul doth tell my body that he may, +Triumph in love, flesh stays no farther reason, +But rising at thy name doth point out thee, +As his triumphant prize, proud of this pride, +He is contented thy poor drudge to be, +To stand in thy affairs, fall by thy side. +No want of conscience hold it that I call, +Her love, for whose dear love I rise and fall. + +In loving thee thou know'st I am forsworn, +But thou art twice forsworn to me love swearing, +In act thy bed-vow broke and new faith torn, +In vowing new hate after new love bearing: +But why of two oaths' breach do I accuse thee, +When I break twenty? I am perjured most, +For all my vows are oaths but to misuse thee: +And all my honest faith in thee is lost. +For I have sworn deep oaths of thy deep kindness: +Oaths of thy love, thy truth, thy constancy, +And to enlighten thee gave eyes to blindness, +Or made them swear against the thing they see. +For I have sworn thee fair: more perjured I, +To swear against the truth so foul a be. + +Cupid laid by his brand and fell asleep, +A maid of Dian's this advantage found, +And his love-kindling fire did quickly steep +In a cold valley-fountain of that ground: +Which borrowed from this holy fire of Love, +A dateless lively heat still to endure, +And grew a seeting bath which yet men prove, +Against strange maladies a sovereign cure: +But at my mistress' eye Love's brand new-fired, +The boy for trial needs would touch my breast, +I sick withal the help of bath desired, +And thither hied a sad distempered guest. +But found no cure, the bath for my help lies, +Where Cupid got new fire; my mistress' eyes. + +The little Love-god lying once asleep, +Laid by his side his heart-inflaming brand, +Whilst many nymphs that vowed chaste life to keep, +Came tripping by, but in her maiden hand, +The fairest votary took up that fire, +Which many legions of true hearts had warmed, +And so the general of hot desire, +Was sleeping by a virgin hand disarmed. +This brand she quenched in a cool well by, +Which from Love's fire took heat perpetual, +Growing a bath and healthful remedy, +For men discased, but I my mistress' thrall, +Came there for cure and this by that I prove, +Love's fire heats water, water cools not love. + + + THE END \ No newline at end of file From 013b653fa11736903d2be0df64d11f9b61a3ca5b Mon Sep 17 00:00:00 2001 From: jazelly Date: Sun, 5 May 2024 18:29:25 +0930 Subject: [PATCH 08/96] chore: update README --- README.md | 57 ++++++++++++++++++++++++--------------------------- mac/README.md | 12 +++++++++++ 2 files changed, 39 insertions(+), 30 deletions(-) create mode 100644 mac/README.md diff --git a/README.md b/README.md index 7045ca3..c8dd57c 100644 --- a/README.md +++ b/README.md @@ -5,51 +5,48 @@ This repo aims to provide the finest collection of all tuning scripts that can b Every training script in this repo is tested across multiple platforms. -## Install dependencies +## General Setup -### Install pytorch +- Install pytorch -The easist way to do this is via conda. If you don't have conda, please go to [the installation guide](https://conda.io/projects/conda/en/latest/user-guide/install/index.html) + The easist way to do this is via conda. If you don't have conda, please go to [the installation guide](https://conda.io/projects/conda/en/latest/user-guide/install/index.html) -``` -conda install pytorch torchvision torchaudio pytorch-cuda=11.7 -c pytorch -c nvidia -``` + ``` + conda install pytorch torchvision torchaudio pytorch-cuda=11.7 -c pytorch -c nvidia + ``` -If you don't want to use conda, I recommend virtual env for different LLMs, as they have different requirements + If you don't want to use conda, I recommend virtual env for different LLMs, as they have different requirements -#### For Linux +- For Linux -Install CUDA from [Nvidia installation guide](https://docs.nvidia.com/cuda/cuda-installation-guide-linux/) + Install CUDA from [Nvidia installation guide](https://docs.nvidia.com/cuda/cuda-installation-guide-linux/) -``` -cd llama2 -python3 -m venv .llama2 -source ./.llama2/bin/activate -pip3 install torch -pip3 install -r requirements.txt -``` + ``` + cd llama2 + python3 -m venv .llama2 + source ./.llama2/bin/activate + pip3 install torch + pip3 install -r requirements.txt + ``` -#### For Windows +- For Windows (with Nvidia GPU) -Enable WSL2 on your machine. + Enable WSL2 on your machine. -Install CUDA inside WSL by following the Linux guide. + Install CUDA from [Nvidia installation guide](https://docs.nvidia.com/cuda/cuda-installation-guide-linux/) -#### For Mac +- For Mac -Incoming, with mlx + Refer to [mac/README.md](./mac/README.md) - -## Usage - -LLM scripts are categorized by their names. Under each, you will see `notebook/`, for `jupyter notebook`, and `script/`, for `python` scripts. They should share same dependencies. -The training dataset or logic, however, might not be the same, as the purpose of this repo is to share various different examples of finetuning scripts so you can grasp the ideas. +Please note, there might be other dependencies for different model training techniques. Please refer to specific `README` under those model directories. ## TODO -- [ ] Try training at GGML and GGUF level -- [ ] Explore OLLAMA -- [ ] Explore mlx examples -- [ ] Explore Finetuning Model in LangChain with OLLAMA \ No newline at end of file +- [x] Support training at GGUF level +- [x] Explore `ollama` and `llama.cpp` +- [ ] Explore `mlx-examples` +- [ ] Support other models than LLAMA +- [ ] Explore `pykan` diff --git a/mac/README.md b/mac/README.md new file mode 100644 index 0000000..99110df --- /dev/null +++ b/mac/README.md @@ -0,0 +1,12 @@ +## Finetune LLM on MacOS + +Currently there are 2 ways supported. + +1. in slowllama - under this dir +2. in llama.cpp - refer to [llama-gguf/README.md](../llama-gguf/README.md) + +Both only support LLAMA based models. + +## Slowllama + +Slowllama is a python project purely focusing on finetuning LLAMA model on MacBook. It offloads weights to SSD to support training of large-sized model, i.e. with 70B. From c0bfdf0464107a42fc3a5bcc6d9eda947593f0d3 Mon Sep 17 00:00:00 2001 From: jazelly Date: Sun, 5 May 2024 18:46:52 +0930 Subject: [PATCH 09/96] chore: remove train text --- llama-gguf/shakespeare.txt | 2469 ------------------------------------ 1 file changed, 2469 deletions(-) delete mode 100644 llama-gguf/shakespeare.txt diff --git a/llama-gguf/shakespeare.txt b/llama-gguf/shakespeare.txt deleted file mode 100644 index dce66b2..0000000 --- a/llama-gguf/shakespeare.txt +++ /dev/null @@ -1,2469 +0,0 @@ -THE SONNETS - -by William Shakespeare - -From fairest creatures we desire increase, -That thereby beauty's rose might never die, -But as the riper should by time decease, -His tender heir might bear his memory: -But thou contracted to thine own bright eyes, -Feed'st thy light's flame with self-substantial fuel, -Making a famine where abundance lies, -Thy self thy foe, to thy sweet self too cruel: -Thou that art now the world's fresh ornament, -And only herald to the gaudy spring, -Within thine own bud buriest thy content, -And tender churl mak'st waste in niggarding: -Pity the world, or else this glutton be, -To eat the world's due, by the grave and thee. - -When forty winters shall besiege thy brow, -And dig deep trenches in thy beauty's field, -Thy youth's proud livery so gazed on now, -Will be a tattered weed of small worth held: -Then being asked, where all thy beauty lies, -Where all the treasure of thy lusty days; -To say within thine own deep sunken eyes, -Were an all-eating shame, and thriftless praise. -How much more praise deserved thy beauty's use, -If thou couldst answer 'This fair child of mine -Shall sum my count, and make my old excuse' -Proving his beauty by succession thine. -This were to be new made when thou art old, -And see thy blood warm when thou feel'st it cold. - -Look in thy glass and tell the face thou viewest, -Now is the time that face should form another, -Whose fresh repair if now thou not renewest, -Thou dost beguile the world, unbless some mother. -For where is she so fair whose uneared womb -Disdains the tillage of thy husbandry? -Or who is he so fond will be the tomb, -Of his self-love to stop posterity? -Thou art thy mother's glass and she in thee -Calls back the lovely April of her prime, -So thou through windows of thine age shalt see, -Despite of wrinkles this thy golden time. -But if thou live remembered not to be, -Die single and thine image dies with thee. - -Unthrifty loveliness why dost thou spend, -Upon thy self thy beauty's legacy? -Nature's bequest gives nothing but doth lend, -And being frank she lends to those are free: -Then beauteous niggard why dost thou abuse, -The bounteous largess given thee to give? -Profitless usurer why dost thou use -So great a sum of sums yet canst not live? -For having traffic with thy self alone, -Thou of thy self thy sweet self dost deceive, -Then how when nature calls thee to be gone, -What acceptable audit canst thou leave? -Thy unused beauty must be tombed with thee, -Which used lives th' executor to be. - -Those hours that with gentle work did frame -The lovely gaze where every eye doth dwell -Will play the tyrants to the very same, -And that unfair which fairly doth excel: -For never-resting time leads summer on -To hideous winter and confounds him there, -Sap checked with frost and lusty leaves quite gone, -Beauty o'er-snowed and bareness every where: -Then were not summer's distillation left -A liquid prisoner pent in walls of glass, -Beauty's effect with beauty were bereft, -Nor it nor no remembrance what it was. -But flowers distilled though they with winter meet, -Leese but their show, their substance still lives sweet. - -Then let not winter's ragged hand deface, -In thee thy summer ere thou be distilled: -Make sweet some vial; treasure thou some place, -With beauty's treasure ere it be self-killed: -That use is not forbidden usury, -Which happies those that pay the willing loan; -That's for thy self to breed another thee, -Or ten times happier be it ten for one, -Ten times thy self were happier than thou art, -If ten of thine ten times refigured thee: -Then what could death do if thou shouldst depart, -Leaving thee living in posterity? -Be not self-willed for thou art much too fair, -To be death's conquest and make worms thine heir. - -Lo in the orient when the gracious light -Lifts up his burning head, each under eye -Doth homage to his new-appearing sight, -Serving with looks his sacred majesty, -And having climbed the steep-up heavenly hill, -Resembling strong youth in his middle age, -Yet mortal looks adore his beauty still, -Attending on his golden pilgrimage: -But when from highmost pitch with weary car, -Like feeble age he reeleth from the day, -The eyes (fore duteous) now converted are -From his low tract and look another way: -So thou, thy self out-going in thy noon: -Unlooked on diest unless thou get a son. - -Music to hear, why hear'st thou music sadly? -Sweets with sweets war not, joy delights in joy: -Why lov'st thou that which thou receiv'st not gladly, -Or else receiv'st with pleasure thine annoy? -If the true concord of well-tuned sounds, -By unions married do offend thine ear, -They do but sweetly chide thee, who confounds -In singleness the parts that thou shouldst bear: -Mark how one string sweet husband to another, -Strikes each in each by mutual ordering; -Resembling sire, and child, and happy mother, -Who all in one, one pleasing note do sing: -Whose speechless song being many, seeming one, -Sings this to thee, 'Thou single wilt prove none'. - -Is it for fear to wet a widow's eye, -That thou consum'st thy self in single life? -Ah, if thou issueless shalt hap to die, -The world will wail thee like a makeless wife, -The world will be thy widow and still weep, -That thou no form of thee hast left behind, -When every private widow well may keep, -By children's eyes, her husband's shape in mind: -Look what an unthrift in the world doth spend -Shifts but his place, for still the world enjoys it; -But beauty's waste hath in the world an end, -And kept unused the user so destroys it: -No love toward others in that bosom sits -That on himself such murd'rous shame commits. - -For shame deny that thou bear'st love to any -Who for thy self art so unprovident. -Grant if thou wilt, thou art beloved of many, -But that thou none lov'st is most evident: -For thou art so possessed with murd'rous hate, -That 'gainst thy self thou stick'st not to conspire, -Seeking that beauteous roof to ruinate -Which to repair should be thy chief desire: -O change thy thought, that I may change my mind, -Shall hate be fairer lodged than gentle love? -Be as thy presence is gracious and kind, -Or to thy self at least kind-hearted prove, -Make thee another self for love of me, -That beauty still may live in thine or thee. - -As fast as thou shalt wane so fast thou grow'st, -In one of thine, from that which thou departest, -And that fresh blood which youngly thou bestow'st, -Thou mayst call thine, when thou from youth convertest, -Herein lives wisdom, beauty, and increase, -Without this folly, age, and cold decay, -If all were minded so, the times should cease, -And threescore year would make the world away: -Let those whom nature hath not made for store, -Harsh, featureless, and rude, barrenly perish: -Look whom she best endowed, she gave thee more; -Which bounteous gift thou shouldst in bounty cherish: -She carved thee for her seal, and meant thereby, -Thou shouldst print more, not let that copy die. - -When I do count the clock that tells the time, -And see the brave day sunk in hideous night, -When I behold the violet past prime, -And sable curls all silvered o'er with white: -When lofty trees I see barren of leaves, -Which erst from heat did canopy the herd -And summer's green all girded up in sheaves -Borne on the bier with white and bristly beard: -Then of thy beauty do I question make -That thou among the wastes of time must go, -Since sweets and beauties do themselves forsake, -And die as fast as they see others grow, -And nothing 'gainst Time's scythe can make defence -Save breed to brave him, when he takes thee hence. - -O that you were your self, but love you are -No longer yours, than you your self here live, -Against this coming end you should prepare, -And your sweet semblance to some other give. -So should that beauty which you hold in lease -Find no determination, then you were -Your self again after your self's decease, -When your sweet issue your sweet form should bear. -Who lets so fair a house fall to decay, -Which husbandry in honour might uphold, -Against the stormy gusts of winter's day -And barren rage of death's eternal cold? -O none but unthrifts, dear my love you know, -You had a father, let your son say so. - -Not from the stars do I my judgement pluck, -And yet methinks I have astronomy, -But not to tell of good, or evil luck, -Of plagues, of dearths, or seasons' quality, -Nor can I fortune to brief minutes tell; -Pointing to each his thunder, rain and wind, -Or say with princes if it shall go well -By oft predict that I in heaven find. -But from thine eyes my knowledge I derive, -And constant stars in them I read such art -As truth and beauty shall together thrive -If from thy self, to store thou wouldst convert: -Or else of thee this I prognosticate, -Thy end is truth's and beauty's doom and date. - -When I consider every thing that grows -Holds in perfection but a little moment. -That this huge stage presenteth nought but shows -Whereon the stars in secret influence comment. -When I perceive that men as plants increase, -Cheered and checked even by the self-same sky: -Vaunt in their youthful sap, at height decrease, -And wear their brave state out of memory. -Then the conceit of this inconstant stay, -Sets you most rich in youth before my sight, -Where wasteful time debateth with decay -To change your day of youth to sullied night, -And all in war with Time for love of you, -As he takes from you, I engraft you new. - -But wherefore do not you a mightier way -Make war upon this bloody tyrant Time? -And fortify your self in your decay -With means more blessed than my barren rhyme? -Now stand you on the top of happy hours, -And many maiden gardens yet unset, -With virtuous wish would bear you living flowers, -Much liker than your painted counterfeit: -So should the lines of life that life repair -Which this (Time's pencil) or my pupil pen -Neither in inward worth nor outward fair -Can make you live your self in eyes of men. -To give away your self, keeps your self still, -And you must live drawn by your own sweet skill. - -Who will believe my verse in time to come -If it were filled with your most high deserts? -Though yet heaven knows it is but as a tomb -Which hides your life, and shows not half your parts: -If I could write the beauty of your eyes, -And in fresh numbers number all your graces, -The age to come would say this poet lies, -Such heavenly touches ne'er touched earthly faces. -So should my papers (yellowed with their age) -Be scorned, like old men of less truth than tongue, -And your true rights be termed a poet's rage, -And stretched metre of an antique song. -But were some child of yours alive that time, -You should live twice in it, and in my rhyme. - -Shall I compare thee to a summer's day? -Thou art more lovely and more temperate: -Rough winds do shake the darling buds of May, -And summer's lease hath all too short a date: -Sometime too hot the eye of heaven shines, -And often is his gold complexion dimmed, -And every fair from fair sometime declines, -By chance, or nature's changing course untrimmed: -But thy eternal summer shall not fade, -Nor lose possession of that fair thou ow'st, -Nor shall death brag thou wand'rest in his shade, -When in eternal lines to time thou grow'st, -So long as men can breathe or eyes can see, -So long lives this, and this gives life to thee. - -Devouring Time blunt thou the lion's paws, -And make the earth devour her own sweet brood, -Pluck the keen teeth from the fierce tiger's jaws, -And burn the long-lived phoenix, in her blood, -Make glad and sorry seasons as thou fleet'st, -And do whate'er thou wilt swift-footed Time -To the wide world and all her fading sweets: -But I forbid thee one most heinous crime, -O carve not with thy hours my love's fair brow, -Nor draw no lines there with thine antique pen, -Him in thy course untainted do allow, -For beauty's pattern to succeeding men. -Yet do thy worst old Time: despite thy wrong, -My love shall in my verse ever live young. - -A woman's face with nature's own hand painted, -Hast thou the master mistress of my passion, -A woman's gentle heart but not acquainted -With shifting change as is false women's fashion, -An eye more bright than theirs, less false in rolling: -Gilding the object whereupon it gazeth, -A man in hue all hues in his controlling, -Which steals men's eyes and women's souls amazeth. -And for a woman wert thou first created, -Till nature as she wrought thee fell a-doting, -And by addition me of thee defeated, -By adding one thing to my purpose nothing. -But since she pricked thee out for women's pleasure, -Mine be thy love and thy love's use their treasure. - -So is it not with me as with that muse, -Stirred by a painted beauty to his verse, -Who heaven it self for ornament doth use, -And every fair with his fair doth rehearse, -Making a couplement of proud compare -With sun and moon, with earth and sea's rich gems: -With April's first-born flowers and all things rare, -That heaven's air in this huge rondure hems. -O let me true in love but truly write, -And then believe me, my love is as fair, -As any mother's child, though not so bright -As those gold candles fixed in heaven's air: -Let them say more that like of hearsay well, -I will not praise that purpose not to sell. - -My glass shall not persuade me I am old, -So long as youth and thou are of one date, -But when in thee time's furrows I behold, -Then look I death my days should expiate. -For all that beauty that doth cover thee, -Is but the seemly raiment of my heart, -Which in thy breast doth live, as thine in me, -How can I then be elder than thou art? -O therefore love be of thyself so wary, -As I not for my self, but for thee will, -Bearing thy heart which I will keep so chary -As tender nurse her babe from faring ill. -Presume not on thy heart when mine is slain, -Thou gav'st me thine not to give back again. - -As an unperfect actor on the stage, -Who with his fear is put beside his part, -Or some fierce thing replete with too much rage, -Whose strength's abundance weakens his own heart; -So I for fear of trust, forget to say, -The perfect ceremony of love's rite, -And in mine own love's strength seem to decay, -O'ercharged with burthen of mine own love's might: -O let my looks be then the eloquence, -And dumb presagers of my speaking breast, -Who plead for love, and look for recompense, -More than that tongue that more hath more expressed. -O learn to read what silent love hath writ, -To hear with eyes belongs to love's fine wit. - -Mine eye hath played the painter and hath stelled, -Thy beauty's form in table of my heart, -My body is the frame wherein 'tis held, -And perspective it is best painter's art. -For through the painter must you see his skill, -To find where your true image pictured lies, -Which in my bosom's shop is hanging still, -That hath his windows glazed with thine eyes: -Now see what good turns eyes for eyes have done, -Mine eyes have drawn thy shape, and thine for me -Are windows to my breast, where-through the sun -Delights to peep, to gaze therein on thee; -Yet eyes this cunning want to grace their art, -They draw but what they see, know not the heart. - -Let those who are in favour with their stars, -Of public honour and proud titles boast, -Whilst I whom fortune of such triumph bars -Unlooked for joy in that I honour most; -Great princes' favourites their fair leaves spread, -But as the marigold at the sun's eye, -And in themselves their pride lies buried, -For at a frown they in their glory die. -The painful warrior famoused for fight, -After a thousand victories once foiled, -Is from the book of honour razed quite, -And all the rest forgot for which he toiled: -Then happy I that love and am beloved -Where I may not remove nor be removed. - -Lord of my love, to whom in vassalage -Thy merit hath my duty strongly knit; -To thee I send this written embassage -To witness duty, not to show my wit. -Duty so great, which wit so poor as mine -May make seem bare, in wanting words to show it; -But that I hope some good conceit of thine -In thy soul's thought (all naked) will bestow it: -Till whatsoever star that guides my moving, -Points on me graciously with fair aspect, -And puts apparel on my tattered loving, -To show me worthy of thy sweet respect, -Then may I dare to boast how I do love thee, -Till then, not show my head where thou mayst prove me. - -Weary with toil, I haste me to my bed, -The dear respose for limbs with travel tired, -But then begins a journey in my head -To work my mind, when body's work's expired. -For then my thoughts (from far where I abide) -Intend a zealous pilgrimage to thee, -And keep my drooping eyelids open wide, -Looking on darkness which the blind do see. -Save that my soul's imaginary sight -Presents thy shadow to my sightless view, -Which like a jewel (hung in ghastly night) -Makes black night beauteous, and her old face new. -Lo thus by day my limbs, by night my mind, -For thee, and for my self, no quiet find. - -How can I then return in happy plight -That am debarred the benefit of rest? -When day's oppression is not eased by night, -But day by night and night by day oppressed. -And each (though enemies to either's reign) -Do in consent shake hands to torture me, -The one by toil, the other to complain -How far I toil, still farther off from thee. -I tell the day to please him thou art bright, -And dost him grace when clouds do blot the heaven: -So flatter I the swart-complexioned night, -When sparkling stars twire not thou gild'st the even. -But day doth daily draw my sorrows longer, -And night doth nightly make grief's length seem stronger - -When in disgrace with Fortune and men's eyes, -I all alone beweep my outcast state, -And trouble deaf heaven with my bootless cries, -And look upon my self and curse my fate, -Wishing me like to one more rich in hope, -Featured like him, like him with friends possessed, -Desiring this man's art, and that man's scope, -With what I most enjoy contented least, -Yet in these thoughts my self almost despising, -Haply I think on thee, and then my state, -(Like to the lark at break of day arising -From sullen earth) sings hymns at heaven's gate, -For thy sweet love remembered such wealth brings, -That then I scorn to change my state with kings. - -When to the sessions of sweet silent thought, -I summon up remembrance of things past, -I sigh the lack of many a thing I sought, -And with old woes new wail my dear time's waste: -Then can I drown an eye (unused to flow) -For precious friends hid in death's dateless night, -And weep afresh love's long since cancelled woe, -And moan th' expense of many a vanished sight. -Then can I grieve at grievances foregone, -And heavily from woe to woe tell o'er -The sad account of fore-bemoaned moan, -Which I new pay as if not paid before. -But if the while I think on thee (dear friend) -All losses are restored, and sorrows end. - -Thy bosom is endeared with all hearts, -Which I by lacking have supposed dead, -And there reigns love and all love's loving parts, -And all those friends which I thought buried. -How many a holy and obsequious tear -Hath dear religious love stol'n from mine eye, -As interest of the dead, which now appear, -But things removed that hidden in thee lie. -Thou art the grave where buried love doth live, -Hung with the trophies of my lovers gone, -Who all their parts of me to thee did give, -That due of many, now is thine alone. -Their images I loved, I view in thee, -And thou (all they) hast all the all of me. - -If thou survive my well-contented day, -When that churl death my bones with dust shall cover -And shalt by fortune once more re-survey -These poor rude lines of thy deceased lover: -Compare them with the bett'ring of the time, -And though they be outstripped by every pen, -Reserve them for my love, not for their rhyme, -Exceeded by the height of happier men. -O then vouchsafe me but this loving thought, -'Had my friend's Muse grown with this growing age, -A dearer birth than this his love had brought -To march in ranks of better equipage: -But since he died and poets better prove, -Theirs for their style I'll read, his for his love'. - -Full many a glorious morning have I seen, -Flatter the mountain tops with sovereign eye, -Kissing with golden face the meadows green; -Gilding pale streams with heavenly alchemy: -Anon permit the basest clouds to ride, -With ugly rack on his celestial face, -And from the forlorn world his visage hide -Stealing unseen to west with this disgrace: -Even so my sun one early morn did shine, -With all triumphant splendour on my brow, -But out alack, he was but one hour mine, -The region cloud hath masked him from me now. -Yet him for this, my love no whit disdaineth, -Suns of the world may stain, when heaven's sun staineth. - -Why didst thou promise such a beauteous day, -And make me travel forth without my cloak, -To let base clouds o'ertake me in my way, -Hiding thy brav'ry in their rotten smoke? -'Tis not enough that through the cloud thou break, -To dry the rain on my storm-beaten face, -For no man well of such a salve can speak, -That heals the wound, and cures not the disgrace: -Nor can thy shame give physic to my grief, -Though thou repent, yet I have still the loss, -Th' offender's sorrow lends but weak relief -To him that bears the strong offence's cross. -Ah but those tears are pearl which thy love sheds, -And they are rich, and ransom all ill deeds. - - - -No more be grieved at that which thou hast done, -Roses have thorns, and silver fountains mud, -Clouds and eclipses stain both moon and sun, -And loathsome canker lives in sweetest bud. -All men make faults, and even I in this, -Authorizing thy trespass with compare, -My self corrupting salving thy amiss, -Excusing thy sins more than thy sins are: -For to thy sensual fault I bring in sense, -Thy adverse party is thy advocate, -And 'gainst my self a lawful plea commence: -Such civil war is in my love and hate, -That I an accessary needs must be, -To that sweet thief which sourly robs from me. - -Let me confess that we two must be twain, -Although our undivided loves are one: -So shall those blots that do with me remain, -Without thy help, by me be borne alone. -In our two loves there is but one respect, -Though in our lives a separable spite, -Which though it alter not love's sole effect, -Yet doth it steal sweet hours from love's delight. -I may not evermore acknowledge thee, -Lest my bewailed guilt should do thee shame, -Nor thou with public kindness honour me, -Unless thou take that honour from thy name: -But do not so, I love thee in such sort, -As thou being mine, mine is thy good report. - -As a decrepit father takes delight, -To see his active child do deeds of youth, -So I, made lame by Fortune's dearest spite -Take all my comfort of thy worth and truth. -For whether beauty, birth, or wealth, or wit, -Or any of these all, or all, or more -Entitled in thy parts, do crowned sit, -I make my love engrafted to this store: -So then I am not lame, poor, nor despised, -Whilst that this shadow doth such substance give, -That I in thy abundance am sufficed, -And by a part of all thy glory live: -Look what is best, that best I wish in thee, -This wish I have, then ten times happy me. - -How can my muse want subject to invent -While thou dost breathe that pour'st into my verse, -Thine own sweet argument, too excellent, -For every vulgar paper to rehearse? -O give thy self the thanks if aught in me, -Worthy perusal stand against thy sight, -For who's so dumb that cannot write to thee, -When thou thy self dost give invention light? -Be thou the tenth Muse, ten times more in worth -Than those old nine which rhymers invocate, -And he that calls on thee, let him bring forth -Eternal numbers to outlive long date. -If my slight muse do please these curious days, -The pain be mine, but thine shall be the praise. - -O how thy worth with manners may I sing, -When thou art all the better part of me? -What can mine own praise to mine own self bring: -And what is't but mine own when I praise thee? -Even for this, let us divided live, -And our dear love lose name of single one, -That by this separation I may give: -That due to thee which thou deserv'st alone: -O absence what a torment wouldst thou prove, -Were it not thy sour leisure gave sweet leave, -To entertain the time with thoughts of love, -Which time and thoughts so sweetly doth deceive. -And that thou teachest how to make one twain, -By praising him here who doth hence remain. - -Take all my loves, my love, yea take them all, -What hast thou then more than thou hadst before? -No love, my love, that thou mayst true love call, -All mine was thine, before thou hadst this more: -Then if for my love, thou my love receivest, -I cannot blame thee, for my love thou usest, -But yet be blamed, if thou thy self deceivest -By wilful taste of what thy self refusest. -I do forgive thy robbery gentle thief -Although thou steal thee all my poverty: -And yet love knows it is a greater grief -To bear greater wrong, than hate's known injury. -Lascivious grace, in whom all ill well shows, -Kill me with spites yet we must not be foes. - -Those pretty wrongs that liberty commits, -When I am sometime absent from thy heart, -Thy beauty, and thy years full well befits, -For still temptation follows where thou art. -Gentle thou art, and therefore to be won, -Beauteous thou art, therefore to be assailed. -And when a woman woos, what woman's son, -Will sourly leave her till he have prevailed? -Ay me, but yet thou mightst my seat forbear, -And chide thy beauty, and thy straying youth, -Who lead thee in their riot even there -Where thou art forced to break a twofold truth: -Hers by thy beauty tempting her to thee, -Thine by thy beauty being false to me. - -That thou hast her it is not all my grief, -And yet it may be said I loved her dearly, -That she hath thee is of my wailing chief, -A loss in love that touches me more nearly. -Loving offenders thus I will excuse ye, -Thou dost love her, because thou know'st I love her, -And for my sake even so doth she abuse me, -Suff'ring my friend for my sake to approve her. -If I lose thee, my loss is my love's gain, -And losing her, my friend hath found that loss, -Both find each other, and I lose both twain, -And both for my sake lay on me this cross, -But here's the joy, my friend and I are one, -Sweet flattery, then she loves but me alone. - -When most I wink then do mine eyes best see, -For all the day they view things unrespected, -But when I sleep, in dreams they look on thee, -And darkly bright, are bright in dark directed. -Then thou whose shadow shadows doth make bright -How would thy shadow's form, form happy show, -To the clear day with thy much clearer light, -When to unseeing eyes thy shade shines so! -How would (I say) mine eyes be blessed made, -By looking on thee in the living day, -When in dead night thy fair imperfect shade, -Through heavy sleep on sightless eyes doth stay! -All days are nights to see till I see thee, -And nights bright days when dreams do show thee me. - -If the dull substance of my flesh were thought, -Injurious distance should not stop my way, -For then despite of space I would be brought, -From limits far remote, where thou dost stay, -No matter then although my foot did stand -Upon the farthest earth removed from thee, -For nimble thought can jump both sea and land, -As soon as think the place where he would be. -But ah, thought kills me that I am not thought -To leap large lengths of miles when thou art gone, -But that so much of earth and water wrought, -I must attend, time's leisure with my moan. -Receiving nought by elements so slow, -But heavy tears, badges of either's woe. - -The other two, slight air, and purging fire, -Are both with thee, wherever I abide, -The first my thought, the other my desire, -These present-absent with swift motion slide. -For when these quicker elements are gone -In tender embassy of love to thee, -My life being made of four, with two alone, -Sinks down to death, oppressed with melancholy. -Until life's composition be recured, -By those swift messengers returned from thee, -Who even but now come back again assured, -Of thy fair health, recounting it to me. -This told, I joy, but then no longer glad, -I send them back again and straight grow sad. - -Mine eye and heart are at a mortal war, -How to divide the conquest of thy sight, -Mine eye, my heart thy picture's sight would bar, -My heart, mine eye the freedom of that right, -My heart doth plead that thou in him dost lie, -(A closet never pierced with crystal eyes) -But the defendant doth that plea deny, -And says in him thy fair appearance lies. -To side this title is impanelled -A quest of thoughts, all tenants to the heart, -And by their verdict is determined -The clear eye's moiety, and the dear heart's part. -As thus, mine eye's due is thy outward part, -And my heart's right, thy inward love of heart. - -Betwixt mine eye and heart a league is took, -And each doth good turns now unto the other, -When that mine eye is famished for a look, -Or heart in love with sighs himself doth smother; -With my love's picture then my eye doth feast, -And to the painted banquet bids my heart: -Another time mine eye is my heart's guest, -And in his thoughts of love doth share a part. -So either by thy picture or my love, -Thy self away, art present still with me, -For thou not farther than my thoughts canst move, -And I am still with them, and they with thee. -Or if they sleep, thy picture in my sight -Awakes my heart, to heart's and eye's delight. - -How careful was I when I took my way, -Each trifle under truest bars to thrust, -That to my use it might unused stay -From hands of falsehood, in sure wards of trust! -But thou, to whom my jewels trifles are, -Most worthy comfort, now my greatest grief, -Thou best of dearest, and mine only care, -Art left the prey of every vulgar thief. -Thee have I not locked up in any chest, -Save where thou art not, though I feel thou art, -Within the gentle closure of my breast, -From whence at pleasure thou mayst come and part, -And even thence thou wilt be stol'n I fear, -For truth proves thievish for a prize so dear. - -Against that time (if ever that time come) -When I shall see thee frown on my defects, -When as thy love hath cast his utmost sum, -Called to that audit by advised respects, -Against that time when thou shalt strangely pass, -And scarcely greet me with that sun thine eye, -When love converted from the thing it was -Shall reasons find of settled gravity; -Against that time do I ensconce me here -Within the knowledge of mine own desert, -And this my hand, against my self uprear, -To guard the lawful reasons on thy part, -To leave poor me, thou hast the strength of laws, -Since why to love, I can allege no cause. - -How heavy do I journey on the way, -When what I seek (my weary travel's end) -Doth teach that case and that repose to say -'Thus far the miles are measured from thy friend.' -The beast that bears me, tired with my woe, -Plods dully on, to bear that weight in me, -As if by some instinct the wretch did know -His rider loved not speed being made from thee: -The bloody spur cannot provoke him on, -That sometimes anger thrusts into his hide, -Which heavily he answers with a groan, -More sharp to me than spurring to his side, -For that same groan doth put this in my mind, -My grief lies onward and my joy behind. - -Thus can my love excuse the slow offence, -Of my dull bearer, when from thee I speed, -From where thou art, why should I haste me thence? -Till I return of posting is no need. -O what excuse will my poor beast then find, -When swift extremity can seem but slow? -Then should I spur though mounted on the wind, -In winged speed no motion shall I know, -Then can no horse with my desire keep pace, -Therefore desire (of perfect'st love being made) -Shall neigh (no dull flesh) in his fiery race, -But love, for love, thus shall excuse my jade, -Since from thee going, he went wilful-slow, -Towards thee I'll run, and give him leave to go. - -So am I as the rich whose blessed key, -Can bring him to his sweet up-locked treasure, -The which he will not every hour survey, -For blunting the fine point of seldom pleasure. -Therefore are feasts so solemn and so rare, -Since seldom coming in that long year set, -Like stones of worth they thinly placed are, -Or captain jewels in the carcanet. -So is the time that keeps you as my chest -Or as the wardrobe which the robe doth hide, -To make some special instant special-blest, -By new unfolding his imprisoned pride. -Blessed are you whose worthiness gives scope, -Being had to triumph, being lacked to hope. - -What is your substance, whereof are you made, -That millions of strange shadows on you tend? -Since every one, hath every one, one shade, -And you but one, can every shadow lend: -Describe Adonis and the counterfeit, -Is poorly imitated after you, -On Helen's cheek all art of beauty set, -And you in Grecian tires are painted new: -Speak of the spring, and foison of the year, -The one doth shadow of your beauty show, -The other as your bounty doth appear, -And you in every blessed shape we know. -In all external grace you have some part, -But you like none, none you for constant heart. - -O how much more doth beauty beauteous seem, -By that sweet ornament which truth doth give! -The rose looks fair, but fairer we it deem -For that sweet odour, which doth in it live: -The canker blooms have full as deep a dye, -As the perfumed tincture of the roses, -Hang on such thorns, and play as wantonly, -When summer's breath their masked buds discloses: -But for their virtue only is their show, -They live unwooed, and unrespected fade, -Die to themselves. Sweet roses do not so, -Of their sweet deaths, are sweetest odours made: -And so of you, beauteous and lovely youth, -When that shall vade, by verse distills your truth. - -Not marble, nor the gilded monuments -Of princes shall outlive this powerful rhyme, -But you shall shine more bright in these contents -Than unswept stone, besmeared with sluttish time. -When wasteful war shall statues overturn, -And broils root out the work of masonry, -Nor Mars his sword, nor war's quick fire shall burn: -The living record of your memory. -'Gainst death, and all-oblivious enmity -Shall you pace forth, your praise shall still find room, -Even in the eyes of all posterity -That wear this world out to the ending doom. -So till the judgment that your self arise, -You live in this, and dwell in lovers' eyes. - -Sweet love renew thy force, be it not said -Thy edge should blunter be than appetite, -Which but to-day by feeding is allayed, -To-morrow sharpened in his former might. -So love be thou, although to-day thou fill -Thy hungry eyes, even till they wink with fulness, -To-morrow see again, and do not kill -The spirit of love, with a perpetual dulness: -Let this sad interim like the ocean be -Which parts the shore, where two contracted new, -Come daily to the banks, that when they see: -Return of love, more blest may be the view. -Or call it winter, which being full of care, -Makes summer's welcome, thrice more wished, more rare. - -Being your slave what should I do but tend, -Upon the hours, and times of your desire? -I have no precious time at all to spend; -Nor services to do till you require. -Nor dare I chide the world-without-end hour, -Whilst I (my sovereign) watch the clock for you, -Nor think the bitterness of absence sour, -When you have bid your servant once adieu. -Nor dare I question with my jealous thought, -Where you may be, or your affairs suppose, -But like a sad slave stay and think of nought -Save where you are, how happy you make those. -So true a fool is love, that in your will, -(Though you do any thing) he thinks no ill. - -That god forbid, that made me first your slave, -I should in thought control your times of pleasure, -Or at your hand th' account of hours to crave, -Being your vassal bound to stay your leisure. -O let me suffer (being at your beck) -Th' imprisoned absence of your liberty, -And patience tame to sufferance bide each check, -Without accusing you of injury. -Be where you list, your charter is so strong, -That you your self may privilage your time -To what you will, to you it doth belong, -Your self to pardon of self-doing crime. -I am to wait, though waiting so be hell, -Not blame your pleasure be it ill or well. - -If there be nothing new, but that which is, -Hath been before, how are our brains beguiled, -Which labouring for invention bear amis -The second burthen of a former child! -O that record could with a backward look, -Even of five hundred courses of the sun, -Show me your image in some antique book, -Since mind at first in character was done. -That I might see what the old world could say, -To this composed wonder of your frame, -Whether we are mended, or whether better they, -Or whether revolution be the same. -O sure I am the wits of former days, -To subjects worse have given admiring praise. - -Like as the waves make towards the pebbled shore, -So do our minutes hasten to their end, -Each changing place with that which goes before, -In sequent toil all forwards do contend. -Nativity once in the main of light, -Crawls to maturity, wherewith being crowned, -Crooked eclipses 'gainst his glory fight, -And Time that gave, doth now his gift confound. -Time doth transfix the flourish set on youth, -And delves the parallels in beauty's brow, -Feeds on the rarities of nature's truth, -And nothing stands but for his scythe to mow. -And yet to times in hope, my verse shall stand -Praising thy worth, despite his cruel hand. - -Is it thy will, thy image should keep open -My heavy eyelids to the weary night? -Dost thou desire my slumbers should be broken, -While shadows like to thee do mock my sight? -Is it thy spirit that thou send'st from thee -So far from home into my deeds to pry, -To find out shames and idle hours in me, -The scope and tenure of thy jealousy? -O no, thy love though much, is not so great, -It is my love that keeps mine eye awake, -Mine own true love that doth my rest defeat, -To play the watchman ever for thy sake. -For thee watch I, whilst thou dost wake elsewhere, -From me far off, with others all too near. - -Sin of self-love possesseth all mine eye, -And all my soul, and all my every part; -And for this sin there is no remedy, -It is so grounded inward in my heart. -Methinks no face so gracious is as mine, -No shape so true, no truth of such account, -And for my self mine own worth do define, -As I all other in all worths surmount. -But when my glass shows me my self indeed -beated and chopt with tanned antiquity, -Mine own self-love quite contrary I read: -Self, so self-loving were iniquity. -'Tis thee (my self) that for my self I praise, -Painting my age with beauty of thy days. - -Against my love shall be as I am now -With Time's injurious hand crushed and o'erworn, -When hours have drained his blood and filled his brow -With lines and wrinkles, when his youthful morn -Hath travelled on to age's steepy night, -And all those beauties whereof now he's king -Are vanishing, or vanished out of sight, -Stealing away the treasure of his spring: -For such a time do I now fortify -Against confounding age's cruel knife, -That he shall never cut from memory -My sweet love's beauty, though my lover's life. -His beauty shall in these black lines be seen, -And they shall live, and he in them still green. - -When I have seen by Time's fell hand defaced -The rich-proud cost of outworn buried age, -When sometime lofty towers I see down-rased, -And brass eternal slave to mortal rage. -When I have seen the hungry ocean gain -Advantage on the kingdom of the shore, -And the firm soil win of the watery main, -Increasing store with loss, and loss with store. -When I have seen such interchange of State, -Or state it self confounded, to decay, -Ruin hath taught me thus to ruminate -That Time will come and take my love away. -This thought is as a death which cannot choose -But weep to have, that which it fears to lose. - -Since brass, nor stone, nor earth, nor boundless sea, -But sad mortality o'ersways their power, -How with this rage shall beauty hold a plea, -Whose action is no stronger than a flower? -O how shall summer's honey breath hold out, -Against the wrackful siege of batt'ring days, -When rocks impregnable are not so stout, -Nor gates of steel so strong but time decays? -O fearful meditation, where alack, -Shall Time's best jewel from Time's chest lie hid? -Or what strong hand can hold his swift foot back, -Or who his spoil of beauty can forbid? -O none, unless this miracle have might, -That in black ink my love may still shine bright. - -Tired with all these for restful death I cry, -As to behold desert a beggar born, -And needy nothing trimmed in jollity, -And purest faith unhappily forsworn, -And gilded honour shamefully misplaced, -And maiden virtue rudely strumpeted, -And right perfection wrongfully disgraced, -And strength by limping sway disabled -And art made tongue-tied by authority, -And folly (doctor-like) controlling skill, -And simple truth miscalled simplicity, -And captive good attending captain ill. -Tired with all these, from these would I be gone, -Save that to die, I leave my love alone. - -Ah wherefore with infection should he live, -And with his presence grace impiety, -That sin by him advantage should achieve, -And lace it self with his society? -Why should false painting imitate his cheek, -And steal dead seeming of his living hue? -Why should poor beauty indirectly seek, -Roses of shadow, since his rose is true? -Why should he live, now nature bankrupt is, -Beggared of blood to blush through lively veins, -For she hath no exchequer now but his, -And proud of many, lives upon his gains? -O him she stores, to show what wealth she had, -In days long since, before these last so bad. - -Thus is his cheek the map of days outworn, -When beauty lived and died as flowers do now, -Before these bastard signs of fair were born, -Or durst inhabit on a living brow: -Before the golden tresses of the dead, -The right of sepulchres, were shorn away, -To live a second life on second head, -Ere beauty's dead fleece made another gay: -In him those holy antique hours are seen, -Without all ornament, it self and true, -Making no summer of another's green, -Robbing no old to dress his beauty new, -And him as for a map doth Nature store, -To show false Art what beauty was of yore. - -Those parts of thee that the world's eye doth view, -Want nothing that the thought of hearts can mend: -All tongues (the voice of souls) give thee that due, -Uttering bare truth, even so as foes commend. -Thy outward thus with outward praise is crowned, -But those same tongues that give thee so thine own, -In other accents do this praise confound -By seeing farther than the eye hath shown. -They look into the beauty of thy mind, -And that in guess they measure by thy deeds, -Then churls their thoughts (although their eyes were kind) -To thy fair flower add the rank smell of weeds: -But why thy odour matcheth not thy show, -The soil is this, that thou dost common grow. - - - -That thou art blamed shall not be thy defect, -For slander's mark was ever yet the fair, -The ornament of beauty is suspect, -A crow that flies in heaven's sweetest air. -So thou be good, slander doth but approve, -Thy worth the greater being wooed of time, -For canker vice the sweetest buds doth love, -And thou present'st a pure unstained prime. -Thou hast passed by the ambush of young days, -Either not assailed, or victor being charged, -Yet this thy praise cannot be so thy praise, -To tie up envy, evermore enlarged, -If some suspect of ill masked not thy show, -Then thou alone kingdoms of hearts shouldst owe. - - - -No longer mourn for me when I am dead, -Than you shall hear the surly sullen bell -Give warning to the world that I am fled -From this vile world with vilest worms to dwell: -Nay if you read this line, remember not, -The hand that writ it, for I love you so, -That I in your sweet thoughts would be forgot, -If thinking on me then should make you woe. -O if (I say) you look upon this verse, -When I (perhaps) compounded am with clay, -Do not so much as my poor name rehearse; -But let your love even with my life decay. -Lest the wise world should look into your moan, -And mock you with me after I am gone. - - - -O lest the world should task you to recite, -What merit lived in me that you should love -After my death (dear love) forget me quite, -For you in me can nothing worthy prove. -Unless you would devise some virtuous lie, -To do more for me than mine own desert, -And hang more praise upon deceased I, -Than niggard truth would willingly impart: -O lest your true love may seem false in this, -That you for love speak well of me untrue, -My name be buried where my body is, -And live no more to shame nor me, nor you. -For I am shamed by that which I bring forth, -And so should you, to love things nothing worth. - - - -That time of year thou mayst in me behold, -When yellow leaves, or none, or few do hang -Upon those boughs which shake against the cold, -Bare ruined choirs, where late the sweet birds sang. -In me thou seest the twilight of such day, -As after sunset fadeth in the west, -Which by and by black night doth take away, -Death's second self that seals up all in rest. -In me thou seest the glowing of such fire, -That on the ashes of his youth doth lie, -As the death-bed, whereon it must expire, -Consumed with that which it was nourished by. -This thou perceiv'st, which makes thy love more strong, -To love that well, which thou must leave ere long. - - - -But be contented when that fell arrest, -Without all bail shall carry me away, -My life hath in this line some interest, -Which for memorial still with thee shall stay. -When thou reviewest this, thou dost review, -The very part was consecrate to thee, -The earth can have but earth, which is his due, -My spirit is thine the better part of me, -So then thou hast but lost the dregs of life, -The prey of worms, my body being dead, -The coward conquest of a wretch's knife, -Too base of thee to be remembered, -The worth of that, is that which it contains, -And that is this, and this with thee remains. - - - -So are you to my thoughts as food to life, -Or as sweet-seasoned showers are to the ground; -And for the peace of you I hold such strife -As 'twixt a miser and his wealth is found. -Now proud as an enjoyer, and anon -Doubting the filching age will steal his treasure, -Now counting best to be with you alone, -Then bettered that the world may see my pleasure, -Sometime all full with feasting on your sight, -And by and by clean starved for a look, -Possessing or pursuing no delight -Save what is had, or must from you be took. -Thus do I pine and surfeit day by day, -Or gluttoning on all, or all away. - - - -Why is my verse so barren of new pride? -So far from variation or quick change? -Why with the time do I not glance aside -To new-found methods, and to compounds strange? -Why write I still all one, ever the same, -And keep invention in a noted weed, -That every word doth almost tell my name, -Showing their birth, and where they did proceed? -O know sweet love I always write of you, -And you and love are still my argument: -So all my best is dressing old words new, -Spending again what is already spent: -For as the sun is daily new and old, -So is my love still telling what is told. - - - -Thy glass will show thee how thy beauties wear, -Thy dial how thy precious minutes waste, -These vacant leaves thy mind's imprint will bear, -And of this book, this learning mayst thou taste. -The wrinkles which thy glass will truly show, -Of mouthed graves will give thee memory, -Thou by thy dial's shady stealth mayst know, -Time's thievish progress to eternity. -Look what thy memory cannot contain, -Commit to these waste blanks, and thou shalt find -Those children nursed, delivered from thy brain, -To take a new acquaintance of thy mind. -These offices, so oft as thou wilt look, -Shall profit thee, and much enrich thy book. - - - -So oft have I invoked thee for my muse, -And found such fair assistance in my verse, -As every alien pen hath got my use, -And under thee their poesy disperse. -Thine eyes, that taught the dumb on high to sing, -And heavy ignorance aloft to fly, -Have added feathers to the learned's wing, -And given grace a double majesty. -Yet be most proud of that which I compile, -Whose influence is thine, and born of thee, -In others' works thou dost but mend the style, -And arts with thy sweet graces graced be. -But thou art all my art, and dost advance -As high as learning, my rude ignorance. - - - -Whilst I alone did call upon thy aid, -My verse alone had all thy gentle grace, -But now my gracious numbers are decayed, -And my sick muse doth give an other place. -I grant (sweet love) thy lovely argument -Deserves the travail of a worthier pen, -Yet what of thee thy poet doth invent, -He robs thee of, and pays it thee again, -He lends thee virtue, and he stole that word, -From thy behaviour, beauty doth he give -And found it in thy cheek: he can afford -No praise to thee, but what in thee doth live. -Then thank him not for that which he doth say, -Since what he owes thee, thou thy self dost pay. - - - -O how I faint when I of you do write, -Knowing a better spirit doth use your name, -And in the praise thereof spends all his might, -To make me tongue-tied speaking of your fame. -But since your worth (wide as the ocean is) -The humble as the proudest sail doth bear, -My saucy bark (inferior far to his) -On your broad main doth wilfully appear. -Your shallowest help will hold me up afloat, -Whilst he upon your soundless deep doth ride, -Or (being wrecked) I am a worthless boat, -He of tall building, and of goodly pride. -Then if he thrive and I be cast away, -The worst was this, my love was my decay. - - - -Or I shall live your epitaph to make, -Or you survive when I in earth am rotten, -From hence your memory death cannot take, -Although in me each part will be forgotten. -Your name from hence immortal life shall have, -Though I (once gone) to all the world must die, -The earth can yield me but a common grave, -When you entombed in men's eyes shall lie, -Your monument shall be my gentle verse, -Which eyes not yet created shall o'er-read, -And tongues to be, your being shall rehearse, -When all the breathers of this world are dead, -You still shall live (such virtue hath my pen) -Where breath most breathes, even in the mouths of men. - - - -I grant thou wert not married to my muse, -And therefore mayst without attaint o'erlook -The dedicated words which writers use -Of their fair subject, blessing every book. -Thou art as fair in knowledge as in hue, -Finding thy worth a limit past my praise, -And therefore art enforced to seek anew, -Some fresher stamp of the time-bettering days. -And do so love, yet when they have devised, -What strained touches rhetoric can lend, -Thou truly fair, wert truly sympathized, -In true plain words, by thy true-telling friend. -And their gross painting might be better used, -Where cheeks need blood, in thee it is abused. - - - -I never saw that you did painting need, -And therefore to your fair no painting set, -I found (or thought I found) you did exceed, -That barren tender of a poet's debt: -And therefore have I slept in your report, -That you your self being extant well might show, -How far a modern quill doth come too short, -Speaking of worth, what worth in you doth grow. -This silence for my sin you did impute, -Which shall be most my glory being dumb, -For I impair not beauty being mute, -When others would give life, and bring a tomb. -There lives more life in one of your fair eyes, -Than both your poets can in praise devise. - - - -Who is it that says most, which can say more, -Than this rich praise, that you alone, are you? -In whose confine immured is the store, -Which should example where your equal grew. -Lean penury within that pen doth dwell, -That to his subject lends not some small glory, -But he that writes of you, if he can tell, -That you are you, so dignifies his story. -Let him but copy what in you is writ, -Not making worse what nature made so clear, -And such a counterpart shall fame his wit, -Making his style admired every where. -You to your beauteous blessings add a curse, -Being fond on praise, which makes your praises worse. - - - -My tongue-tied muse in manners holds her still, -While comments of your praise richly compiled, -Reserve their character with golden quill, -And precious phrase by all the Muses filed. -I think good thoughts, whilst other write good words, -And like unlettered clerk still cry Amen, -To every hymn that able spirit affords, -In polished form of well refined pen. -Hearing you praised, I say 'tis so, 'tis true, -And to the most of praise add something more, -But that is in my thought, whose love to you -(Though words come hindmost) holds his rank before, -Then others, for the breath of words respect, -Me for my dumb thoughts, speaking in effect. - - - -Was it the proud full sail of his great verse, -Bound for the prize of (all too precious) you, -That did my ripe thoughts in my brain inhearse, -Making their tomb the womb wherein they grew? -Was it his spirit, by spirits taught to write, -Above a mortal pitch, that struck me dead? -No, neither he, nor his compeers by night -Giving him aid, my verse astonished. -He nor that affable familiar ghost -Which nightly gulls him with intelligence, -As victors of my silence cannot boast, -I was not sick of any fear from thence. -But when your countenance filled up his line, -Then lacked I matter, that enfeebled mine. - - - -Farewell! thou art too dear for my possessing, -And like enough thou know'st thy estimate, -The charter of thy worth gives thee releasing: -My bonds in thee are all determinate. -For how do I hold thee but by thy granting, -And for that riches where is my deserving? -The cause of this fair gift in me is wanting, -And so my patent back again is swerving. -Thy self thou gav'st, thy own worth then not knowing, -Or me to whom thou gav'st it, else mistaking, -So thy great gift upon misprision growing, -Comes home again, on better judgement making. -Thus have I had thee as a dream doth flatter, -In sleep a king, but waking no such matter. - - - -When thou shalt be disposed to set me light, -And place my merit in the eye of scorn, -Upon thy side, against my self I'll fight, -And prove thee virtuous, though thou art forsworn: -With mine own weakness being best acquainted, -Upon thy part I can set down a story -Of faults concealed, wherein I am attainted: -That thou in losing me, shalt win much glory: -And I by this will be a gainer too, -For bending all my loving thoughts on thee, -The injuries that to my self I do, -Doing thee vantage, double-vantage me. -Such is my love, to thee I so belong, -That for thy right, my self will bear all wrong. - - - -Say that thou didst forsake me for some fault, -And I will comment upon that offence, -Speak of my lameness, and I straight will halt: -Against thy reasons making no defence. -Thou canst not (love) disgrace me half so ill, -To set a form upon desired change, -As I'll my self disgrace, knowing thy will, -I will acquaintance strangle and look strange: -Be absent from thy walks and in my tongue, -Thy sweet beloved name no more shall dwell, -Lest I (too much profane) should do it wronk: -And haply of our old acquaintance tell. -For thee, against my self I'll vow debate, -For I must ne'er love him whom thou dost hate. - - - -Then hate me when thou wilt, if ever, now, -Now while the world is bent my deeds to cross, -join with the spite of fortune, make me bow, -And do not drop in for an after-loss: -Ah do not, when my heart hath 'scaped this sorrow, -Come in the rearward of a conquered woe, -Give not a windy night a rainy morrow, -To linger out a purposed overthrow. -If thou wilt leave me, do not leave me last, -When other petty griefs have done their spite, -But in the onset come, so shall I taste -At first the very worst of fortune's might. -And other strains of woe, which now seem woe, -Compared with loss of thee, will not seem so. - - - -Some glory in their birth, some in their skill, -Some in their wealth, some in their body's force, -Some in their garments though new-fangled ill: -Some in their hawks and hounds, some in their horse. -And every humour hath his adjunct pleasure, -Wherein it finds a joy above the rest, -But these particulars are not my measure, -All these I better in one general best. -Thy love is better than high birth to me, -Richer than wealth, prouder than garments' costs, -Of more delight than hawks and horses be: -And having thee, of all men's pride I boast. -Wretched in this alone, that thou mayst take, -All this away, and me most wretchcd make. - - - -But do thy worst to steal thy self away, -For term of life thou art assured mine, -And life no longer than thy love will stay, -For it depends upon that love of thine. -Then need I not to fear the worst of wrongs, -When in the least of them my life hath end, -I see, a better state to me belongs -Than that, which on thy humour doth depend. -Thou canst not vex me with inconstant mind, -Since that my life on thy revolt doth lie, -O what a happy title do I find, -Happy to have thy love, happy to die! -But what's so blessed-fair that fears no blot? -Thou mayst be false, and yet I know it not. - - - -So shall I live, supposing thou art true, -Like a deceived husband, so love's face, -May still seem love to me, though altered new: -Thy looks with me, thy heart in other place. -For there can live no hatred in thine eye, -Therefore in that I cannot know thy change, -In many's looks, the false heart's history -Is writ in moods and frowns and wrinkles strange. -But heaven in thy creation did decree, -That in thy face sweet love should ever dwell, -Whate'er thy thoughts, or thy heart's workings be, -Thy looks should nothing thence, but sweetness tell. -How like Eve's apple doth thy beauty grow, -If thy sweet virtue answer not thy show. - - - -They that have power to hurt, and will do none, -That do not do the thing, they most do show, -Who moving others, are themselves as stone, -Unmoved, cold, and to temptation slow: -They rightly do inherit heaven's graces, -And husband nature's riches from expense, -Tibey are the lords and owners of their faces, -Others, but stewards of their excellence: -The summer's flower is to the summer sweet, -Though to it self, it only live and die, -But if that flower with base infection meet, -The basest weed outbraves his dignity: -For sweetest things turn sourest by their deeds, -Lilies that fester, smell far worse than weeds. - - - -How sweet and lovely dost thou make the shame, -Which like a canker in the fragrant rose, -Doth spot the beauty of thy budding name! -O in what sweets dost thou thy sins enclose! -That tongue that tells the story of thy days, -(Making lascivious comments on thy sport) -Cannot dispraise, but in a kind of praise, -Naming thy name, blesses an ill report. -O what a mansion have those vices got, -Which for their habitation chose out thee, -Where beauty's veil doth cover every blot, -And all things turns to fair, that eyes can see! -Take heed (dear heart) of this large privilege, -The hardest knife ill-used doth lose his edge. - - - -Some say thy fault is youth, some wantonness, -Some say thy grace is youth and gentle sport, -Both grace and faults are loved of more and less: -Thou mak'st faults graces, that to thee resort: -As on the finger of a throned queen, -The basest jewel will be well esteemed: -So are those errors that in thee are seen, -To truths translated, and for true things deemed. -How many lambs might the stern wolf betray, -If like a lamb he could his looks translate! -How many gazers mightst thou lead away, -if thou wouldst use the strength of all thy state! -But do not so, I love thee in such sort, -As thou being mine, mine is thy good report. - - - -How like a winter hath my absence been -From thee, the pleasure of the fleeting year! -What freezings have I felt, what dark days seen! -What old December's bareness everywhere! -And yet this time removed was summer's time, -The teeming autumn big with rich increase, -Bearing the wanton burden of the prime, -Like widowed wombs after their lords' decease: -Yet this abundant issue seemed to me -But hope of orphans, and unfathered fruit, -For summer and his pleasures wait on thee, -And thou away, the very birds are mute. -Or if they sing, 'tis with so dull a cheer, -That leaves look pale, dreading the winter's near. - - - -From you have I been absent in the spring, -When proud-pied April (dressed in all his trim) -Hath put a spirit of youth in every thing: -That heavy Saturn laughed and leaped with him. -Yet nor the lays of birds, nor the sweet smell -Of different flowers in odour and in hue, -Could make me any summer's story tell: -Or from their proud lap pluck them where they grew: -Nor did I wonder at the lily's white, -Nor praise the deep vermilion in the rose, -They were but sweet, but figures of delight: -Drawn after you, you pattern of all those. -Yet seemed it winter still, and you away, -As with your shadow I with these did play. - - - -The forward violet thus did I chide, -Sweet thief, whence didst thou steal thy sweet that smells, -If not from my love's breath? The purple pride -Which on thy soft check for complexion dwells, -In my love's veins thou hast too grossly dyed. -The lily I condemned for thy hand, -And buds of marjoram had stol'n thy hair, -The roses fearfully on thorns did stand, -One blushing shame, another white despair: -A third nor red, nor white, had stol'n of both, -And to his robbery had annexed thy breath, -But for his theft in pride of all his growth -A vengeful canker eat him up to death. -More flowers I noted, yet I none could see, -But sweet, or colour it had stol'n from thee. - - - -Where art thou Muse that thou forget'st so long, -To speak of that which gives thee all thy might? -Spend'st thou thy fury on some worthless song, -Darkening thy power to lend base subjects light? -Return forgetful Muse, and straight redeem, -In gentle numbers time so idly spent, -Sing to the ear that doth thy lays esteem, -And gives thy pen both skill and argument. -Rise resty Muse, my love's sweet face survey, -If time have any wrinkle graven there, -If any, be a satire to decay, -And make time's spoils despised everywhere. -Give my love fame faster than Time wastes life, -So thou prevent'st his scythe, and crooked knife. - - - -O truant Muse what shall be thy amends, -For thy neglect of truth in beauty dyed? -Both truth and beauty on my love depends: -So dost thou too, and therein dignified: -Make answer Muse, wilt thou not haply say, -'Truth needs no colour with his colour fixed, -Beauty no pencil, beauty's truth to lay: -But best is best, if never intermixed'? -Because he needs no praise, wilt thou be dumb? -Excuse not silence so, for't lies in thee, -To make him much outlive a gilded tomb: -And to be praised of ages yet to be. -Then do thy office Muse, I teach thee how, -To make him seem long hence, as he shows now. - - - -My love is strengthened though more weak in seeming, -I love not less, though less the show appear, -That love is merchandized, whose rich esteeming, -The owner's tongue doth publish every where. -Our love was new, and then but in the spring, -When I was wont to greet it with my lays, -As Philomel in summer's front doth sing, -And stops her pipe in growth of riper days: -Not that the summer is less pleasant now -Than when her mournful hymns did hush the night, -But that wild music burthens every bough, -And sweets grown common lose their dear delight. -Therefore like her, I sometime hold my tongue: -Because I would not dull you with my song. - - - -Alack what poverty my muse brings forth, -That having such a scope to show her pride, -The argument all bare is of more worth -Than when it hath my added praise beside. -O blame me not if I no more can write! -Look in your glass and there appears a face, -That over-goes my blunt invention quite, -Dulling my lines, and doing me disgrace. -Were it not sinful then striving to mend, -To mar the subject that before was well? -For to no other pass my verses tend, -Than of your graces and your gifts to tell. -And more, much more than in my verse can sit, -Your own glass shows you, when you look in it. - - - -To me fair friend you never can be old, -For as you were when first your eye I eyed, -Such seems your beauty still: three winters cold, -Have from the forests shook three summers' pride, -Three beauteous springs to yellow autumn turned, -In process of the seasons have I seen, -Three April perfumes in three hot Junes burned, -Since first I saw you fresh which yet are green. -Ah yet doth beauty like a dial hand, -Steal from his figure, and no pace perceived, -So your sweet hue, which methinks still doth stand -Hath motion, and mine eye may be deceived. -For fear of which, hear this thou age unbred, -Ere you were born was beauty's summer dead. - - - -Let not my love be called idolatry, -Nor my beloved as an idol show, -Since all alike my songs and praises be -To one, of one, still such, and ever so. -Kind is my love to-day, to-morrow kind, -Still constant in a wondrous excellence, -Therefore my verse to constancy confined, -One thing expressing, leaves out difference. -Fair, kind, and true, is all my argument, -Fair, kind, and true, varying to other words, -And in this change is my invention spent, -Three themes in one, which wondrous scope affords. -Fair, kind, and true, have often lived alone. -Which three till now, never kept seat in one. - - - -When in the chronicle of wasted time, -I see descriptions of the fairest wights, -And beauty making beautiful old rhyme, -In praise of ladies dead, and lovely knights, -Then in the blazon of sweet beauty's best, -Of hand, of foot, of lip, of eye, of brow, -I see their antique pen would have expressed, -Even such a beauty as you master now. -So all their praises are but prophecies -Of this our time, all you prefiguring, -And for they looked but with divining eyes, -They had not skill enough your worth to sing: -For we which now behold these present days, -Have eyes to wonder, but lack tongues to praise. - - - -Not mine own fears, nor the prophetic soul, -Of the wide world, dreaming on things to come, -Can yet the lease of my true love control, -Supposed as forfeit to a confined doom. -The mortal moon hath her eclipse endured, -And the sad augurs mock their own presage, -Incertainties now crown themselves assured, -And peace proclaims olives of endless age. -Now with the drops of this most balmy time, -My love looks fresh, and death to me subscribes, -Since spite of him I'll live in this poor rhyme, -While he insults o'er dull and speechless tribes. -And thou in this shalt find thy monument, -When tyrants' crests and tombs of brass are spent. - - - -What's in the brain that ink may character, -Which hath not figured to thee my true spirit, -What's new to speak, what now to register, -That may express my love, or thy dear merit? -Nothing sweet boy, but yet like prayers divine, -I must each day say o'er the very same, -Counting no old thing old, thou mine, I thine, -Even as when first I hallowed thy fair name. -So that eternal love in love's fresh case, -Weighs not the dust and injury of age, -Nor gives to necessary wrinkles place, -But makes antiquity for aye his page, -Finding the first conceit of love there bred, -Where time and outward form would show it dead. - - - -O never say that I was false of heart, -Though absence seemed my flame to qualify, -As easy might I from my self depart, -As from my soul which in thy breast doth lie: -That is my home of love, if I have ranged, -Like him that travels I return again, -Just to the time, not with the time exchanged, -So that my self bring water for my stain, -Never believe though in my nature reigned, -All frailties that besiege all kinds of blood, -That it could so preposterously be stained, -To leave for nothing all thy sum of good: -For nothing this wide universe I call, -Save thou my rose, in it thou art my all. - - - -Alas 'tis true, I have gone here and there, -And made my self a motley to the view, -Gored mine own thoughts, sold cheap what is most dear, -Made old offences of affections new. -Most true it is, that I have looked on truth -Askance and strangely: but by all above, -These blenches gave my heart another youth, -And worse essays proved thee my best of love. -Now all is done, have what shall have no end, -Mine appetite I never more will grind -On newer proof, to try an older friend, -A god in love, to whom I am confined. -Then give me welcome, next my heaven the best, -Even to thy pure and most most loving breast. - - - -O for my sake do you with Fortune chide, -The guilty goddess of my harmful deeds, -That did not better for my life provide, -Than public means which public manners breeds. -Thence comes it that my name receives a brand, -And almost thence my nature is subdued -To what it works in, like the dyer's hand: -Pity me then, and wish I were renewed, -Whilst like a willing patient I will drink, -Potions of eisel 'gainst my strong infection, -No bitterness that I will bitter think, -Nor double penance to correct correction. -Pity me then dear friend, and I assure ye, -Even that your pity is enough to cure me. - - - -Your love and pity doth th' impression fill, -Which vulgar scandal stamped upon my brow, -For what care I who calls me well or ill, -So you o'er-green my bad, my good allow? -You are my all the world, and I must strive, -To know my shames and praises from your tongue, -None else to me, nor I to none alive, -That my steeled sense or changes right or wrong. -In so profound abysm I throw all care -Of others' voices, that my adder's sense, -To critic and to flatterer stopped are: -Mark how with my neglect I do dispense. -You are so strongly in my purpose bred, -That all the world besides methinks are dead. - - - -Since I left you, mine eye is in my mind, -And that which governs me to go about, -Doth part his function, and is partly blind, -Seems seeing, but effectually is out: -For it no form delivers to the heart -Of bird, of flower, or shape which it doth latch, -Of his quick objects hath the mind no part, -Nor his own vision holds what it doth catch: -For if it see the rud'st or gentlest sight, -The most sweet favour or deformed'st creature, -The mountain, or the sea, the day, or night: -The crow, or dove, it shapes them to your feature. -Incapable of more, replete with you, -My most true mind thus maketh mine untrue. - - - -Or whether doth my mind being crowned with you -Drink up the monarch's plague this flattery? -Or whether shall I say mine eye saith true, -And that your love taught it this alchemy? -To make of monsters, and things indigest, -Such cherubins as your sweet self resemble, -Creating every bad a perfect best -As fast as objects to his beams assemble: -O 'tis the first, 'tis flattery in my seeing, -And my great mind most kingly drinks it up, -Mine eye well knows what with his gust is 'greeing, -And to his palate doth prepare the cup. -If it be poisoned, 'tis the lesser sin, -That mine eye loves it and doth first begin. - - - -Those lines that I before have writ do lie, -Even those that said I could not love you dearer, -Yet then my judgment knew no reason why, -My most full flame should afterwards burn clearer, -But reckoning time, whose millioned accidents -Creep in 'twixt vows, and change decrees of kings, -Tan sacred beauty, blunt the sharp'st intents, -Divert strong minds to the course of alt'ring things: -Alas why fearing of time's tyranny, -Might I not then say 'Now I love you best,' -When I was certain o'er incertainty, -Crowning the present, doubting of the rest? -Love is a babe, then might I not say so -To give full growth to that which still doth grow. - - - -Let me not to the marriage of true minds -Admit impediments, love is not love -Which alters when it alteration finds, -Or bends with the remover to remove. -O no, it is an ever-fixed mark -That looks on tempests and is never shaken; -It is the star to every wand'ring bark, -Whose worth's unknown, although his height be taken. -Love's not Time's fool, though rosy lips and cheeks -Within his bending sickle's compass come, -Love alters not with his brief hours and weeks, -But bears it out even to the edge of doom: -If this be error and upon me proved, -I never writ, nor no man ever loved. - - - -Accuse me thus, that I have scanted all, -Wherein I should your great deserts repay, -Forgot upon your dearest love to call, -Whereto all bonds do tie me day by day, -That I have frequent been with unknown minds, -And given to time your own dear-purchased right, -That I have hoisted sail to all the winds -Which should transport me farthest from your sight. -Book both my wilfulness and errors down, -And on just proof surmise, accumulate, -Bring me within the level of your frown, -But shoot not at me in your wakened hate: -Since my appeal says I did strive to prove -The constancy and virtue of your love. - - - -Like as to make our appetite more keen -With eager compounds we our palate urge, -As to prevent our maladies unseen, -We sicken to shun sickness when we purge. -Even so being full of your ne'er-cloying sweetness, -To bitter sauces did I frame my feeding; -And sick of welfare found a kind of meetness, -To be diseased ere that there was true needing. -Thus policy in love t' anticipate -The ills that were not, grew to faults assured, -And brought to medicine a healthful state -Which rank of goodness would by ill be cured. -But thence I learn and find the lesson true, -Drugs poison him that so feil sick of you. - - - -What potions have I drunk of Siren tears -Distilled from limbecks foul as hell within, -Applying fears to hopes, and hopes to fears, -Still losing when I saw my self to win! -What wretched errors hath my heart committed, -Whilst it hath thought it self so blessed never! -How have mine eyes out of their spheres been fitted -In the distraction of this madding fever! -O benefit of ill, now I find true -That better is, by evil still made better. -And ruined love when it is built anew -Grows fairer than at first, more strong, far greater. -So I return rebuked to my content, -And gain by ills thrice more than I have spent. - - - -That you were once unkind befriends me now, -And for that sorrow, which I then did feel, -Needs must I under my transgression bow, -Unless my nerves were brass or hammered steel. -For if you were by my unkindness shaken -As I by yours, y'have passed a hell of time, -And I a tyrant have no leisure taken -To weigh how once I suffered in your crime. -O that our night of woe might have remembered -My deepest sense, how hard true sorrow hits, -And soon to you, as you to me then tendered -The humble salve, which wounded bosoms fits! -But that your trespass now becomes a fee, -Mine ransoms yours, and yours must ransom me. - - - -'Tis better to be vile than vile esteemed, -When not to be, receives reproach of being, -And the just pleasure lost, which is so deemed, -Not by our feeling, but by others' seeing. -For why should others' false adulterate eyes -Give salutation to my sportive blood? -Or on my frailties why are frailer spies, -Which in their wills count bad what I think good? -No, I am that I am, and they that level -At my abuses, reckon up their own, -I may be straight though they themselves be bevel; -By their rank thoughts, my deeds must not be shown -Unless this general evil they maintain, -All men are bad and in their badness reign. - - - -Thy gift, thy tables, are within my brain -Full charactered with lasting memory, -Which shall above that idle rank remain -Beyond all date even to eternity. -Or at the least, so long as brain and heart -Have faculty by nature to subsist, -Till each to razed oblivion yield his part -Of thee, thy record never can be missed: -That poor retention could not so much hold, -Nor need I tallies thy dear love to score, -Therefore to give them from me was I bold, -To trust those tables that receive thee more: -To keep an adjunct to remember thee -Were to import forgetfulness in me. - - - -No! Time, thou shalt not boast that I do change, -Thy pyramids built up with newer might -To me are nothing novel, nothing strange, -They are but dressings Of a former sight: -Our dates are brief, and therefore we admire, -What thou dost foist upon us that is old, -And rather make them born to our desire, -Than think that we before have heard them told: -Thy registers and thee I both defy, -Not wond'ring at the present, nor the past, -For thy records, and what we see doth lie, -Made more or less by thy continual haste: -This I do vow and this shall ever be, -I will be true despite thy scythe and thee. - - - -If my dear love were but the child of state, -It might for Fortune's bastard be unfathered, -As subject to time's love or to time's hate, -Weeds among weeds, or flowers with flowers gathered. -No it was builded far from accident, -It suffers not in smiling pomp, nor falls -Under the blow of thralled discontent, -Whereto th' inviting time our fashion calls: -It fears not policy that heretic, -Which works on leases of short-numbered hours, -But all alone stands hugely politic, -That it nor grows with heat, nor drowns with showers. -To this I witness call the fools of time, -Which die for goodness, who have lived for crime. - - - -Were't aught to me I bore the canopy, -With my extern the outward honouring, -Or laid great bases for eternity, -Which proves more short than waste or ruining? -Have I not seen dwellers on form and favour -Lose all, and more by paying too much rent -For compound sweet; forgoing simple savour, -Pitiful thrivers in their gazing spent? -No, let me be obsequious in thy heart, -And take thou my oblation, poor but free, -Which is not mixed with seconds, knows no art, -But mutual render, only me for thee. -Hence, thou suborned informer, a true soul -When most impeached, stands least in thy control. - - - -O thou my lovely boy who in thy power, -Dost hold Time's fickle glass his fickle hour: -Who hast by waning grown, and therein show'st, -Thy lovers withering, as thy sweet self grow'st. -If Nature (sovereign mistress over wrack) -As thou goest onwards still will pluck thee back, -She keeps thee to this purpose, that her skill -May time disgrace, and wretched minutes kill. -Yet fear her O thou minion of her pleasure, -She may detain, but not still keep her treasure! -Her audit (though delayed) answered must be, -And her quietus is to render thee. - - - -In the old age black was not counted fair, -Or if it were it bore not beauty's name: -But now is black beauty's successive heir, -And beauty slandered with a bastard shame, -For since each hand hath put on nature's power, -Fairing the foul with art's false borrowed face, -Sweet beauty hath no name no holy bower, -But is profaned, if not lives in disgrace. -Therefore my mistress' eyes are raven black, -Her eyes so suited, and they mourners seem, -At such who not born fair no beauty lack, -Slandering creation with a false esteem, -Yet so they mourn becoming of their woe, -That every tongue says beauty should look so. - - - -How oft when thou, my music, music play'st, -Upon that blessed wood whose motion sounds -With thy sweet fingers when thou gently sway'st -The wiry concord that mine ear confounds, -Do I envy those jacks that nimble leap, -To kiss the tender inward of thy hand, -Whilst my poor lips which should that harvest reap, -At the wood's boldness by thee blushing stand. -To be so tickled they would change their state -And situation with those dancing chips, -O'er whom thy fingers walk with gentle gait, -Making dead wood more blest than living lips, -Since saucy jacks so happy are in this, -Give them thy fingers, me thy lips to kiss. - - - -Th' expense of spirit in a waste of shame -Is lust in action, and till action, lust -Is perjured, murd'rous, bloody full of blame, -Savage, extreme, rude, cruel, not to trust, -Enjoyed no sooner but despised straight, -Past reason hunted, and no sooner had -Past reason hated as a swallowed bait, -On purpose laid to make the taker mad. -Mad in pursuit and in possession so, -Had, having, and in quest, to have extreme, -A bliss in proof and proved, a very woe, -Before a joy proposed behind a dream. -All this the world well knows yet none knows well, -To shun the heaven that leads men to this hell. - - - -My mistress' eyes are nothing like the sun, -Coral is far more red, than her lips red, -If snow be white, why then her breasts are dun: -If hairs be wires, black wires grow on her head: -I have seen roses damasked, red and white, -But no such roses see I in her cheeks, -And in some perfumes is there more delight, -Than in the breath that from my mistress reeks. -I love to hear her speak, yet well I know, -That music hath a far more pleasing sound: -I grant I never saw a goddess go, -My mistress when she walks treads on the ground. -And yet by heaven I think my love as rare, -As any she belied with false compare. - - - -Thou art as tyrannous, so as thou art, -As those whose beauties proudly make them cruel; -For well thou know'st to my dear doting heart -Thou art the fairest and most precious jewel. -Yet in good faith some say that thee behold, -Thy face hath not the power to make love groan; -To say they err, I dare not be so bold, -Although I swear it to my self alone. -And to be sure that is not false I swear, -A thousand groans but thinking on thy face, -One on another's neck do witness bear -Thy black is fairest in my judgment's place. -In nothing art thou black save in thy deeds, -And thence this slander as I think proceeds. - - - -Thine eyes I love, and they as pitying me, -Knowing thy heart torment me with disdain, -Have put on black, and loving mourners be, -Looking with pretty ruth upon my pain. -And truly not the morning sun of heaven -Better becomes the grey cheeks of the east, -Nor that full star that ushers in the even -Doth half that glory to the sober west -As those two mourning eyes become thy face: -O let it then as well beseem thy heart -To mourn for me since mourning doth thee grace, -And suit thy pity like in every part. -Then will I swear beauty herself is black, -And all they foul that thy complexion lack. - - - -Beshrew that heart that makes my heart to groan -For that deep wound it gives my friend and me; -Is't not enough to torture me alone, -But slave to slavery my sweet'st friend must be? -Me from my self thy cruel eye hath taken, -And my next self thou harder hast engrossed, -Of him, my self, and thee I am forsaken, -A torment thrice three-fold thus to be crossed: -Prison my heart in thy steel bosom's ward, -But then my friend's heart let my poor heart bail, -Whoe'er keeps me, let my heart be his guard, -Thou canst not then use rigour in my gaol. -And yet thou wilt, for I being pent in thee, -Perforce am thine and all that is in me. - - - -So now I have confessed that he is thine, -And I my self am mortgaged to thy will, -My self I'll forfeit, so that other mine, -Thou wilt restore to be my comfort still: -But thou wilt not, nor he will not be free, -For thou art covetous, and he is kind, -He learned but surety-like to write for me, -Under that bond that him as fist doth bind. -The statute of thy beauty thou wilt take, -Thou usurer that put'st forth all to use, -And sue a friend, came debtor for my sake, -So him I lose through my unkind abuse. -Him have I lost, thou hast both him and me, -He pays the whole, and yet am I not free. - - - -Whoever hath her wish, thou hast thy will, -And 'Will' to boot, and 'Will' in over-plus, -More than enough am I that vex thee still, -To thy sweet will making addition thus. -Wilt thou whose will is large and spacious, -Not once vouchsafe to hide my will in thine? -Shall will in others seem right gracious, -And in my will no fair acceptance shine? -The sea all water, yet receives rain still, -And in abundance addeth to his store, -So thou being rich in will add to thy will -One will of mine to make thy large will more. -Let no unkind, no fair beseechers kill, -Think all but one, and me in that one 'Will.' - - - -If thy soul check thee that I come so near, -Swear to thy blind soul that I was thy 'Will', -And will thy soul knows is admitted there, -Thus far for love, my love-suit sweet fulfil. -'Will', will fulfil the treasure of thy love, -Ay, fill it full with wills, and my will one, -In things of great receipt with case we prove, -Among a number one is reckoned none. -Then in the number let me pass untold, -Though in thy store's account I one must be, -For nothing hold me, so it please thee hold, -That nothing me, a something sweet to thee. -Make but my name thy love, and love that still, -And then thou lov'st me for my name is Will. - - - -Thou blind fool Love, what dost thou to mine eyes, -That they behold and see not what they see? -They know what beauty is, see where it lies, -Yet what the best is, take the worst to be. -If eyes corrupt by over-partial looks, -Be anchored in the bay where all men ride, -Why of eyes' falsehood hast thou forged hooks, -Whereto the judgment of my heart is tied? -Why should my heart think that a several plot, -Which my heart knows the wide world's common place? -Or mine eyes seeing this, say this is not -To put fair truth upon so foul a face? -In things right true my heart and eyes have erred, -And to this false plague are they now transferred. - - - -When my love swears that she is made of truth, -I do believe her though I know she lies, -That she might think me some untutored youth, -Unlearned in the world's false subtleties. -Thus vainly thinking that she thinks me young, -Although she knows my days are past the best, -Simply I credit her false-speaking tongue, -On both sides thus is simple truth suppressed: -But wherefore says she not she is unjust? -And wherefore say not I that I am old? -O love's best habit is in seeming trust, -And age in love, loves not to have years told. -Therefore I lie with her, and she with me, -And in our faults by lies we flattered be. - - - -O call not me to justify the wrong, -That thy unkindness lays upon my heart, -Wound me not with thine eye but with thy tongue, -Use power with power, and slay me not by art, -Tell me thou lov'st elsewhere; but in my sight, -Dear heart forbear to glance thine eye aside, -What need'st thou wound with cunning when thy might -Is more than my o'erpressed defence can bide? -Let me excuse thee, ah my love well knows, -Her pretty looks have been mine enemies, -And therefore from my face she turns my foes, -That they elsewhere might dart their injuries: -Yet do not so, but since I am near slain, -Kill me outright with looks, and rid my pain. - - - -Be wise as thou art cruel, do not press -My tongue-tied patience with too much disdain: -Lest sorrow lend me words and words express, -The manner of my pity-wanting pain. -If I might teach thee wit better it were, -Though not to love, yet love to tell me so, -As testy sick men when their deaths be near, -No news but health from their physicians know. -For if I should despair I should grow mad, -And in my madness might speak ill of thee, -Now this ill-wresting world is grown so bad, -Mad slanderers by mad ears believed be. -That I may not be so, nor thou belied, -Bear thine eyes straight, though thy proud heart go wide. - - - -In faith I do not love thee with mine eyes, -For they in thee a thousand errors note, -But 'tis my heart that loves what they despise, -Who in despite of view is pleased to dote. -Nor are mine cars with thy tongue's tune delighted, -Nor tender feeling to base touches prone, -Nor taste, nor smell, desire to be invited -To any sensual feast with thee alone: -But my five wits, nor my five senses can -Dissuade one foolish heart from serving thee, -Who leaves unswayed the likeness of a man, -Thy proud heart's slave and vassal wretch to be: -Only my plague thus far I count my gain, -That she that makes me sin, awards me pain. - - - -Love is my sin, and thy dear virtue hate, -Hate of my sin, grounded on sinful loving, -O but with mine, compare thou thine own state, -And thou shalt find it merits not reproving, -Or if it do, not from those lips of thine, -That have profaned their scarlet ornaments, -And sealed false bonds of love as oft as mine, -Robbed others' beds' revenues of their rents. -Be it lawful I love thee as thou lov'st those, -Whom thine eyes woo as mine importune thee, -Root pity in thy heart that when it grows, -Thy pity may deserve to pitied be. -If thou dost seek to have what thou dost hide, -By self-example mayst thou be denied. - - - -Lo as a careful huswife runs to catch, -One of her feathered creatures broke away, -Sets down her babe and makes all swift dispatch -In pursuit of the thing she would have stay: -Whilst her neglected child holds her in chase, -Cries to catch her whose busy care is bent, -To follow that which flies before her face: -Not prizing her poor infant's discontent; -So run'st thou after that which flies from thee, -Whilst I thy babe chase thee afar behind, -But if thou catch thy hope turn back to me: -And play the mother's part, kiss me, be kind. -So will I pray that thou mayst have thy Will, -If thou turn back and my loud crying still. - - - -Two loves I have of comfort and despair, -Which like two spirits do suggest me still, -The better angel is a man right fair: -The worser spirit a woman coloured ill. -To win me soon to hell my female evil, -Tempteth my better angel from my side, -And would corrupt my saint to be a devil: -Wooing his purity with her foul pride. -And whether that my angel be turned fiend, -Suspect I may, yet not directly tell, -But being both from me both to each friend, -I guess one angel in another's hell. -Yet this shall I ne'er know but live in doubt, -Till my bad angel fire my good one out. - - - -Those lips that Love's own hand did make, -Breathed forth the sound that said 'I hate', -To me that languished for her sake: -But when she saw my woeful state, -Straight in her heart did mercy come, -Chiding that tongue that ever sweet, -Was used in giving gentle doom: -And taught it thus anew to greet: -'I hate' she altered with an end, -That followed it as gentle day, -Doth follow night who like a fiend -From heaven to hell is flown away. -'I hate', from hate away she threw, -And saved my life saying 'not you'. - -Poor soul the centre of my sinful earth, -My sinful earth these rebel powers array, -Why dost thou pine within and suffer dearth -Painting thy outward walls so costly gay? -Why so large cost having so short a lease, -Dost thou upon thy fading mansion spend? -Shall worms inheritors of this excess -Eat up thy charge? is this thy body's end? -Then soul live thou upon thy servant's loss, -And let that pine to aggravate thy store; -Buy terms divine in selling hours of dross; -Within be fed, without be rich no more, -So shall thou feed on death, that feeds on men, -And death once dead, there's no more dying then. - -My love is as a fever longing still, -For that which longer nurseth the disease, -Feeding on that which doth preserve the ill, -Th' uncertain sickly appetite to please: -My reason the physician to my love, -Angry that his prescriptions are not kept -Hath left me, and I desperate now approve, -Desire is death, which physic did except. -Past cure I am, now reason is past care, -And frantic-mad with evermore unrest, -My thoughts and my discourse as mad men's are, -At random from the truth vainly expressed. -For I have sworn thee fair, and thought thee bright, -Who art as black as hell, as dark as night. - -O me! what eyes hath love put in my head, -Which have no correspondence with true sight, -Or if they have, where is my judgment fled, -That censures falsely what they see aright? -If that be fair whereon my false eyes dote, -What means the world to say it is not so? -If it be not, then love doth well denote, -Love's eye is not so true as all men's: no, -How can it? O how can love's eye be true, -That is so vexed with watching and with tears? -No marvel then though I mistake my view, -The sun it self sees not, till heaven clears. -O cunning love, with tears thou keep'st me blind, -Lest eyes well-seeing thy foul faults should find. - -Canst thou O cruel, say I love thee not, -When I against my self with thee partake? -Do I not think on thee when I forgot -Am of my self, all-tyrant, for thy sake? -Who hateth thee that I do call my friend, -On whom frown'st thou that I do fawn upon, -Nay if thou lour'st on me do I not spend -Revenge upon my self with present moan? -What merit do I in my self respect, -That is so proud thy service to despise, -When all my best doth worship thy defect, -Commanded by the motion of thine eyes? -But love hate on for now I know thy mind, -Those that can see thou lov'st, and I am blind. - -O from what power hast thou this powerful might, -With insufficiency my heart to sway, -To make me give the lie to my true sight, -And swear that brightness doth not grace the day? -Whence hast thou this becoming of things ill, -That in the very refuse of thy deeds, -There is such strength and warrantise of skill, -That in my mind thy worst all best exceeds? -Who taught thee how to make me love thee more, -The more I hear and see just cause of hate? -O though I love what others do abhor, -With others thou shouldst not abhor my state. -If thy unworthiness raised love in me, -More worthy I to be beloved of thee. - -Love is too young to know what conscience is, -Yet who knows not conscience is born of love? -Then gentle cheater urge not my amiss, -Lest guilty of my faults thy sweet self prove. -For thou betraying me, I do betray -My nobler part to my gross body's treason, -My soul doth tell my body that he may, -Triumph in love, flesh stays no farther reason, -But rising at thy name doth point out thee, -As his triumphant prize, proud of this pride, -He is contented thy poor drudge to be, -To stand in thy affairs, fall by thy side. -No want of conscience hold it that I call, -Her love, for whose dear love I rise and fall. - -In loving thee thou know'st I am forsworn, -But thou art twice forsworn to me love swearing, -In act thy bed-vow broke and new faith torn, -In vowing new hate after new love bearing: -But why of two oaths' breach do I accuse thee, -When I break twenty? I am perjured most, -For all my vows are oaths but to misuse thee: -And all my honest faith in thee is lost. -For I have sworn deep oaths of thy deep kindness: -Oaths of thy love, thy truth, thy constancy, -And to enlighten thee gave eyes to blindness, -Or made them swear against the thing they see. -For I have sworn thee fair: more perjured I, -To swear against the truth so foul a be. - -Cupid laid by his brand and fell asleep, -A maid of Dian's this advantage found, -And his love-kindling fire did quickly steep -In a cold valley-fountain of that ground: -Which borrowed from this holy fire of Love, -A dateless lively heat still to endure, -And grew a seeting bath which yet men prove, -Against strange maladies a sovereign cure: -But at my mistress' eye Love's brand new-fired, -The boy for trial needs would touch my breast, -I sick withal the help of bath desired, -And thither hied a sad distempered guest. -But found no cure, the bath for my help lies, -Where Cupid got new fire; my mistress' eyes. - -The little Love-god lying once asleep, -Laid by his side his heart-inflaming brand, -Whilst many nymphs that vowed chaste life to keep, -Came tripping by, but in her maiden hand, -The fairest votary took up that fire, -Which many legions of true hearts had warmed, -And so the general of hot desire, -Was sleeping by a virgin hand disarmed. -This brand she quenched in a cool well by, -Which from Love's fire took heat perpetual, -Growing a bath and healthful remedy, -For men discased, but I my mistress' thrall, -Came there for cure and this by that I prove, -Love's fire heats water, water cools not love. - - - THE END \ No newline at end of file From 7026e02ee0200d51f8c7ca0a51f0899cda09a9c4 Mon Sep 17 00:00:00 2001 From: jazelly Date: Sun, 5 May 2024 19:42:00 +0930 Subject: [PATCH 10/96] chore: update readme of slowllama --- .gitignore | 1 + .gitmodules | 4 ++-- mac/README.md | 4 +++- 3 files changed, 6 insertions(+), 3 deletions(-) diff --git a/.gitignore b/.gitignore index 57118c8..61f88e8 100644 --- a/.gitignore +++ b/.gitignore @@ -163,3 +163,4 @@ cython_debug/ checkpoint_dir/ results/ llama-2-7b/ +data/** \ No newline at end of file diff --git a/.gitmodules b/.gitmodules index 98a3545..ce2a89d 100644 --- a/.gitmodules +++ b/.gitmodules @@ -1,5 +1,5 @@ -[submodule "mac/slowllama"] - path = mac/slowllama +[submodule "mac/slowllama/slowllama"] + path = mac/slowllama/slowllama url = git@github.com:jazelly/slowllama.git [submodule "llama-gguf/llama.cpp"] path = llama-gguf/llama.cpp diff --git a/mac/README.md b/mac/README.md index 99110df..068334e 100644 --- a/mac/README.md +++ b/mac/README.md @@ -9,4 +9,6 @@ Both only support LLAMA based models. ## Slowllama -Slowllama is a python project purely focusing on finetuning LLAMA model on MacBook. It offloads weights to SSD to support training of large-sized model, i.e. with 70B. +Slowllama is a python project purely focusing on finetuning LLAMA model on MacBook. It offloads weights to SSD to support training of large-sized model, i.e. 70B parameters. + +Please refer to `./slowllama/` for specific instructions of usage \ No newline at end of file From e35661073d13afc3ad8077916f7b7a6bff6fafd2 Mon Sep 17 00:00:00 2001 From: jazelly Date: Sun, 5 May 2024 19:54:56 +0930 Subject: [PATCH 11/96] fix: submodule mv --- .gitignore | 3 +- LICENSE | 2 +- mac/slowllama | 1 - mac/slowllama/llama2/README.md | 17 + mac/slowllama/llama2/config.py | 62 +++ mac/slowllama/llama2/logs/.gitignore | 2 + mac/slowllama/llama2/slowllama.py | 281 ++++++++++++ mac/slowllama/slowllama/.gitignore | 8 + mac/slowllama/slowllama/LICENSE | 21 + mac/slowllama/slowllama/README.md | 298 +++++++++++++ mac/slowllama/slowllama/blackbox.py | 60 +++ mac/slowllama/slowllama/chat.py | 29 ++ mac/slowllama/slowllama/conf.py | 55 +++ mac/slowllama/slowllama/conf_fp16.py | 9 + mac/slowllama/slowllama/conf_fp32.py | 8 + mac/slowllama/slowllama/docs/a10.md | 64 +++ mac/slowllama/slowllama/docs/lora_weights.md | 416 ++++++++++++++++++ mac/slowllama/slowllama/e2e7b.sh | 6 + mac/slowllama/slowllama/finetune.py | 58 +++ mac/slowllama/slowllama/finetune_dolly.py | 93 ++++ mac/slowllama/slowllama/llama2.py | 380 ++++++++++++++++ mac/slowllama/slowllama/llama2_loader.py | 202 +++++++++ mac/slowllama/slowllama/logs/.gitignore | 2 + mac/slowllama/slowllama/merge_lora.py | 17 + mac/slowllama/slowllama/model_config.py | 27 ++ mac/slowllama/slowllama/plot_lora.py | 48 ++ mac/slowllama/slowllama/prepare_model.py | 14 + .../slowllama/static/finetune_a10_7b.png | Bin 0 -> 176530 bytes .../slowllama/static/finetune_combined.png | Bin 0 -> 327766 bytes .../slowllama/static/finetune_fwd.png | Bin 0 -> 339067 bytes .../slowllama/static/finetune_m1_7b.png | Bin 0 -> 209732 bytes .../slowllama/static/llama2_70b_m1.png | Bin 0 -> 213506 bytes .../slowllama/test_data/cubestat.txt | 9 + mac/slowllama/slowllama/test_gen.py | 25 ++ mac/slowllama/slowllama/utils.py | 94 ++++ 35 files changed, 2307 insertions(+), 4 deletions(-) delete mode 160000 mac/slowllama create mode 100644 mac/slowllama/llama2/README.md create mode 100644 mac/slowllama/llama2/config.py create mode 100644 mac/slowllama/llama2/logs/.gitignore create mode 100644 mac/slowllama/llama2/slowllama.py create mode 100644 mac/slowllama/slowllama/.gitignore create mode 100644 mac/slowllama/slowllama/LICENSE create mode 100644 mac/slowllama/slowllama/README.md create mode 100644 mac/slowllama/slowllama/blackbox.py create mode 100644 mac/slowllama/slowllama/chat.py create mode 100644 mac/slowllama/slowllama/conf.py create mode 100644 mac/slowllama/slowllama/conf_fp16.py create mode 100644 mac/slowllama/slowllama/conf_fp32.py create mode 100644 mac/slowllama/slowllama/docs/a10.md create mode 100644 mac/slowllama/slowllama/docs/lora_weights.md create mode 100755 mac/slowllama/slowllama/e2e7b.sh create mode 100644 mac/slowllama/slowllama/finetune.py create mode 100644 mac/slowllama/slowllama/finetune_dolly.py create mode 100644 mac/slowllama/slowllama/llama2.py create mode 100644 mac/slowllama/slowllama/llama2_loader.py create mode 100644 mac/slowllama/slowllama/logs/.gitignore create mode 100644 mac/slowllama/slowllama/merge_lora.py create mode 100644 mac/slowllama/slowllama/model_config.py create mode 100644 mac/slowllama/slowllama/plot_lora.py create mode 100644 mac/slowllama/slowllama/prepare_model.py create mode 100644 mac/slowllama/slowllama/static/finetune_a10_7b.png create mode 100644 mac/slowllama/slowllama/static/finetune_combined.png create mode 100644 mac/slowllama/slowllama/static/finetune_fwd.png create mode 100644 mac/slowllama/slowllama/static/finetune_m1_7b.png create mode 100644 mac/slowllama/slowllama/static/llama2_70b_m1.png create mode 100644 mac/slowllama/slowllama/test_data/cubestat.txt create mode 100644 mac/slowllama/slowllama/test_gen.py create mode 100644 mac/slowllama/slowllama/utils.py diff --git a/.gitignore b/.gitignore index 61f88e8..d86ec6e 100644 --- a/.gitignore +++ b/.gitignore @@ -162,5 +162,4 @@ cython_debug/ checkpoint_dir/ results/ -llama-2-7b/ -data/** \ No newline at end of file +llama-2-7b/ \ No newline at end of file diff --git a/LICENSE b/LICENSE index b76a2bd..9dabb71 100644 --- a/LICENSE +++ b/LICENSE @@ -1,6 +1,6 @@ MIT License -Copyright (c) 2024 jazelly +Copyright (c) 2024 Jason Zhang Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal diff --git a/mac/slowllama b/mac/slowllama deleted file mode 160000 index 0d8a4cf..0000000 --- a/mac/slowllama +++ /dev/null @@ -1 +0,0 @@ -Subproject commit 0d8a4cf5dc8767db81d019812f054a77ce68b31e diff --git a/mac/slowllama/llama2/README.md b/mac/slowllama/llama2/README.md new file mode 100644 index 0000000..18f3e2d --- /dev/null +++ b/mac/slowllama/llama2/README.md @@ -0,0 +1,17 @@ +## Finetune LLAMA 2 with Slowllama + +The submodule `slowllama` hardcoded model loader, so we have to get it running +with your case dynamically by adding a facade `slowllama.py` under this dir. To +make it work with `slowllama`, make sure you place this finetune directory at the +same level as `slowllama`, e.g. + +``` +project +│ llama2-finetune-dir +│ slowllama +``` + +- Download model from [meta-llama/llama](https://github.com/meta-llama/llama) to +this dir + +- Suppose the downloaded model is in dir `llama-2-7b` \ No newline at end of file diff --git a/mac/slowllama/llama2/config.py b/mac/slowllama/llama2/config.py new file mode 100644 index 0000000..6da85a5 --- /dev/null +++ b/mac/slowllama/llama2/config.py @@ -0,0 +1,62 @@ +import logging +import torch + +# which device to use for finetuning +# 'cpu', 'mps' (for Apple devices) or 'cuda' +device = 'mps' + +# random seed to use. Makes runs reproducible. +seed = 54321 + +# learning rate +lr = 1e-4 + +# logging gradient and weight distribution to log file +# useful for debugging, but makes more +log_lora_grad = False +log_lora_weight = False + +# how wide would LoRA layers be? (N x lora_rank) and (lora_rank x M). +# Larger number - larger layer - more capacity. +lora_rank = 4 + +log_level = logging.DEBUG + +# training settings + +# total number of iterations to run. No microbatching so far +iters = 20 + +# how long should be the sequence to train on? +# we pick seq_len tokens and try to predict token [seq_len + 1] +seq_len = 128 + +# how large should be the batch size? +batch_size = 16 + +# current script doesn't have validation set at all. +# instead, we run prompt completion every eval_period iterations +# and check how the completion look like +eval_before_training = False +eval_period = 20 + +# how many tokens to generate for such test completion +gen_tokens = 32 +# what prompt to use for test completion +prompt = 'Cubestat reports the following metrics: ' + +# where to save LoRA snapshots +snapshots_path = 'out' + +# plaintext input file which will be tokenized and used for training +finetune_file = '../slowllama/test_data/cubestat.txt' + +# which model to use - path to raw model +llama2_model_path = './llama-2-7b' + +adamw_eps = 1e-4 +compute_dtype = torch.float16 +frozen_dtype = torch.float16 + +# trained model to store +frozen_model_path = './llama-2-7b_f16' \ No newline at end of file diff --git a/mac/slowllama/llama2/logs/.gitignore b/mac/slowllama/llama2/logs/.gitignore new file mode 100644 index 0000000..c96a04f --- /dev/null +++ b/mac/slowllama/llama2/logs/.gitignore @@ -0,0 +1,2 @@ +* +!.gitignore \ No newline at end of file diff --git a/mac/slowllama/llama2/slowllama.py b/mac/slowllama/llama2/slowllama.py new file mode 100644 index 0000000..8c5f0d4 --- /dev/null +++ b/mac/slowllama/llama2/slowllama.py @@ -0,0 +1,281 @@ +# loads model in original llama2 format and saves to another folder in sequential format + +import torch +import logging + +from config import * +import os +import json +import gc +import glob +import shutil + +from llama2 import Transformer + +from dataclasses import dataclass +from typing import Optional + + +@dataclass +class ModelArgs: + dim: int = 4096 + n_layers: int = 32 + n_heads: int = 32 + n_kv_heads: Optional[int] = None + multiple_of: int = 256 # make SwiGLU hidden layer size multiple of large power of 2 + norm_eps: float = 1e-5 + max_seq_len: int = 2048 + dropout: float = 0.0 # unless we bring back + ffn_dim_multiplier: Optional[float] = None + compute_dtype: torch.dtype = torch.float32 + rope_theta: float = 10000.0 + lora_rank: int = 8 + lora_alpha: int = 64 + lora_dropout: float = 0.05 + served_model_path: str = "" # relative path by default + cached_data_path: str = "" # relative path by default + init_frozen: bool = True + frozen_dtype: torch.dtype = torch.bfloat16 + vocab_size: int = 32000 + vocab_size_override: int = 32000 + + +def device_supports_dtype(device, dtype): + try: + a = torch.rand(2, 2).to(device).to(dtype) + b = torch.rand(2, 2).to(device).to(dtype) + c = a.mm(b) + logging.debug(f"success, {device} supports {dtype}") + return True + except TypeError as e: + return False + + +# how are weights sharded in llama2 - by rows or columns +join_dim = { + "wq": 0, + "wk": 0, + "wv": 0, + "wo": 1, + "w1": 0, + "w2": 1, + "w3": 0, + "output": 0, + "tok_embeddings": 1, +} + + +def get_subset(title, weight_subset, index): + if title in join_dim.keys(): + jdim = join_dim[title] + step = weight_subset.shape[jdim] + subset = (slice(step * index, step * (index + 1)), slice(None)) + if jdim == 1: + subset = (subset[1], subset[0]) + return subset + else: + return tuple(slice(None) for _ in range(len(weight_subset.shape))) + + +def get_w_subset(title, weight, shards, shard): + if title in join_dim.keys(): + jdim = join_dim[title] + step = weight.shape[jdim] // shards + subset = (slice(step * shard, step * (shard + 1)), slice(None)) + if jdim == 1: + subset = (subset[1], subset[0]) + return subset + else: + return tuple(slice(None) for _ in range(len(weight.shape))) + + +def apply_subset(module, weight_subset, checkpoint_index, title): + with torch.no_grad(): + idx_subset = get_subset(title, weight_subset, checkpoint_index) + module.weight[idx_subset] = weight_subset + + +def prepare_model(llama2_path, frozen_path, **kwargs): + params_path = os.path.join(llama2_path, "params.json") + with open(params_path, "r") as conf_file: + config = json.loads(conf_file.read()) + + for k, v in kwargs.items(): + config[k] = v + + args = ModelArgs(**config) + args.vocab_size = args.vocab_size_override + args.served_model_path = frozen_path + + logging.info("creating model instance") + model = Transformer(args) + paths = sorted(glob.glob(f"{llama2_path}/consolidated.*.pth")) + + shards = len(paths) + + for ci, checkpoint_path in enumerate(paths): + logging.info(f"prepare_model: processing checkpoint {ci} out of {shards}") + + checkpoint = torch.load(checkpoint_path, map_location="cpu") + + for i, layer in enumerate(model.layers): + prefix = f"layers.{i}." + # block = layer.loaded_inner() + for title, submodule in layer.named_modules(): + if hasattr(submodule, "weight"): + full_path = f"{prefix}{title}.weight" + weight_subset = checkpoint[full_path] + apply_subset(submodule, weight_subset, ci, title) + del checkpoint[full_path] + gc.collect() + + prefix = f"layers.{i}.attention." + attention = layer.attention.loaded_inner() + for title, submodule in attention.named_modules(): + if hasattr(submodule, "weight"): + if "attention_norm" in title: + full_path = f"layers.{i}.attention_norm.weight" + else: + full_path = f"{prefix}{title}.weight" + weight_subset = checkpoint[full_path] + apply_subset(submodule, weight_subset, ci, title) + del checkpoint[full_path] + gc.collect() + layer.attention.save(attention) + + prefix = f"layers.{i}.feed_forward." + feed_forward = layer.feed_forward.loaded_inner() + for title, submodule in feed_forward.named_modules(): + if hasattr(submodule, "weight"): + if "ffn_norm" in title: + full_path = f"layers.{i}.ffn_norm.weight" + else: + full_path = f"{prefix}{title}.weight" + weight_subset = checkpoint[full_path] + apply_subset(submodule, weight_subset, ci, title) + del checkpoint[full_path] + gc.collect() + layer.feed_forward.save(feed_forward) + logging.info( + f"prepare_model: updating layer {i} out of {len(model.layers)}" + ) + # layer.save(block) + + # now repeat for other submodules: output, embeddings and norm + title = "output" + block = model.output.loaded_inner() + apply_subset(block, checkpoint[f"{title}.weight"], ci, title) + logging.info(f"prepare_model: updating output layer") + model.output.save(block) + + title = "tok_embeddings" + block = model.tok_embeddings.loaded_inner() + apply_subset(block, checkpoint[f"{title}.weight"], ci, title) + logging.info(f"prepare_model: updating token embeddings") + model.tok_embeddings.save(block) + + # norm left + apply_subset(model.norm, checkpoint["norm.weight"], ci, None) + + # we also need to copy: + # - params.json + # - model dict itself (norm + Lora) + # - tokenizer?' + shutil.copy(params_path, os.path.join(frozen_path, "params.json")) + shutil.copy( + os.path.join(llama2_path, "tokenizer.model"), + os.path.join(frozen_path, "tokenizer.model"), + ) + torch.save( + model.to(args.frozen_dtype).state_dict(), os.path.join(frozen_path, "model.pth") + ) + + return model + + +def load_frozen(path, **kwargs): + logging.info(f"loading sequential model from {path}") + params_path = os.path.join(path, "params.json") + with open(params_path, "r") as conf_file: + config = json.loads(conf_file.read()) + + for k, v in kwargs.items(): + config[k] = v + + args = ModelArgs(**config) + args.vocab_size = args.vocab_size_override + args.init_frozen = False + args.served_model_path = path + logging.info(f"creating model instance") + model = Transformer(args).to(args.compute_dtype) + logging.info(f"loading model dict") + model.load_state_dict(torch.load(os.path.join(path, "model.pth")), strict=False) + return model + + +# this is merging LoRA back to original weights in llama2 format +def add_lora(model_path, lora_path): + lora_weights = torch.load(lora_path, map_location="cpu") + paths = sorted(glob.glob(f"{model_path}/consolidated.*.pth")) + params_path = os.path.join(model_path, "params.json") + with open(params_path, "r") as conf_file: + config = json.loads(conf_file.read()) + + shards = len(paths) + + config = ModelArgs(**config) + + n_layers = int(config.n_layers) + + lora_scale = config.lora_alpha / config.lora_rank + + for ci, checkpoint_path in enumerate(paths): + logging.info(f"add_lora: processing checkpoint {ci} out of {shards}") + checkpoint = torch.load(checkpoint_path, map_location="cpu") + + for layer in range(n_layers): + logging.info( + f"add_lora: processing checkpoint {ci} layer {layer} out of {n_layers}" + ) + for attn_key in ["v", "q"]: + local_path = f"w{attn_key}" + checkpoint_key = f"layers.{layer}.attention.{local_path}.weight" + a_key = f"{attn_key}_lora_{layer}.A.weight" + b_key = f"{attn_key}_lora_{layer}.B.weight" + + original_type = lora_weights[b_key].dtype + + if device_supports_dtype("cpu", original_type): + lora = lora_weights[b_key].mm(lora_weights[a_key]) * lora_scale + else: + lora = ( + lora_weights[b_key] + .to(torch.float32) + .mm(lora_weights[a_key].to(torch.float32)) + * lora_scale + ) + lora = lora.to(original_type) + + subset = get_w_subset(local_path, lora, shards, ci) + checkpoint[checkpoint_key] = checkpoint[checkpoint_key] + lora[ + subset + ].to(torch.bfloat16) + torch.save(checkpoint, checkpoint_path) + del checkpoint + gc.collect() + + +logging.basicConfig( + format="%(asctime)s %(message)s", + level=logging.DEBUG, + filename="logs/prepare_model.log", +) +torch.random.manual_seed(seed) + +prepare_model( + llama2_path=llama2_model_path, + frozen_path=frozen_model_path, + compute_dtype=compute_dtype, + lora_rank=lora_rank, + frozen_dtype=frozen_dtype, +) diff --git a/mac/slowllama/slowllama/.gitignore b/mac/slowllama/slowllama/.gitignore new file mode 100644 index 0000000..0a4859d --- /dev/null +++ b/mac/slowllama/slowllama/.gitignore @@ -0,0 +1,8 @@ +**/__pycache__/** +data/** +*.log +frozen/** +inputs/** +model/** +llama7b_serve/** +out/** \ No newline at end of file diff --git a/mac/slowllama/slowllama/LICENSE b/mac/slowllama/slowllama/LICENSE new file mode 100644 index 0000000..fd1950d --- /dev/null +++ b/mac/slowllama/slowllama/LICENSE @@ -0,0 +1,21 @@ +MIT License + +Copyright (c) 2023 Oleksandr Kuvshynov + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. diff --git a/mac/slowllama/slowllama/README.md b/mac/slowllama/slowllama/README.md new file mode 100644 index 0000000..d1aba1e --- /dev/null +++ b/mac/slowllama/slowllama/README.md @@ -0,0 +1,298 @@ +## slowllama + +Fine-tune Llama2 and CodeLLama models, including 70B/35B on Apple M1/M2 devices (for example, Macbook Air or Mac Mini) or consumer nVidia GPUs. + +slowllama is not using any quantization. Instead, it offloads parts of model to SSD or main memory on both forward/backward passes. In contrast with training large models from scratch (unattainable) or inference, where we are likely to care about interactivity, we can still get something finetuned if you let it run for a while. + +Current version is using LoRA to limit the updates to a smaller set of parameters. First version supported full finetuning as well, but I decided to remove it for now, more on that below. + +Finetuning is the only focus, there's nothing special done for inference, consider [llama.cpp](https://github.com/ggerganov/llama.cpp). + +For CUDA-specific experiments, see [report on a10](docs/a10.md). + +It is all very experimental, but even more so for CUDA. + +### Example + +Tests were done on Apple M1 with 16Gb memory and Apple M2 with 24Gb memory. + +In order to fine-tune llama2 model we need to: +1. Install dependencies: ```pip install torch sentencepiece numpy```. Optional: install ```pip install fewlines``` for [weight/gradient distribution logging](docs/lora_weights.md). +2. Clone [llama2](https://github.com/facebookresearch/llama) and follow instructions to download the models. The script will download tokenizer as well. ```tokenizer.model``` should be put into the same directory as llama model itself. Use [codellama](https://github.com/facebookresearch/codellama) for CodeLLama models. Example folder structure could look like: +``` +/parent/ + /slowllama/... # <- this repo + /llama-2-7b/... # <- put tokenizer.model here + /llama-2-13b/... # <- and here + /llama-2-70b/... # <- and here as well + /CodeLlama-34b-Python/... # and here +``` + +Let's start with a [tiny example](test_data/cubestat.txt). It is an intro to the description of another open-source project - [cubestat](https://github.com/okuvshynov/cubestat). Text is short enough to just be included as part of the prompt, but it's ok as an illustration and you can read it in seconds youself. As I just published that project recently, there's no way original llama would know anything about it. + +Asking base llama2-7b to complete the prompt _"Cubestat reports the following metrics: "_ results in _"1) the number of cubes in the system, 2) the number of cubes that are in the process of being created"_. + +First step is to transform the model to the sequential format more suitable for loading to/from storage block-by-block. + +``` +python prepare_model.py +``` + +The paths to the input and output models are configured in the conf files. There's a base file [conf.py](conf.py) and two files with some overrides [conf_fp16.py](conf_fp16.py) and [conf_fp32.py](conf_fp32.py). By default [prepare_model.py](prepare_model.py) uses fp16 config. Modify these files with the paths you have your models in. +The scripts below use the same configuration files as well. + +Now we can try not-finetuned llama2: +``` +python test_gen.py +``` + +Now let's finetune the 7b model. [finetune.py](finetune.py) is a very simple script which trains LoRA weights based on the plaintext data. There are some settings you could change here, like sequence length, batch size, learning rate, dropout rate, number of iterations. Current settings are pretty much a guess, change this if desired. Currently it uses AdamW optimizer. + +``` +python finetune.py +``` + +Here's train dataset loss: +``` +2023-09-10 22:05:35,569 backprop done, loss after forward pass = 2.9539270401000977 +2023-09-10 22:06:08,022 backprop done, loss after forward pass = 2.9073102474212646 +2023-09-10 22:06:40,223 backprop done, loss after forward pass = 2.7192320823669434 +2023-09-10 22:07:12,468 backprop done, loss after forward pass = 2.7223477363586426 +2023-09-10 22:07:44,626 backprop done, loss after forward pass = 2.5889995098114014 +2023-09-10 22:08:16,899 backprop done, loss after forward pass = 2.4459967613220215 +2023-09-10 22:08:49,072 backprop done, loss after forward pass = 2.3632657527923584 +2023-09-10 22:09:21,335 backprop done, loss after forward pass = 2.250361442565918 +2023-09-10 22:09:53,511 backprop done, loss after forward pass = 2.165428638458252 +2023-09-10 22:10:25,738 backprop done, loss after forward pass = 2.031874656677246 +2023-09-10 22:13:45,794 backprop done, loss after forward pass = 1.8926434516906738 +2023-09-10 22:14:18,049 backprop done, loss after forward pass = 1.7222942113876343 +2023-09-10 22:14:50,243 backprop done, loss after forward pass = 1.58726966381073 +2023-09-10 22:15:22,405 backprop done, loss after forward pass = 1.4983913898468018 +2023-09-10 22:15:54,598 backprop done, loss after forward pass = 1.296463131904602 +2023-09-10 22:16:26,909 backprop done, loss after forward pass = 1.3328818082809448 +2023-09-10 22:16:59,031 backprop done, loss after forward pass = 1.0978631973266602 +2023-09-10 22:17:31,200 backprop done, loss after forward pass = 1.018444538116455 +2023-09-10 22:18:03,406 backprop done, loss after forward pass = 0.8421685099601746 +2023-09-10 22:18:35,673 backprop done, loss after forward pass = 0.7168515920639038 +2023-09-10 22:21:55,482 backprop done, loss after forward pass = 0.7870235443115234 +``` + +I didn't add a validation set for this data, instead I just checked what would the fine-tuned model produce for the same prompt. + +At ~10 iteration we get the following reasonable output: _Cubestat reports the following metrics: 1. CPU usage, 2. Memory usage, 3. Disk usage_ + +At ~20 iteration another output is produced: + +_0 - Cubestat reports the following metrics: CPU utilization: Efficiency and Performance cores. Shows as percentage._ + +Maybe we were overfitting already at this point. + +Running completion with newly produced lora checkpoint can be done like this: + +``` +python test_gen.py ./out/state_dict_19.pth +``` + +### How does it work? +For all versions the process is roughly the same. + +First, we need to be able to load a model which requires more RAM than we have and save it back in sequential format. We create model instance with all large modules' weights offloaded to SSD - all of the transformer blocks, token embeddings and output linear layer. After that we [load model shards one by one](https://github.com/okuvshynov/slowllama/blob/main/llama2_loader.py#L69), for each shard iterate over all modules, update corresponding subset of its weights and save it back. + +Doing forward path is easy - we just load modules when we need and pass the output forward. + +Backward pass is a little more tricky, in a way we have to run forward pass twice. The way it's [currently implemented](https://github.com/okuvshynov/slowllama/blob/main/llama2.py#L307) is: +1. Do a forward pass while also saving inputs to each offloaded block to the SSD. The goal of the first forward pass is to compute the final loss and cache inputs to each offloaded block. +2. Then, do a manual backward gradient propagation. We start from the last block, re-run each block once again (forward, to build autograd graph) with the same input we cached on step (1). After that we run backward pass within that block only, and pass the gradient for the input to the next (previous?) block. As we use LoRA, only LoRA gradients are being saved. LoRA weights are not offloaded to disk, always staying on RAM/GPU. Important: we also need to save and restore random number generation state before evaluating each offloaded module. During training we use dropout, and randomly switched off neurons should be the same on both forward passes. +3. After that we run optimizer step on LoRA weights and save them separately if needed. + +Original llama2 weights are in bfloat16, but mps backend doesn't support that type natively, so we do computation in float32 instead. + +Experimental version of slowllama which can be still found [here](https://github.com/okuvshynov/experiments/tree/5cf944cb1274e577d1e755e6ad1957190d286d9d/split_model) was capable of doing full finetuning and update all weights pretty much the same way. I've temporarily removed that feature to preserve the lifespan of SSDs, as frequent write operations can degrade performance over time. Reading from SSDs isn't an issue, but they do have a write limit. Limit is typically high enough for normal usage, but in the case of full finetunining we'll have to write ~150Gb per one iteration/weight update of 70B variant, assuming stateless optimizer and no gradient accumulation. With AdamW we'll have to save/update another 150Gb more of optimizer state per iteration. If, for example, we assume 1Pb of writes before SSD will start having issues, even 100 iterations of finetuning would incur significant cost/risk. + +### Experiments + +#### Llama2 7B finetune on M1 Mini (16Gb memory): + +![finetune on mac mini](static/finetune_m1_7b.png) + +Here we can see resource utilization for 1 full iteration on 7B model - forward and manual backward passes. Each column == 1 second. A few notes: +1. GPU is reasonably well utilized; +2. First forward pass has lower GPU utilization and spends more time on IO as we need to both read weights and write cached inputs/outputs +3. Backward (combined?) pass achieves very high GPU utilization, close to 100% +4. As we move along layers back and forth, right after each 'direction switch' we process layers in LIFO order. Thus in the beginning of both forward and backward pass we don't have to access disk, weights are being cached and we don't see disk reads. + +batch_size/seq_len - works ok with, say, 2048 seq_len and batch_size = 2. + +#### Llama2 70B finetune on M1 Mini (16Gb memory) +![finetune 70b model](static/llama2_70b_m1.png) + +The chart here has different granularity - each column is 30 seconds. Input data was also different - it is the readme file you are reading now. +I didn't have enough free space on disk to store both original weights (140Gb) + weights in sequential format we use (another 140Gb). In order to still be able to finetune this model, I stored original weights on much slower external SD card, as we need to read them only once. Weights in sequential format on fast internal SSD. +With batch size = 16 and sequence length = 128 it was taking ~25-30 min per iteration. + +As we can see, GPU utilization doesn't look that great - we might be able to benefit from prefetching next transformer block, assuming we have enough memory for storing 2 layers. Memory utilization peaked at around 80% of 16Gb. + +Loss over time: + +``` +2023-09-13 17:30:28,731 backprop done, loss after forward pass = 2.431253433227539 +2023-09-13 18:00:00,133 backprop done, loss after forward pass = 2.604712963104248 +2023-09-13 18:29:36,473 backprop done, loss after forward pass = 2.6277880668640137 +2023-09-13 19:00:40,463 backprop done, loss after forward pass = 2.408756971359253 +2023-09-13 19:29:55,974 backprop done, loss after forward pass = 2.6121537685394287 +2023-09-13 19:59:04,849 backprop done, loss after forward pass = 2.428431987762451 +2023-09-13 20:27:03,760 backprop done, loss after forward pass = 2.4040215015411377 +2023-09-13 20:55:56,969 backprop done, loss after forward pass = 2.158071279525757 +2023-09-13 21:25:04,615 backprop done, loss after forward pass = 2.3459620475769043 +2023-09-13 21:54:07,128 backprop done, loss after forward pass = 2.2933709621429443 +2023-09-13 23:18:57,588 backprop done, loss after forward pass = 2.273494243621826 +2023-09-13 23:48:05,310 backprop done, loss after forward pass = 2.4055371284484863 +2023-09-14 00:17:19,113 backprop done, loss after forward pass = 2.2604546546936035 +2023-09-14 00:46:31,872 backprop done, loss after forward pass = 2.552386522293091 +2023-09-14 01:15:45,731 backprop done, loss after forward pass = 2.297588586807251 +2023-09-14 01:44:51,640 backprop done, loss after forward pass = 2.1217401027679443 +2023-09-14 02:14:09,033 backprop done, loss after forward pass = 1.9815442562103271 +2023-09-14 02:43:09,114 backprop done, loss after forward pass = 2.020181179046631 +2023-09-14 03:12:17,966 backprop done, loss after forward pass = 2.0041542053222656 +2023-09-14 03:41:20,649 backprop done, loss after forward pass = 1.9396495819091797 +2023-09-14 05:06:31,414 backprop done, loss after forward pass = 2.1592249870300293 +2023-09-14 05:35:39,080 backprop done, loss after forward pass = 1.976989984512329 +2023-09-14 06:04:57,859 backprop done, loss after forward pass = 1.7638890743255615 +2023-09-14 06:34:06,953 backprop done, loss after forward pass = 1.9829202890396118 +2023-09-14 07:03:18,661 backprop done, loss after forward pass = 1.754631519317627 +2023-09-14 07:32:26,179 backprop done, loss after forward pass = 2.027863025665283 +2023-09-14 08:01:37,546 backprop done, loss after forward pass = 1.8579339981079102 +2023-09-14 08:30:41,689 backprop done, loss after forward pass = 1.7934837341308594 +2023-09-14 08:59:55,921 backprop done, loss after forward pass = 1.794022798538208 +2023-09-14 09:28:59,690 backprop done, loss after forward pass = 1.750269889831543 +2023-09-14 10:56:19,282 backprop done, loss after forward pass = 1.4310824871063232 +2023-09-14 11:25:28,462 backprop done, loss after forward pass = 1.6895856857299805 +2023-09-14 11:54:39,973 backprop done, loss after forward pass = 1.5074403285980225 +2023-09-14 12:23:42,604 backprop done, loss after forward pass = 1.6695624589920044 +2023-09-14 12:53:00,535 backprop done, loss after forward pass = 1.4220315217971802 +2023-09-14 13:22:15,685 backprop done, loss after forward pass = 1.5720497369766235 +2023-09-14 13:51:30,744 backprop done, loss after forward pass = 1.544579267501831 +2023-09-14 14:20:44,482 backprop done, loss after forward pass = 1.2813694477081299 +2023-09-14 14:50:03,384 backprop done, loss after forward pass = 1.2990479469299316 +2023-09-14 15:19:09,620 backprop done, loss after forward pass = 1.0500637292861938 +``` + +We used prompt 'slowllama is a ', and here you can see the completions: +* before any weight update: _slowllama is a 24 year old (DOB: December 25, 1994) pure-blood witch_ +* after 10 iterations: _slowllama is a 24 year old (DOB: December 25, 1994) pure-blood witch_ +* after 20 iterations: _slowllama is a 70B model trained on the same data as llama.70b, but with a different training setup._ +* after 30 iterations: _slowllama is a 2022 fork of llama2, which is a 2021 fork of llama, which is a 2020 fork_ +* after 40 iterations: _slowllama is a 2-stage finetuning implementation for llama2._ + +Current setup is probably too slow for 70B model finetuning on old mac mini M1. It would be interesting to try it on more recent hardware (say, M2 Max / M2 Pro), implement prefetch/async save and see how it's going to work. + +**Float16 update:** + +Using Fp16 both for storing frozen weights and compute on MPS devices considerably improves memory requirements and time for iteration. A few notes: +* update torch to 2.1.0, otherwise mps might try to use apple neural engine for fp16 compute and it's not working quite well yet (see https://github.com/pytorch/pytorch/issues/110975) +* time win comes from the fact that we don't have to transform each block from bf16 to fp32. + +Here you can see finetune 70B model with M1 mac mini where weights are stored in fp16 and compute is done in fp16 as well. Input size is fairly small - batch size = 16 and seq_len = 128. + +Forward pass with 100ms granularity +![finetune](static/finetune_fwd.png) + +Combined pass with 100ms granularity +![finetune](static/finetune_combined.png) + +GPU utilization is at ~89% for combined pass and ~78% for forward. Now prefetch and saving in different format might make a difference. + +### merging LoRA weights back + +In order to merge LoRA checkpoint back to the model in original format, we can do the following: + +``` +# confirm that old model is producing wrong output +python test_gen.py + +... +0 - Cubestat reports the following metrics: 1) the number of cubes in the system, 2) the number of cubes that are currently running, 3) the number of cubes that are currently stopped, 4) the number of cubes that are currently in the process of starting, + +# check what would be the output for finetuned model by passing path to checkpoint +python test_gen.py ./out/state_dict_18.pth + +... +0 - Cubestat reports the following metrics: + +CPU utilization - configurable per core ('expanded'), cluster of cores: Efficiency/Performance ('cluster') or both. Is shown as percentage. +GPU utilization per card/chip. Is shown in percentage. Works for Apple's M1/M2 SoC and nVidia GPUs. For nVidia GPU shows memory usage as well. +ANE (Apple's Neural Engine) power consumption..... + +# now run merge. we need to pass: +# - original model path +# - new path for new model +# - lora checkpoint path +# note that merge would first delete the output directory if it exists and copy over original weights there. +python merge_lora.py ../llama-2-13b ./out/state_dict_18.pth ../llama-2-13b-out + +# at this point ../llama-2-13b-out is merged can be used in exactly same way as original llama2 for further quantization, inference, etc. + + +# If we want to run inference within slowllama for testing, we need to run prepare_model.py again. +# update the llama2_model_path in conf.py to be ../llama-2-13b-out/ and in conf_16.py frozen_model_path = '../llama13b_f16-out' + +python prepare_model.py + +# now run new model with no extra checkpoint, observe new output, same as in runtime-combined model: +python test_gen.py + +... +0 - Cubestat reports the following metrics: + +CPU utilization - configurable per core ('expanded'), cluster of cores: Efficiency/Performance ('cluster') or both. Is shown as percentage. +GPU utilization per card. Is shown in percentage. Works for Apple's M1/M2 SoC and nVidia GPUs. For nVidia GPU shows memory usage as well. +ANE (Apple's Neural Engine) power consumption..... + +``` + +### Project structure + +Just a few files with no dependencies other than torch, numpy and sentencepiece for tokenizer. + +1. [llama2.py](llama2.py) -- model definition and manual backprop implementation. It's based on model.py from [llama2.c](https://github.com/karpathy/llama2.c), also MIT licenced. +2. [finetune.py](finetune.py) - script which does the training +3. [llama2_loader.py](llama2_loader.py) - manual loading/saving of large llama2 models +4. [utils.py](utils.py) - small utility functions, including saving/loading random generator state for different devices. +5. [test_gen.py](test_gen.py) - greedily complete the prompt. Takes base weights + trained LoRA weights as input. Useful for sanity checks. +6. [blackbox.py](blackbox.py) - module wrapper which offloads the module to disk or main memory. +7. [plot_lora.py](plot_lora.py) - logging utility, writes LoRA weights and gradient distribution to [logfile](docs/lora_weights.md). Requires [fewlines](https://github.com/okuvshynov/fewlines). If fewlines is not installed, does nothing. +8. [merge_lora.py](merge_lora.py) - merge original weights + lora weights in the original format which can then be used directly. +9. [prepare_model.py](prepare_model.py) - script to transform sharded model to sequentially split model. + +### TODO: + +``` +[ ] masking +[ ] optimizations -- focus on memory usage + [ ] consider splitting transformer block into attention/ff + [ ] check if loading state dict to the same block instance would avoid the reallocation + [ ] microopt - no need to compute gradient for some of the leaf parts +[ ] more generic train routine + [ ] pause/resume from LoRA snapshot + [ ] do not create LoRA layers on prepare, only on finetune? +[ ] optimizations - prefetch the next layer/input, save asyncronously, etc; +[ ] gradient accumulation +[ ] plot something like memory requirement for (batch_size , seq_len) +[ ] combined RAM/disk offload - 200Gb RAM is rarity. +[ ] tests, cleanup and comments; +[ ] progress tracking for everything; +[ ] quantization beyond 16 bit? +[ ] configurable weight tying; +[ ] double check RNG state correctness. +``` + +### References +* [llama2](https://github.com/facebookresearch/llama) +* [llama.cpp](https://github.com/ggerganov/llama.cpp) +* [llama2.c](https://github.com/karpathy/llama2.c) +* [cubestat](https://github.com/okuvshynov/cubestat) +* [LoRA](https://arxiv.org/abs/2106.09685) + +### Contact + +{github handle} @ gmail.com diff --git a/mac/slowllama/slowllama/blackbox.py b/mac/slowllama/slowllama/blackbox.py new file mode 100644 index 0000000..a2d5280 --- /dev/null +++ b/mac/slowllama/slowllama/blackbox.py @@ -0,0 +1,60 @@ +import os + +import torch + +from utils import device_map, next_id, device_supports_dtype +from model_config import ModelArgs + +class BlackboxDisk(torch.nn.Module): + def __init__(self, module, args: ModelArgs): + super().__init__() + self.module_id = next_id() + self.input_id = next_id() + self.compute_dtype = args.compute_dtype + self.served_model_path = args.served_model_path + self.cached_data_path = args.cached_data_path + # TODO: can we deduce this from the data itself + self.frozen_dtype = args.frozen_dtype + if args.init_frozen: + torch.save(module.to('cpu').to(self.frozen_dtype), self.frozen_path()) + + def frozen_path(self): + folder = os.path.join(self.served_model_path, 'frozen') + if not os.path.exists(folder): + os.makedirs(folder) + return os.path.join(folder, f'block_{self.module_id}.pt') + + def input_path(self): + folder = os.path.join(self.cached_data_path, 'inputs') + if not os.path.exists(folder): + os.makedirs(folder) + return f'{folder}/saved_{self.input_id}.pt' + + def loaded_inner(self): + return torch.load(self.frozen_path(), map_location='cpu') + + def load(self, device): + if device_supports_dtype(device, self.frozen_dtype): + return torch.load(self.frozen_path(), map_location=device_map(device)).to(self.compute_dtype) + else: + res = torch.load(self.frozen_path(), map_location='cpu') + return res.to(self.compute_dtype).to(device_map(device)) + + def save(self, module): + torch.save(module.to('cpu').to(self.frozen_dtype), self.frozen_path()) + + def load_input(self, device): + return torch.load(self.input_path(), map_location=torch.device(device_map(device))) + + def forward(self, input, *args): + torch.save(input, self.input_path()) + device = device_map(input.device) + module = self.load(device) + + if not self.training: + module.eval() + + # we offload model immediately anyway. + # no need to have gradient here ever. + with torch.no_grad(): + return module(input, *args) \ No newline at end of file diff --git a/mac/slowllama/slowllama/chat.py b/mac/slowllama/slowllama/chat.py new file mode 100644 index 0000000..05431b5 --- /dev/null +++ b/mac/slowllama/slowllama/chat.py @@ -0,0 +1,29 @@ +import logging +import torch +import sys +import os + +from llama2_loader import load_frozen +from utils import Tokenizer, greedy_gen2 +from conf_fp16 import * + +logging.basicConfig(format='%(asctime)s %(message)s', level=logging.WARN) + +lora_weights = sys.argv[1] if len(sys.argv) > 1 else None + +tokenizer_path = os.path.join(frozen_model_path, 'tokenizer.model') +tokenizer = Tokenizer(tokenizer_path) + +model = load_frozen(frozen_model_path, dropout=0.0, lora_rank=4, frozen_dtype=frozen_dtype, compute_dtype=compute_dtype).to(device) +if lora_weights is not None: + logging.debug(model.load_state_dict(torch.load(lora_weights), strict=False)) + +print(f'Model {frozen_model_path} loaded') + +while True: + prompt = input("> ") + while True: + for next in greedy_gen2(model, tokenizer, device, prompt, max_new_tokens=100): + sys.stdout.write(next) + sys.stdout.flush() + diff --git a/mac/slowllama/slowllama/conf.py b/mac/slowllama/slowllama/conf.py new file mode 100644 index 0000000..44906f2 --- /dev/null +++ b/mac/slowllama/slowllama/conf.py @@ -0,0 +1,55 @@ +import logging + +# which device to use for finetuning +# 'cpu', 'mps' (for Apple devices) or 'cuda' +device = 'mps' + +# random seed to use. Makes runs reproducible. +seed = 54321 + +# learning rate +lr = 1e-4 + +# logging gradient and weight distribution to log file +# useful for debugging, but makes more +log_lora_grad = False +log_lora_weight = False + +# how wide would LoRA layers be? (N x lora_rank) and (lora_rank x M). +# Larger number - larger layer - more capacity. +lora_rank = 4 + +log_level = logging.DEBUG + +# training settings + +# total number of iterations to run. No microbatching so far +iters = 20 + +# how long should be the sequence to train on? +# we pick seq_len tokens and try to predict token [seq_len + 1] +seq_len = 128 + +# how large should be the batch size? +batch_size = 16 + +# current script doesn't have validation set at all. +# instead, we run prompt completion every eval_period iterations +# and check how the completion look like +eval_before_training = False +eval_period = 20 + +# how many tokens to generate for such test completion +gen_tokens = 32 +# what prompt to use for test completion +prompt = 'Cubestat reports the following metrics: ' + +# where to save LoRA snapshots +snapshots_path = 'out' + +# plaintext input file which will be tokenized and used for training +finetune_file = './test_data/cubestat.txt' + +# which model to use - path to raw model +llama2_model_path = '../llama-2-13b' +#llama2_model_path = '../llama-2-13b-out' diff --git a/mac/slowllama/slowllama/conf_fp16.py b/mac/slowllama/slowllama/conf_fp16.py new file mode 100644 index 0000000..58e9178 --- /dev/null +++ b/mac/slowllama/slowllama/conf_fp16.py @@ -0,0 +1,9 @@ +import torch +from conf import * + +adamw_eps = 1e-4 +compute_dtype = torch.float16 +frozen_dtype = torch.float16 + +frozen_model_path = '../llama13b_f16' +#frozen_model_path = '../llama13b_f16-out' diff --git a/mac/slowllama/slowllama/conf_fp32.py b/mac/slowllama/slowllama/conf_fp32.py new file mode 100644 index 0000000..12cfb6b --- /dev/null +++ b/mac/slowllama/slowllama/conf_fp32.py @@ -0,0 +1,8 @@ +import torch +from conf import * + +adamw_eps = 1e-8 +compute_dtype = torch.float32 +frozen_dtype = torch.bfloat16 + +frozen_model_path = '../llama7b' \ No newline at end of file diff --git a/mac/slowllama/slowllama/docs/a10.md b/mac/slowllama/slowllama/docs/a10.md new file mode 100644 index 0000000..65e5384 --- /dev/null +++ b/mac/slowllama/slowllama/docs/a10.md @@ -0,0 +1,64 @@ +# Testing/notes for CUDA implementation + +Current version is tested the following instance config: +1. A10 GPU, 24Gb +2. 200 Gb RAM +3. 30 core intel cpu +4. 1.4 Tb SSD drive + +Running finetune for 7B llama works reasonably fast, but GPU utilization is bad - we can do much better. + +![finetune a10](static/finetune_a10_7b.png) + +Several immediate observations here: +1. one CPU core is 100% utilized. What exactly is it doing, moving data around, supposedly? +2. no disk reads are happening - we most likely just serve all files from cache. +3. each burst of writes is a forward pass - we save inputs. GPU util is especially bad there. +4. On backward/combined pass GPU utilization is slightly better but not much. +5. The time before first forward pass is generation - we use batch of size 1 here so utilization is very low but that's to be expected +6. GPU memory util is low as well - we can go with much larger batch size + +What should we do? +1. With this amount of memory we don't need to write to disk ever. We can just move layers back and forth between main memory and GPU +2. Optionally prefetch and save async. + +Let's check 7B model: + +offloading to disk: +``` +2023-09-05 22:11:56,099 starting iteration 5 +2023-09-05 22:12:16,246 starting iteration 6 +2023-09-05 22:12:36,387 starting iteration 7 +2023-09-05 22:12:56,433 starting iteration 8 +``` + +Each iteration takes ~20s + +After offloading the layers to RAM rather than disk, we get considerable speedup: +``` +2023-09-05 22:19:27,544 starting iteration 5 +2023-09-05 22:19:35,563 starting iteration 6 +2023-09-05 22:19:43,580 starting iteration 7 +2023-09-05 22:19:51,603 starting iteration 8 +``` + +Each iteration is ~8 seconds. + +For 70B model on disk: +``` +2023-09-06 00:08:59,143 starting iteration 5 +2023-09-06 00:10:41,738 starting iteration 6 +2023-09-06 00:12:24,215 starting iteration 7 +2023-09-06 00:14:04,903 starting iteration 8 +``` +~100s / iteration + +70B model on RAM: +``` +2023-09-05 23:14:31,709 starting iteration 5 +2023-09-05 23:15:46,593 starting iteration 6 +2023-09-05 23:17:01,593 starting iteration 7 +2023-09-05 23:18:16,730 starting iteration 8 +``` + +~75s / iteration diff --git a/mac/slowllama/slowllama/docs/lora_weights.md b/mac/slowllama/slowllama/docs/lora_weights.md new file mode 100644 index 0000000..8f3df4b --- /dev/null +++ b/mac/slowllama/slowllama/docs/lora_weights.md @@ -0,0 +1,416 @@ +Here's a log of how lora weights are changing during finetuning after first few iterations with AdamW. + +Produced with [fewlines](https://github.com/okuvshynov/fewlines). + +As we can see, after first step matrix B which was initialized with zeroes becomes bimodal - each weight makes a step either +lr or -lr. +After that it slowly creeps to the middle. + + +``` +=== WEIGHTS A === +2023-09-11 09:19:26,617 ~~~~~~~~~~~ -0.0156|~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~|0.0156 +2023-09-11 09:19:26,617 Q0.A|▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇| +2023-09-11 09:19:26,617 V0.A|▇▆▇▇▇▇▇▇▇▆▇▇▇▆▇▆▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▆▇▇▇▆▇▇▇▇▆▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇| +2023-09-11 09:19:26,617 Q1.A|▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▆▇▇▆▇▇▇▇▇▇▇▇▇▇▆▇▇▆▇▇▆▇▆▇▇▇▇▆▇▇▇▇▇| +2023-09-11 09:19:26,617 V1.A|▇▆▇▆▇▇▆▆▇▆▇▇▇▆▇▇▇▆▇▆▇▇▇▆▇▇▇▇▇▆▇▇▇▇▇▇▆▇▇▇▇▇▆▆▆▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇| +2023-09-11 09:19:26,617 Q2.A|▇▇▇▇▇▆▇▇▇▇▆▇▇▆▇▇▇▇▇▇▆▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇| +2023-09-11 09:19:26,617 V2.A|▆▇▆▆▇▇▇▇▇▇▇▆▇▇▇▆▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▆▇▇▇▆▇▇▇▇▇▇▆▇▇▇▇▆▇▇▇▇▇| +2023-09-11 09:19:26,617 Q3.A|▇▇▇▇▇▇▇▇▆▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▆▇▆▇▇▇▇▇▆▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▆▇▆▆| +2023-09-11 09:19:26,617 V3.A|▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▆▆▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▆▆▇| +2023-09-11 09:19:26,617 Q4.A|▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▆▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▆▇▇▇▇| +2023-09-11 09:19:26,617 V4.A|▇▇▇▇▇▇▇▇▇▇▇▇▆▇▆▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇| +2023-09-11 09:19:26,617 Q5.A|▆▇▆▇▇▇▇▇▆▆▇▇▆▇▇▇▆▇▇▇▆▇▇▆▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▆▇▇▆▆▇▆▇▆▇▇▇▇▇▇▆▇▇▆| +2023-09-11 09:19:26,617 V5.A|▆▆▇▇▆▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▆▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇| +2023-09-11 09:19:26,617 Q6.A|▇▆▇▆▇▆▆▇▇▇▇▆▇▇▆▇▇▇▇▇▇▇▆▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▆▆▆▇▇▆▆▆▇▇▆▇▇▆▇▇▇▇▇| +2023-09-11 09:19:26,617 V6.A|▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▆▇▆▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇| +2023-09-11 09:19:26,617 Q7.A|▆▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇| +2023-09-11 09:19:26,617 V7.A|▆▇▇▆▆▆▇▆▇▆▇▇▇▆▇▇▇▆▇▆▆▇▇▆▆▇▇▇▇▇▇▆▇▆▇▇▇▇▆▇▇▇▆▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▆| +2023-09-11 09:19:26,617 Q8.A|▇▇▆▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▆▇▇▇▇▆▇▇▆▆▆▆▇▇▆▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇| +2023-09-11 09:19:26,617 V8.A|▇▆▇▆▆▆▇▇▇▆▆▆▇▇▆▇▆▆▇▆▇▇▇▇▇▇▇▇▇▇▆▆▇▆▇▇▇▇▇▇▇▆▆▇▇▆▇▇▇▇▆▇▆▇▇▇▇▇▇▆| +2023-09-11 09:19:26,617 Q9.A|▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▆▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇| +2023-09-11 09:19:26,617 V9.A|▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇| +2023-09-11 09:19:26,617 Q10.A|▇▇▇▆▇▇▆▆▇▇▇▇▇▇▆▇▇▇▇▇▆▇▆▇▇▆▇▇▆▇▆▇▇▆▇▇▇▆▇▇▇▇▇▇▆▆▇▇▇▇▆▆▇▆▇▇▆▆▆▇| +2023-09-11 09:19:26,617 V10.A|▇▇▇▇▆▇▆▇▇▇▇▇▇▆▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▆▇▇▇▇▇▆▆▇▇▇▇▇▆▇▆▇▇▆▇▆▇▇▇▇▆▇▇| +2023-09-11 09:19:26,617 Q11.A|▇▇▇▇▆▆▇▇▇▇▇▆▇▆▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▆▇▇▇▇▇▇▇▆▆▇▇▇▆▇▇▆▇▇▇▇▇| +2023-09-11 09:19:26,617 V11.A|▇▆▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▆▇▇▇▇▇▆▆▇▆▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇| +2023-09-11 09:19:26,617 Q12.A|▇▆▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▆▇▆▆▆▆▇▇▆▇▇▇▆▇▇▆| +2023-09-11 09:19:26,617 V12.A|▆▇▆▇▇▇▆▇▇▇▇▆▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇| +2023-09-11 09:19:26,617 Q13.A|▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▆▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇| +2023-09-11 09:19:26,617 V13.A|▇▇▆▇▇▇▆▆▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▆▆▆▇▆▇▇▇▆▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇| +2023-09-11 09:19:26,617 Q14.A|▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▆▇▇▇▇▆▇▆▇▇▇▆▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▆▇▇▇| +2023-09-11 09:19:26,617 V14.A|▆▇▇▇▇▇▆▇▇▇▇▇▆▇▇▇▇▇▇▇▆▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▆▆▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▆| +2023-09-11 09:19:26,617 Q15.A|▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▆▇▇▆▇▇▆▇▇▇▇▇▇▇▇| +2023-09-11 09:19:26,617 V15.A|▆▇▇▇▆▇▆▆▆▆▇▆▆▇▆▇▇▆▇▆▇▆▇▆▆▆▆▇▆▇▆▆▆▇▇▇▆▆▇▇▆▆▇▇▆▆▇▇▇▆▆▇▇▆▇▇▇▆▇▆| +2023-09-11 09:19:26,617 Q16.A|▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▆▆▇▇▇▆▇▇▇▆▆▇▆▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▆| +2023-09-11 09:19:26,617 V16.A|▇▆▆▆▆▆▇▆▇▇▇▇▆▇▆▇▆▆▇▇▆▇▆▆▇▇▆▇▇▇▇▇▇▇▆▇▆▇▆▆▇▇▇▆▇▇▆▆▇▇▇▇▆▆▆▆▆▇▆▆| +2023-09-11 09:19:26,617 Q17.A|▆▇▇▇▇▆▇▇▇▆▇▇▇▇▇▇▇▇▇▇▆▇▆▇▇▇▇▇▇▇▇▆▇▇▇▆▇▆▆▇▇▇▆▇▇▇▇▆▇▇▇▇▆▇▆▇▆▇▇▇| +2023-09-11 09:19:26,617 V17.A|▇▇▆▆▆▇▇▇▇▇▇▆▇▇▇▆▇▆▇▆▇▇▇▆▇▆▇▆▆▆▆▆▆▇▆▆▆▆▇▆▇▇▆▇▆▇▆▆▇▇▇▇▇▇▆▇▇▇▇▆| +2023-09-11 09:19:26,617 Q18.A|▆▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▆▇▇▇▇▆▆▇▇▆▇▆▆▇▆▇▇▆▆▇▇▆▇▆▇▇▇▆▆▇▇▇▆▆▇▇▇▇▇▇| +2023-09-11 09:19:26,617 V18.A|▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▆▇▇▆▇▇▆▆▆▇▇▇▇▇▆▇▆▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▆▆▇▇▆▇▇▇▇▇▇▆| +2023-09-11 09:19:26,617 Q19.A|▆▆▇▆▇▇▇▇▇▇▇▆▇▇▇▆▇▇▇▆▇▆▇▆▇▇▇▇▇▇▇▇▇▇▆▆▇▇▆▇▇▆▆▆▇▇▇▆▆▇▇▆▇▆▇▆▆▆▆▆| +2023-09-11 09:19:26,617 V19.A|▇▇▇▆▆▆▇▆▇▇▆▆▇▆▇▆▇▆▇▆▆▆▇▆▆▇▇▆▆▇▇▇▆▆▇▆▇▆▇▆▆▆▆▇▇▇▆▇▆▆▆▆▇▆▆▇▆▇▆▆| +2023-09-11 09:19:26,617 Q20.A|▇▆▆▇▆▇▆▇▆▆▆▆▆▇▇▆▇▆▇▇▆▆▇▆▆▆▇▆▇▇▆▆▆▆▇▆▇▇▇▇▆▆▇▆▇▇▆▇▇▆▆▆▇▆▇▇▆▆▇▇| +2023-09-11 09:19:26,617 V20.A|▇▇▇▇▇▇▇▇▇▇▆▆▇▆▇▇▇▆▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇| +2023-09-11 09:19:26,617 Q21.A|▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▆▆▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▆▇▇▇▆▇| +2023-09-11 09:19:26,617 V21.A|▇▇▇▇▇▆▆▇▇▇▇▇▇▆▇▇▆▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▆▇▇▇▇▇| +2023-09-11 09:19:26,617 Q22.A|▆▆▇▆▇▇▆▆▆▇▇▇▆▆▆▆▆▇▆▆▆▆▆▆▆▇▇▆▆▆▆▆▇▆▇▆▇▆▇▆▆▆▇▆▆▆▆▇▆▆▇▇▆▆▇▇▆▆▆▇| +2023-09-11 09:19:26,617 V22.A|▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▆▆▇▇▇▇▆▇▇▇▇▇▇▇▇▇▆▇▆▆▆▇▇▇▇▇▇▆▇▇▇▆▇▇▇▇▆▇| +2023-09-11 09:19:26,617 Q23.A|▆▇▇▇▇▆▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇| +2023-09-11 09:19:26,618 V23.A|▆▇▇▆▇▆▆▇▆▇▇▆▇▆▆▇▇▇▇▆▆▆▆▇▇▇▇▇▇▇▇▇▇▆▆▆▇▇▆▆▇▇▆▆▇▆▆▆▇▇▇▇▇▆▇▆▇▇▇▆| +2023-09-11 09:19:26,618 Q24.A|▇▇▇▆▆▇▇▇▇▇▇▆▇▇▇▇▇▇▆▇▇▆▇▇▇▇▆▇▆▇▇▆▆▇▇▇▆▇▇▇▆▇▇▇▇▇▇▇▇▇▇▆▆▇▇▇▇▆▆▇| +2023-09-11 09:19:26,618 V24.A|▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▆▆▆▆▇▆▇▇▇▇▆▆▇▇▇▆▇▇▇▇▇▇▆▇▇▇▇▆▇▇▇| +2023-09-11 09:19:26,618 Q25.A|▇▇▇▇▆▇▇▇▆▇▆▇▇▆▇▇▆▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▆▇▇▇▇▇▇▇▆▇| +2023-09-11 09:19:26,618 V25.A|▇▇▇▇▇▆▇▇▇▇▇▇▇▆▆▇▆▇▇▇▆▇▇▇▇▇▆▇▇▇▆▇▇▆▇▆▆▇▇▆▇▇▆▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇| +2023-09-11 09:19:26,618 Q26.A|▇▇▇▇▇▆▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇| +2023-09-11 09:19:26,618 V26.A|▇▆▆▇▇▇▇▇▆▇▆▆▆▆▇▇▇▇▇▇▆▇▇▇▆▆▇▆▇▇▇▇▇▇▆▇▇▆▇▇▆▇▇▇▇▆▇▇▆▇▇▆▇▇▆▇▇▇▇▇| +2023-09-11 09:19:26,618 Q27.A|▇▇▆▇▇▆▇▇▆▇▇▇▇▆▆▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▆▆▆▇▇▆▆▇▇▇▇▇▆▇▇▆▇▆▇▇▇▇▇▇▇▆▇▇▆| +2023-09-11 09:19:26,618 V27.A|▇▇▇▇▆▇▇▇▆▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▆▇▇| +2023-09-11 09:19:26,618 Q28.A|▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆| +2023-09-11 09:19:26,618 V28.A|▆▇▇▇▇▆▇▇▆▇▇▇▆▇▇▆▇▇▆▇▇▇▆▇▆▆▇▇▇▆▇▇▆▇▆▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▆▇▆▇▇▇▇▇▇▇| +2023-09-11 09:19:26,618 Q29.A|▆▇▇▇▇▇▆▇▇▆▇▇▇▇▆▇▆▆▇▇▆▆▇▇▆▆▆▇▇▆▇▆▆▇▇▇▆▇▆▇▇▇▇▇▆▇▆▇▇▇▆▇▇▇▇▇▇▇▇▆| +2023-09-11 09:19:26,618 V29.A|▆▆▇▆▇▆▇▆▇▇▆▇▇▇▇▇▇▆▇▇▇▇▆▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▆▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇| +2023-09-11 09:19:26,618 Q30.A|▆▇▇▇▇▇▇▇▆▇▆▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇| +2023-09-11 09:19:26,618 V30.A|▆▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇| +2023-09-11 09:19:26,618 Q31.A|▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▆▇▇▇▇▇▆▇▇▇▇▇▆▇▇| +2023-09-11 09:19:26,618 V31.A|▆▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▆▇▆▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▆▇▇| +2023-09-11 09:19:26,618 +=== WEIGHTS B === +2023-09-11 09:19:27,099 ~~~~~~~~~~~ -0.0001|~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~|0.0001 +2023-09-11 09:19:27,100 Q0.B|▇ ▇| +2023-09-11 09:19:27,100 V0.B|▇ ▇| +2023-09-11 09:19:27,100 Q1.B|▇ ▇| +2023-09-11 09:19:27,100 V1.B|▇ ▇| +2023-09-11 09:19:27,100 Q2.B|▇ ▇| +2023-09-11 09:19:27,100 V2.B|▇ ▇| +2023-09-11 09:19:27,100 Q3.B|▇ ▇| +2023-09-11 09:19:27,100 V3.B|▇ ▇| +2023-09-11 09:19:27,100 Q4.B|▇ ▇| +2023-09-11 09:19:27,100 V4.B|▇ ▇| +2023-09-11 09:19:27,100 Q5.B|▇ ▇| +2023-09-11 09:19:27,100 V5.B|▇ ▇| +2023-09-11 09:19:27,100 Q6.B|▇ ▇| +2023-09-11 09:19:27,100 V6.B|▇ ▇| +2023-09-11 09:19:27,100 Q7.B|▇ ▇| +2023-09-11 09:19:27,100 V7.B|▇ ▇| +2023-09-11 09:19:27,100 Q8.B|▇ ▇| +2023-09-11 09:19:27,100 V8.B|▇ ▇| +2023-09-11 09:19:27,100 Q9.B|▇ ▇| +2023-09-11 09:19:27,100 V9.B|▇ ▇| +2023-09-11 09:19:27,100 Q10.B|▇ ▇| +2023-09-11 09:19:27,100 V10.B|▇ ▇| +2023-09-11 09:19:27,100 Q11.B|▇ ▇| +2023-09-11 09:19:27,100 V11.B|▇ ▇| +2023-09-11 09:19:27,100 Q12.B|▇ ▇| +2023-09-11 09:19:27,100 V12.B|▇ ▇| +2023-09-11 09:19:27,100 Q13.B|▇ ▇| +2023-09-11 09:19:27,100 V13.B|▇ ▇| +2023-09-11 09:19:27,100 Q14.B|▇ ▇| +2023-09-11 09:19:27,100 V14.B|▇ ▇| +2023-09-11 09:19:27,100 Q15.B|▇ ▇| +2023-09-11 09:19:27,100 V15.B|▇ ▇| +2023-09-11 09:19:27,100 Q16.B|▇ ▇| +2023-09-11 09:19:27,100 V16.B|▇ ▇| +2023-09-11 09:19:27,100 Q17.B|▇ ▇| +2023-09-11 09:19:27,100 V17.B|▇ ▇| +2023-09-11 09:19:27,100 Q18.B|▇ ▇| +2023-09-11 09:19:27,100 V18.B|▇ ▇| +2023-09-11 09:19:27,100 Q19.B|▇ ▇| +2023-09-11 09:19:27,100 V19.B|▇ ▇| +2023-09-11 09:19:27,100 Q20.B|▇ ▇| +2023-09-11 09:19:27,100 V20.B|▇ ▇| +2023-09-11 09:19:27,100 Q21.B|▇ ▇| +2023-09-11 09:19:27,100 V21.B|▇ ▇| +2023-09-11 09:19:27,100 Q22.B|▇ ▇| +2023-09-11 09:19:27,100 V22.B|▇ ▇| +2023-09-11 09:19:27,100 Q23.B|▇ ▇| +2023-09-11 09:19:27,100 V23.B|▇ ▇| +2023-09-11 09:19:27,100 Q24.B|▇ ▇| +2023-09-11 09:19:27,100 V24.B|▇ ▇| +2023-09-11 09:19:27,100 Q25.B|▇ ▇| +2023-09-11 09:19:27,101 V25.B|▇ ▇| +2023-09-11 09:19:27,101 Q26.B|▇ ▇| +2023-09-11 09:19:27,101 V26.B|▇ ▇| +2023-09-11 09:19:27,101 Q27.B|▇ ▇| +2023-09-11 09:19:27,101 V27.B|▇ ▇| +2023-09-11 09:19:27,101 Q28.B|▇ ▇| +2023-09-11 09:19:27,101 V28.B|▇ ▇| +2023-09-11 09:19:27,101 Q29.B|▇ ▇| +2023-09-11 09:19:27,101 V29.B|▇ ▇| +2023-09-11 09:19:27,101 Q30.B|▇ ▇| +2023-09-11 09:19:27,101 V30.B|▇ ▇| +2023-09-11 09:19:27,101 Q31.B|▇ ▇| +2023-09-11 09:19:27,101 V31.B|▇ ▇| +2023-09-11 09:19:27,119 backprop done, loss after forward pass = 2.9539270401000977 +2023-09-11 09:19:27,119 starting iteration 1 +2023-09-11 09:19:48,372 +=== WEIGHTS A === +2023-09-11 09:19:48,840 ~~~~~~~~~~~ -0.0157|~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~|0.0157 +2023-09-11 09:19:48,841 Q0.A|▆▇▇▇▇▇▇▇▇▇▇▇▇▆▇▆▇▇▆▇▇▇▇▆▇▇▇▇▇▇▆▇▇▆▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▆| +2023-09-11 09:19:48,841 V0.A|▆▆▇▇▇▇▇▇▆▆▆▇▇▆▆▆▇▆▆▇▇▆▇▆▇▇▆▇▇▇▆▆▇▆▆▇▇▆▇▇▇▆▆▇▇▆▇▇▇▆▇▇▇▇▇▇▇▇▇▅| +2023-09-11 09:19:48,841 Q1.A|▆▇▇▇▇▇▇▇▇▇▆▇▇▇▇▆▇▇▇▆▇▇▇▇▇▆▇▆▇▆▇▇▇▇▇▇▇▇▇▆▇▆▇▇▇▇▇▆▇▆▇▇▇▇▆▇▇▇▇▆| +2023-09-11 09:19:48,841 V1.A|▆▆▇▆▇▇▆▇▇▆▇▇▇▆▇▇▆▇▇▆▇▇▇▆▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▆▇▇▆▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆| +2023-09-11 09:19:48,841 Q2.A|▆▇▇▇▇▆▇▇▇▇▆▇▆▆▇▇▇▇▇▇▆▇▇▇▇▆▇▇▆▇▇▇▇▆▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▆| +2023-09-11 09:19:48,841 V2.A|▅▇▆▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆| +2023-09-11 09:19:48,841 Q3.A|▆▇▇▆▇▆▇▇▆▇▇▇▆▇▇▇▆▇▇▇▇▆▇▇▇▆▇▇▇▇▇▆▇▆▇▇▇▆▇▆▇▇▇▇▇▇▆▇▆▇▇▇▆▇▇▇▆▇▆▅| +2023-09-11 09:19:48,841 V3.A|▆▇▇▇▇▇▇▇▇▆▇▇▆▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▆▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▆▇▆▆| +2023-09-11 09:19:48,841 Q4.A|▆▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▆▇▇▆▇▆▇▇▆▇▇▆▇▆▆▇▆▇▇▇▇▇▇▆▇▇▇▆▆| +2023-09-11 09:19:48,841 V4.A|▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▆| +2023-09-11 09:19:48,841 Q5.A|▆▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▆▇▇▅| +2023-09-11 09:19:48,841 V5.A|▅▆▇▇▆▇▆▆▇▆▇▇▆▇▇▇▆▇▇▇▇▆▇▇▆▇▆▇▇▇▆▇▇▇▇▇▆▇▆▆▆▆▆▇▇▆▆▇▇▆▇▇▇▇▇▇▇▇▇▆| +2023-09-11 09:19:48,841 Q6.A|▆▆▇▇▇▆▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▆▆▇▇▇▆▇▇▇▇▇▇▇▆| +2023-09-11 09:19:48,841 V6.A|▅▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▆▆▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▆▇▇▇▆| +2023-09-11 09:19:48,841 Q7.A|▅▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▆▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▆▇▇▇▇▇▇▆| +2023-09-11 09:19:48,841 V7.A|▆▇▇▆▇▆▇▇▇▇▇▇▇▆▇▇▇▇▇▆▇▆▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▅| +2023-09-11 09:19:48,841 Q8.A|▆▇▆▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▆▇▆▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▆▇▇▆| +2023-09-11 09:19:48,841 V8.A|▆▆▇▆▆▆▇▇▇▆▆▆▇▇▇▇▆▆▇▆▇▇▇▆▇▇▇▇▇▇▆▆▇▆▇▇▇▇▇▇▆▇▆▇▇▆▇▇▇▆▆▇▆▇▇▆▇▇▇▅| +2023-09-11 09:19:48,841 Q9.A|▆▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆| +2023-09-11 09:19:48,841 V9.A|▆▇▇▆▇▇▇▆▇▇▇▆▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▆▆▇▇▆▇▇▇▆▇▇▇▇▇▆▇▇▇▆▇▇▇▇▆▇▇▆| +2023-09-11 09:19:48,841 Q10.A|▆▇▇▆▆▆▇▆▇▇▇▇▆▇▇▇▇▇▇▇▆▇▆▇▇▆▇▇▆▇▆▇▇▆▇▇▇▆▆▇▇▇▇▇▆▆▇▇▇▇▆▆▇▆▇▇▆▆▆▆| +2023-09-11 09:19:48,841 V10.A|▆▇▇▇▆▇▆▇▇▇▇▇▇▇▆▆▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▆▆▇▇▇▇▇▆▇▆▇▇▆▇▇▇▇▇▇▇▇▆| +2023-09-11 09:19:48,841 Q11.A|▆▇▇▇▇▇▇▇▇▇▇▆▇▇▆▇▇▇▇▇▇▇▆▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▆▇▇▇▇▇▇▇▇▆| +2023-09-11 09:19:48,841 V11.A|▆▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▆▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▆▇▇▆| +2023-09-11 09:19:48,841 Q12.A|▆▆▆▆▇▇▇▇▇▆▇▆▇▇▆▆▇▆▇▇▇▇▆▇▇▇▆▆▇▇▇▇▆▇▇▆▇▇▆▇▇▆▇▇▆▇▆▆▆▆▆▇▆▆▇▆▇▆▇▅| +2023-09-11 09:19:48,841 V12.A|▅▇▇▇▇▇▇▆▇▇▇▆▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆| +2023-09-11 09:19:48,841 Q13.A|▆▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▆▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▆▇▇▆▇▇▇▆▇▇▇▆▇▇▇▆▆| +2023-09-11 09:19:48,841 V13.A|▆▇▆▇▇▇▆▆▇▇▇▇▇▇▇▆▇▇▇▆▇▆▆▇▆▆▇▇▇▇▆▇▇▇▇▇▆▆▆▇▆▇▆▇▆▇▆▇▇▇▇▇▇▇▆▇▇▇▇▆| +2023-09-11 09:19:48,841 Q14.A|▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▆▆▇▇▇▇▆▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▆▇▇▇▆▇▇▆| +2023-09-11 09:19:48,841 V14.A|▅▆▇▇▆▇▆▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆| +2023-09-11 09:19:48,841 Q15.A|▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▆| +2023-09-11 09:19:48,841 V15.A|▅▆▇▇▆▇▆▆▆▆▆▇▇▆▆▇▇▆▇▆▇▆▆▆▆▆▇▇▆▆▆▆▆▆▇▇▆▆▇▇▆▆▆▆▆▆▆▇▇▆▆▇▇▆▇▇▆▆▇▅| +2023-09-11 09:19:48,841 Q16.A|▆▇▆▇▇▆▇▇▇▇▇▇▇▇▆▇▆▇▇▇▆▇▇▇▇▆▇▇▇▆▆▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▆▅| +2023-09-11 09:19:48,841 V16.A|▆▆▇▆▇▇▇▇▇▇▇▇▇▇▆▇▆▆▇▇▇▇▆▆▇▇▆▇▇▇▇▇▇▇▆▇▆▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▆▇▆▇▇▇▇▅| +2023-09-11 09:19:48,841 Q17.A|▅▇▇▆▆▆▇▇▆▇▇▇▇▇▇▇▇▇▇▇▆▇▆▇▆▇▇▇▆▇▇▆▇▇▇▆▇▆▆▇▇▇▆▇▆▇▇▆▇▇▇▇▆▇▆▇▆▇▇▆| +2023-09-11 09:19:48,841 V17.A|▆▇▆▆▆▇▇▇▇▇▆▆▇▇▇▆▇▇▆▆▇▇▇▆▇▆▇▆▆▇▆▆▇▆▆▆▇▆▇▆▇▇▆▇▆▇▆▇▇▇▇▆▇▆▇▇▇▇▇▅| +2023-09-11 09:19:48,841 Q18.A|▆▇▆▇▇▇▆▇▇▇▆▇▇▇▇▇▆▆▇▇▆▆▇▇▇▇▆▆▇▆▇▇▆▇▇▇▇▆▆▇▇▆▇▆▇▇▇▆▇▆▇▇▆▇▆▇▇▇▇▆| +2023-09-11 09:19:48,841 V18.A|▆▇▇▇▇▇▇▇▇▇▆▇▇▆▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▆▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▆▇▇▆▇▇▇▇▇▇▅| +2023-09-11 09:19:48,841 Q19.A|▅▆▆▇▇▇▇▇▇▇▇▆▇▇▇▆▆▇▆▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▆▆▇▆▆▆▇▆▆▆▇▇▇▆▆▆▇▇▇▆▇▆▇▆▆▅| +2023-09-11 09:19:48,841 V19.A|▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▆▇▇▇▇▆▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▆▆▇▇▇▇▇▇▆▇▆▇▆▇▇▇▇▇▆| +2023-09-11 09:19:48,841 Q20.A|▆▆▆▆▆▇▆▇▇▆▆▆▆▇▇▇▇▆▇▇▆▆▇▆▆▆▇▆▇▇▆▆▆▆▆▆▇▇▇▇▆▆▇▇▇▆▆▇▇▆▆▆▆▇▇▇▇▆▇▆| +2023-09-11 09:19:48,841 V20.A|▆▆▇▇▆▇▇▇▇▇▆▆▆▆▇▇▆▇▆▇▆▆▆▆▇▇▇▇▇▇▇▆▆▇▆▇▇▇▆▆▆▇▇▇▇▆▇▇▇▇▇▆▇▇▇▇▇▆▆▆| +2023-09-11 09:19:48,841 Q21.A|▆▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▆▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▆▇▇▇▇▇▇▇▇▆▇▇▆▇▆| +2023-09-11 09:19:48,841 V21.A|▆▆▇▆▇▆▆▆▇▇▇▇▇▆▆▇▆▆▇▆▇▇▇▆▆▇▇▇▇▆▆▇▇▆▇▇▆▆▇▇▇▇▇▇▇▇▇▇▆▇▆▇▆▆▆▇▇▇▇▅| +2023-09-11 09:19:48,841 Q22.A|▆▇▇▇▇▇▆▇▇▇▇▇▆▆▇▇▇▇▇▇▆▆▇▆▆▇▇▆▆▆▇▇▇▇▇▇▇▇▇▆▇▇▇▆▇▇▇▇▆▆▇▇▆▇▇▇▇▆▇▆| +2023-09-11 09:19:48,841 V22.A|▅▇▇▇▆▆▇▆▇▇▇▇▇▇▆▇▇▆▆▆▇▆▆▇▆▇▇▆▆▇▇▇▇▇▇▇▇▇▆▇▆▆▆▇▇▇▆▇▆▆▇▇▇▆▇▇▆▇▆▆| +2023-09-11 09:19:48,841 Q23.A|▆▇▇▇▇▆▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆| +2023-09-11 09:19:48,841 V23.A|▅▆▇▆▇▆▆▇▇▇▇▆▇▆▆▇▇▇▇▆▆▇▆▇▇▇▇▆▇▇▇▇▇▆▆▇▇▇▆▆▇▇▆▇▇▇▆▇▇▇▇▇▇▇▇▆▇▇▇▅| +2023-09-11 09:19:48,841 Q24.A|▆▇▇▆▆▇▇▇▇▇▇▇▇▇▆▇▇▇▆▇▇▆▇▇▇▇▆▇▆▇▇▆▆▆▇▇▆▇▆▇▇▆▇▇▇▇▇▇▇▆▇▆▆▇▇▇▇▆▇▆| +2023-09-11 09:19:48,841 V24.A|▆▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▆▆▆▇▇▇▇▇▇▇▆▇▆▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆| +2023-09-11 09:19:48,841 Q25.A|▆▇▇▇▆▇▇▆▆▇▆▇▇▆▆▇▆▆▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▆▇▇▇▇▇▆▇▇▆▇▇▇▇▇▆| +2023-09-11 09:19:48,841 V25.A|▆▇▆▇▇▆▇▇▆▇▆▇▇▆▆▇▆▇▆▆▇▇▇▇▇▇▆▇▆▇▇▆▇▆▇▆▆▇▇▆▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▆| +2023-09-11 09:19:48,841 Q26.A|▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▆▇▇▇▇▇▇▇▇▇▇▇▇▆| +2023-09-11 09:19:48,841 V26.A|▆▆▇▇▇▇▇▇▇▆▇▆▆▇▇▇▇▇▇▇▆▇▇▇▇▆▇▇▆▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▆▇▇▇▇▇▆▇▇▇▇▆| +2023-09-11 09:19:48,841 Q27.A|▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▅| +2023-09-11 09:19:48,841 V27.A|▆▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▆▇▇▇▆▇▇▇▇▇▇▇▆▇▇▇▇▇▇▆| +2023-09-11 09:19:48,841 Q28.A|▆▇▇▇▇▇▇▇▇▇▇▇▆▆▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▆▇▆▇▇▇▇▇▇▆▇▇▇▇▇▇▇▆▇▇▇▇▆▇▇▇▅| +2023-09-11 09:19:48,841 V28.A|▆▇▇▇▇▆▇▇▆▇▇▇▆▇▇▆▇▇▆▇▆▇▆▇▇▆▇▇▆▆▇▇▆▇▆▇▇▆▇▇▇▇▇▆▇▇▇▇▆▇▆▇▆▇▇▇▇▇▇▆| +2023-09-11 09:19:48,841 Q29.A|▆▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▆▆▇▇▇▇▆▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▅| +2023-09-11 09:19:48,841 V29.A|▆▆▇▆▇▇▇▆▆▇▆▇▇▇▇▇▇▆▇▆▇▇▆▇▇▇▇▇▆▇▇▆▇▇▇▇▇▇▆▇▇▇▆▇▆▇▇▇▇▇▆▇▇▇▇▇▆▇▇▆| +2023-09-11 09:19:48,841 Q30.A|▅▇▇▇▇▆▇▇▆▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▆| +2023-09-11 09:19:48,841 V30.A|▅▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▆▆▇▇▆▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▆| +2023-09-11 09:19:48,841 Q31.A|▅▇▇▇▆▆▇▇▇▇▇▆▇▆▇▆▇▆▇▇▇▆▇▇▇▆▇▇▆▇▇▆▇▇▇▇▇▆▆▆▇▆▇▇▆▆▇▇▇▆▇▆▇▇▆▇▇▆▇▆| +2023-09-11 09:19:48,842 V31.A|▅▆▇▆▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▆▇▆▆▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▆▆▇▇▇▇▇▇▇▆▇▆| +2023-09-11 09:19:48,842 +=== WEIGHTS B === +2023-09-11 09:19:49,326 ~~~~~~~~~~~ -0.0002|~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~|0.0002 +2023-09-11 09:19:49,326 Q0.B|▇▂▁▁ ▁▁▂▇| +2023-09-11 09:19:49,326 V0.B|▇▂▁▁ ▁▂▇| +2023-09-11 09:19:49,326 Q1.B|▇▂▁▁ ▁▁▂▇| +2023-09-11 09:19:49,326 V1.B|▇▂▁ ▁▂▇| +2023-09-11 09:19:49,326 Q2.B|▇▂▁▁ ▁▁▂▇| +2023-09-11 09:19:49,326 V2.B|▇▂▁ ▁▂▇| +2023-09-11 09:19:49,326 Q3.B|▇▂▁▁ ▁▁▂▇| +2023-09-11 09:19:49,326 V3.B|▇▂▁ ▁▂▇| +2023-09-11 09:19:49,326 Q4.B|▇▂▁▁ ▁▁▂▇| +2023-09-11 09:19:49,326 V4.B|▇▂▁ ▁▂▇| +2023-09-11 09:19:49,326 Q5.B|▇▂▁▁ ▁▁▂▇| +2023-09-11 09:19:49,326 V5.B|▇▂▁ ▁▂▇| +2023-09-11 09:19:49,326 Q6.B|▇▂▁ ▁▁▂▇| +2023-09-11 09:19:49,326 V6.B|▇▂▁ ▁▂▇| +2023-09-11 09:19:49,326 Q7.B|▇▂▁▁ ▁▁▂▇| +2023-09-11 09:19:49,326 V7.B|▇▂▁ ▁▁▇| +2023-09-11 09:19:49,326 Q8.B|▇▂▁ ▁▂▇| +2023-09-11 09:19:49,326 V8.B|▇▂▁ ▁▂▇| +2023-09-11 09:19:49,326 Q9.B|▇▂▁▁ ▁▂▇| +2023-09-11 09:19:49,326 V9.B|▇▂▁ ▁▁▇| +2023-09-11 09:19:49,326 Q10.B|▇▂▁ ▁▂▇| +2023-09-11 09:19:49,326 V10.B|▇▂▁ ▁▂▇| +2023-09-11 09:19:49,326 Q11.B|▇▂▁ ▁▂▇| +2023-09-11 09:19:49,326 V11.B|▇▂▁ ▁▂▇| +2023-09-11 09:19:49,326 Q12.B|▇▂▁ ▁▂▇| +2023-09-11 09:19:49,326 V12.B|▇▁▁ ▁▂▇| +2023-09-11 09:19:49,326 Q13.B|▇▂▁ ▁▂▇| +2023-09-11 09:19:49,326 V13.B|▇▁▁ ▁▁▇| +2023-09-11 09:19:49,326 Q14.B|▇▂▁ ▁▂▇| +2023-09-11 09:19:49,326 V14.B|▇▂▁ ▁▂▇| +2023-09-11 09:19:49,326 Q15.B|▇▂▁ ▁▂▇| +2023-09-11 09:19:49,326 V15.B|▇▁▁ ▁▁▇| +2023-09-11 09:19:49,326 Q16.B|▇▂▁ ▁▂▇| +2023-09-11 09:19:49,326 V16.B|▇▁▁ ▁▁▇| +2023-09-11 09:19:49,326 Q17.B|▇▂▁ ▁▂▇| +2023-09-11 09:19:49,326 V17.B|▇▁ ▁▇| +2023-09-11 09:19:49,326 Q18.B|▇▂▁ ▁▂▇| +2023-09-11 09:19:49,326 V18.B|▇▁▁ ▁▁▇| +2023-09-11 09:19:49,326 Q19.B|▇▂▁ ▁▂▇| +2023-09-11 09:19:49,326 V19.B|▇▁ ▁▇| +2023-09-11 09:19:49,326 Q20.B|▇▂▁ ▁▂▇| +2023-09-11 09:19:49,326 V20.B|▇▁▁ ▁▁▇| +2023-09-11 09:19:49,326 Q21.B|▇▂▁ ▁▂▇| +2023-09-11 09:19:49,326 V21.B|▇▁▁ ▁▁▇| +2023-09-11 09:19:49,326 Q22.B|▇▁▁ ▁▁▇| +2023-09-11 09:19:49,326 V22.B|▇▁▁ ▁▁▇| +2023-09-11 09:19:49,326 Q23.B|▇▂▁ ▁▂▇| +2023-09-11 09:19:49,326 V23.B|▇▁▁ ▁▁▇| +2023-09-11 09:19:49,327 Q24.B|▇▂▁ ▁▂▇| +2023-09-11 09:19:49,327 V24.B|▇▁ ▁▁▇| +2023-09-11 09:19:49,327 Q25.B|▇▂▁ ▁▂▇| +2023-09-11 09:19:49,327 V25.B|▇▁▁ ▁▁▇| +2023-09-11 09:19:49,327 Q26.B|▇▂▁ ▁▂▇| +2023-09-11 09:19:49,327 V26.B|▇▁▁ ▁▂▇| +2023-09-11 09:19:49,327 Q27.B|▇▂▁ ▁▂▇| +2023-09-11 09:19:49,327 V27.B|▇▁▁ ▁▂▇| +2023-09-11 09:19:49,327 Q28.B|▇▂▁ ▁▂▇| +2023-09-11 09:19:49,327 V28.B|▇▂▁ ▁▂▇| +2023-09-11 09:19:49,327 Q29.B|▇▂▁ ▁▂▇| +2023-09-11 09:19:49,327 V29.B|▇▂▁ ▁▁▇| +2023-09-11 09:19:49,327 Q30.B|▇▂▁ ▁▂▇| +2023-09-11 09:19:49,327 V30.B|▇▂▁ ▁▂▇| +2023-09-11 09:19:49,327 Q31.B|▇▂▁ ▁▂▇| +2023-09-11 09:19:49,327 V31.B|▇▂▁ ▁▂▇| +2023-09-11 09:19:49,345 backprop done, loss after forward pass = 2.9073104858398438 +2023-09-11 09:19:49,345 saving snapshot +2023-09-11 09:19:49,392 starting iteration 2 +2023-09-11 09:20:10,670 +=== WEIGHTS A === +2023-09-11 09:20:11,137 ~~~~~~~~~~~ -0.0158|~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~|0.0158 +2023-09-11 09:20:11,138 Q0.A|▅▇▇▇▇▇▆▇▇▆▆▇▇▆▇▆▇▇▆▇▆▇▇▆▇▆▇▇▇▇▆▇▇▆▇▆▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▆▇▅| +2023-09-11 09:20:11,138 V0.A|▅▇▇▇▆▇▇▇▇▇▆▇▇▆▆▆▇▆▇▇▇▇▇▇▇▇▇▇▇▇▆▆▇▆▆▇▇▇▇▇▇▇▆▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▅| +2023-09-11 09:20:11,138 Q1.A|▅▇▇▇▇▇▇▇▇▇▆▇▇▇▇▆▇▆▇▆▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▅| +2023-09-11 09:20:11,138 V1.A|▅▆▇▆▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▅| +2023-09-11 09:20:11,138 Q2.A|▅▇▇▇▇▆▇▇▇▇▆▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▅| +2023-09-11 09:20:11,138 V2.A|▄▇▆▇▇▇▇▆▇▇▇▆▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▅| +2023-09-11 09:20:11,138 Q3.A|▅▇▇▆▇▇▇▇▆▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▆▆▇▇▇▇▇▆▇▇▇▇▇▇▆▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▆▆▇▇▄| +2023-09-11 09:20:11,138 V3.A|▅▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▆▅| +2023-09-11 09:20:11,138 Q4.A|▅▇▇▇▆▆▇▇▆▇▇▆▇▆▇▆▇▆▆▇▇▆▇▆▇▇▇▇▇▇▇▆▆▇▆▇▆▇▇▆▇▇▆▇▆▆▇▆▆▇▆▇▇▆▆▆▆▇▆▅| +2023-09-11 09:20:11,138 V4.A|▅▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▆▇▇▆▇▇▇▆▆▇▇▇▇▇▇▇▇▇▇▆▆▇▇▇▇▇▇▇▇▇▇▇▇▆▅| +2023-09-11 09:20:11,138 Q5.A|▄▇▇▇▇▇▇▇▇▆▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▆▇▆▇▇▇▄| +2023-09-11 09:20:11,138 V5.A|▄▆▇▇▆▇▇▆▇▆▇▇▇▇▇▇▆▇▇▇▇▆▇▇▇▇▆▇▇▇▇▇▇▇▇▇▆▇▆▆▇▆▆▇▇▆▆▇▇▆▇▇▇▆▇▇▇▇▇▅| +2023-09-11 09:20:11,138 Q6.A|▅▆▇▇▇▇▇▆▇▇▇▇▇▇▆▇▇▇▇▇▇▇▆▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▆▆▇▇▇▇▇▇▆▇▇▇▇▅| +2023-09-11 09:20:11,138 V6.A|▄▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▆▇▇▆▇▆▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▆▇▇▇▇▅| +2023-09-11 09:20:11,138 Q7.A|▄▇▇▇▆▇▇▇▇▆▇▇▇▇▇▇▇▇▆▆▆▇▇▆▇▆▆▇▇▇▆▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▆▇▇▇▇▇▇▅| +2023-09-11 09:20:11,138 V7.A|▄▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▆▆▇▆▇▆▆▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▄| +2023-09-11 09:20:11,138 Q8.A|▅▆▇▇▇▇▆▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▆▆▇▆▆▆▆▇▆▆▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▆▇▇▄| +2023-09-11 09:20:11,138 V8.A|▅▇▇▇▆▇▇▇▇▇▇▆▇▇▇▇▆▆▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▆▇▇▇▇▇▇▆▆▇▇▇▇▆▇▇▇▅| +2023-09-11 09:20:11,138 Q9.A|▅▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▆▆▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▅| +2023-09-11 09:20:11,138 V9.A|▅▇▇▆▇▇▆▆▇▇▇▆▆▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▆▇▆▆▇▇▆▇▇▇▆▇▇▇▇▇▆▇▇▇▆▇▇▆▇▆▇▇▅| +2023-09-11 09:20:11,138 Q10.A|▅▇▇▇▆▆▆▆▇▆▇▇▆▇▇▇▇▇▇▆▆▇▆▇▇▆▇▇▆▇▆▇▇▇▇▆▇▆▆▆▇▇▇▆▆▆▇▆▇▇▆▆▆▆▇▇▆▆▆▅| +2023-09-11 09:20:11,138 V10.A|▅▇▇▇▆▇▆▇▇▆▇▇▇▇▆▆▇▇▇▇▇▇▇▇▇▇▆▇▆▇▇▇▆▆▇▇▇▇▆▆▆▇▆▇▆▆▇▇▆▆▆▇▆▇▇▇▇▆▇▅| +2023-09-11 09:20:11,138 Q11.A|▅▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▆▇▇▇▇▇▆▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▆▇▇▇▆▇▇▇▇▇▇▇▇▅| +2023-09-11 09:20:11,138 V11.A|▅▆▇▆▇▆▇▆▇▇▇▇▇▇▇▇▆▆▇▇▆▇▇▇▇▇▇▆▇▆▇▆▇▆▇▇▆▇▇▇▇▇▇▆▇▇▆▇▆▇▇▇▇▇▇▇▆▇▇▄| +2023-09-11 09:20:11,138 Q12.A|▅▇▇▆▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▆▆▆▇▇▇▇▇▇▆▇▇▇▅| +2023-09-11 09:20:11,138 V12.A|▄▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▅| +2023-09-11 09:20:11,138 Q13.A|▅▇▇▇▇▇▆▇▇▇▇▇▇▇▇▆▆▇▇▇▇▇▇▇▇▇▇▇▆▇▇▆▇▆▇▇▇▇▇▇▇▇▆▇▇▇▆▇▆▇▇▇▇▇▆▇▇▇▆▅| +2023-09-11 09:20:11,138 V13.A|▄▇▆▇▇▇▆▆▇▇▇▇▇▇▇▆▇▇▇▆▇▆▆▇▆▆▇▇▆▇▆▇▇▆▇▇▆▆▆▇▆▇▇▇▆▇▇▇▇▇▇▇▆▆▇▇▆▆▇▅| +2023-09-11 09:20:11,138 Q14.A|▅▆▆▇▇▆▇▇▆▆▇▇▇▆▇▇▇▇▆▆▆▇▆▇▆▆▆▆▆▇▇▆▆▆▆▆▆▇▆▇▆▇▆▆▇▇▇▇▆▆▆▆▆▇▆▆▆▇▇▄| +2023-09-11 09:20:11,138 V14.A|▄▆▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▄| +2023-09-11 09:20:11,138 Q15.A|▅▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▆▇▇▆▇▇▇▇▇▇▇▇▇▇▅| +2023-09-11 09:20:11,138 V15.A|▄▇▇▇▆▇▆▇▆▆▆▇▇▇▆▇▇▆▇▆▇▆▆▇▆▆▆▇▇▇▆▆▆▆▇▇▆▇▆▇▆▆▇▆▆▆▇▇▇▆▆▇▇▇▇▇▆▆▇▄| +2023-09-11 09:20:11,138 Q16.A|▅▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▆▆▇▇▆▇▇▇▇▆▇▇▇▆▇▇▆▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▆▇▇▆▄| +2023-09-11 09:20:11,138 V16.A|▅▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▆▇▆▇▇▇▆▇▇▇▆▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▅| +2023-09-11 09:20:11,138 Q17.A|▄▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▅| +2023-09-11 09:20:11,138 V17.A|▄▇▆▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▆▇▆▆▇▆▆▇▆▇▇▇▇▆▇▇▇▇▇▇▇▇▆▇▆▇▇▇▇▇▅| +2023-09-11 09:20:11,138 Q18.A|▄▇▆▇▆▇▆▇▇▇▆▇▇▇▇▆▇▇▇▇▇▆▇▇▇▆▇▆▆▆▇▇▆▇▇▇▇▆▆▇▇▆▇▆▇▇▆▆▇▆▇▇▇▆▆▇▇▇▇▅| +2023-09-11 09:20:11,138 V18.A|▄▇▇▆▇▆▇▇▇▇▇▇▆▆▇▆▇▆▆▇▇▇▆▆▆▇▇▇▇▆▇▆▇▇▆▇▇▇▇▆▇▇▇▆▇▇▆▇▆▆▇▇▆▇▇▆▇▆▆▄| +2023-09-11 09:20:11,138 Q19.A|▄▇▆▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▆▆▇▇▇▇▆▇▆▇▇▆▇▇▆▇▆▆▄| +2023-09-11 09:20:11,138 V19.A|▅▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▅| +2023-09-11 09:20:11,138 Q20.A|▅▇▆▇▇▇▆▇▇▇▆▆▆▇▇▇▇▇▇▇▇▆▇▇▆▇▇▆▇▇▇▆▆▆▇▇▇▇▇▇▆▇▇▇▇▆▇▇▇▇▆▇▇▇▇▇▇▇▇▅| +2023-09-11 09:20:11,138 V20.A|▄▇▆▇▆▇▆▇▆▇▆▆▆▆▇▇▆▇▆▇▆▆▆▆▇▇▇▇▇▇▇▆▇▇▆▆▇▇▇▆▆▇▇▇▇▆▇▇▇▇▇▆▇▇▇▇▇▆▆▅| +2023-09-11 09:20:11,138 Q21.A|▅▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▆▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▆▇▅| +2023-09-11 09:20:11,138 V21.A|▄▇▇▇▇▆▆▇▇▆▇▇▇▇▆▇▆▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▆▆▇▇▇▇▇▄| +2023-09-11 09:20:11,138 Q22.A|▅▇▇▇▇▇▆▇▇▇▇▇▆▆▇▇▇▇▇▇▆▆▇▆▆▇▇▇▆▆▇▇▇▆▇▇▇▇▇▆▇▇▇▆▇▆▇▇▇▆▇▇▇▇▇▇▇▆▇▅| +2023-09-11 09:20:11,138 V22.A|▅▇▇▇▆▇▆▇▇▇▇▇▇▇▇▇▇▇▆▆▇▆▇▇▆▇▆▇▆▇▇▇▆▇▇▇▇▇▆▇▆▆▇▇▇▇▆▆▇▆▇▇▇▆▇▇▇▇▆▅| +2023-09-11 09:20:11,138 Q23.A|▅▆▇▇▇▆▆▆▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▅| +2023-09-11 09:20:11,138 V23.A|▅▇▇▇▇▇▆▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▆▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▅| +2023-09-11 09:20:11,138 Q24.A|▅▇▇▆▆▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▆▇▇▇▇▆▇▇▇▇▆▆▇▇▇▇▇▆▇▇▆▇▇▇▇▇▇▇▆▇▆▆▇▇▇▆▆▇▅| +2023-09-11 09:20:11,138 V24.A|▅▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▆▆▆▆▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▅| +2023-09-11 09:20:11,138 Q25.A|▅▇▇▇▆▇▇▆▇▇▆▇▇▆▆▆▇▆▇▇▇▆▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▆▇▇▆▇▇▇▇▇▆▇▇▆▇▇▇▇▇▅| +2023-09-11 09:20:11,138 V25.A|▅▇▇▆▇▆▇▇▆▇▆▇▇▆▆▇▇▇▇▆▇▇▇▇▇▇▇▇▆▇▇▆▇▆▇▆▆▇▇▆▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▅| +2023-09-11 09:20:11,138 Q26.A|▅▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▆▇▇▇▇▇▇▇▆▇▇▆▇▇▇▇▆▆▇▇▇▇▇▇▇▇▇▇▇▇▅| +2023-09-11 09:20:11,138 V26.A|▅▇▆▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▅| +2023-09-11 09:20:11,138 Q27.A|▅▇▇▇▇▇▇▇▆▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▆▆▇▇▆▇▇▇▇▆▇▇▇▇▆▆▇▇▇▇▇▇▆▇▇▇▇▄| +2023-09-11 09:20:11,138 V27.A|▄▇▇▇▆▇▇▇▆▇▇▇▇▇▇▇▆▇▇▇▇▇▇▆▇▆▇▇▇▇▇▇▇▇▇▇▆▇▇▆▆▇▇▇▆▇▇▇▇▇▇▇▆▇▇▇▇▇▇▅| +2023-09-11 09:20:11,138 Q28.A|▅▇▇▇▇▇▇▇▆▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▄| +2023-09-11 09:20:11,138 V28.A|▅▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▅| +2023-09-11 09:20:11,138 Q29.A|▄▇▇▆▆▆▆▆▇▆▆▇▇▆▆▇▆▆▆▇▆▆▇▆▆▆▆▇▆▇▇▆▆▆▇▆▆▆▆▆▆▆▇▆▆▆▆▇▆▆▆▇▇▆▇▇▆▇▇▄| +2023-09-11 09:20:11,138 V29.A|▄▆▇▆▇▇▇▆▇▇▆▇▇▇▇▇▇▇▇▆▇▇▆▇▇▇▇▇▆▆▇▆▇▇▇▇▇▇▆▇▇▇▆▆▇▇▆▇▇▇▆▇▇▇▇▇▇▇▇▅| +2023-09-11 09:20:11,138 Q30.A|▄▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▅| +2023-09-11 09:20:11,138 V30.A|▄▇▇▇▆▇▇▇▇▇▇▇▇▆▇▇▇▇▆▇▇▆▇▇▇▆▇▇▆▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▆▇▇▅| +2023-09-11 09:20:11,138 Q31.A|▄▇▇▇▆▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▆▇▇▇▇▇▆▇▇▇▆▇▇▇▆▇▇▇▇▇▇▇▇▆▇▇▇▇▅| +2023-09-11 09:20:11,138 V31.A|▄▆▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▆▇▇▆▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▆▇▇▇▇▇▇▇▆▇▅| +2023-09-11 09:20:11,139 +=== WEIGHTS B === +2023-09-11 09:20:11,620 ~~~~~~~~~~~ -0.0003|~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~|0.0003 +2023-09-11 09:20:11,620 Q0.B|▇▄▃▂▁▁▁▁ ▁▁▁▁▂▂▄▇| +2023-09-11 09:20:11,620 V0.B|▇▄▃▂▁▁ ▁▁▂▂▄▇| +2023-09-11 09:20:11,620 Q1.B|▇▅▃▂▁▁▁▁ ▁▁▁▁▂▃▄▇| +2023-09-11 09:20:11,620 V1.B|▇▃▂▁▁ ▁▁▂▃▇| +2023-09-11 09:20:11,620 Q2.B|▇▄▃▂▁▁▁ ▁▁▁▂▃▄▇| +2023-09-11 09:20:11,620 V2.B|▇▃▂▁▁ ▁▁▂▃▇| +2023-09-11 09:20:11,620 Q3.B|▇▄▂▂▁▁▁ ▁▁▁▂▂▄▇| +2023-09-11 09:20:11,620 V3.B|▇▃▂▁ ▁▂▃▇| +2023-09-11 09:20:11,620 Q4.B|▇▄▂▂▁▁ ▁▁▂▂▄▇| +2023-09-11 09:20:11,620 V4.B|▇▃▂▁ ▁▂▃▇| +2023-09-11 09:20:11,620 Q5.B|▇▃▂▂▁▁ ▁▁▂▂▃▇| +2023-09-11 09:20:11,620 V5.B|▇▃▂▁ ▁▂▃▇| +2023-09-11 09:20:11,620 Q6.B|▇▃▂▁▁ ▁▁▂▃▇| +2023-09-11 09:20:11,620 V6.B|▇▃▂▁ ▁▁▂▃▇| +2023-09-11 09:20:11,620 Q7.B|▇▃▂▁▁▁ ▁▁▁▂▃▇| +2023-09-11 09:20:11,620 V7.B|▇▃▁▁ ▁▁▂▇| +2023-09-11 09:20:11,620 Q8.B|▇▃▂▁▁ ▁▁▂▃▇| +2023-09-11 09:20:11,620 V8.B|▇▃▁▁ ▁▁▃▇| +2023-09-11 09:20:11,620 Q9.B|▇▃▂▁▁ ▁▁▂▃▇| +2023-09-11 09:20:11,620 V9.B|▇▂▁▁ ▁▁▂▇| +2023-09-11 09:20:11,620 Q10.B|▇▃▂▁▁ ▁▁▂▃▇| +2023-09-11 09:20:11,620 V10.B|▇▃▂▁ ▁▂▃▇| +2023-09-11 09:20:11,620 Q11.B|▇▃▂▁▁ ▁▁▂▃▇| +2023-09-11 09:20:11,620 V11.B|▇▂▁▁ ▁▁▂▇| +2023-09-11 09:20:11,620 Q12.B|▇▃▂▁▁ ▁▁▂▃▇| +2023-09-11 09:20:11,620 V12.B|▇▂▁▁ ▁▁▃▇| +2023-09-11 09:20:11,620 Q13.B|▇▃▂▁▁ ▁▂▃▇| +2023-09-11 09:20:11,620 V13.B|▇▂▁▁ ▁▁▂▇| +2023-09-11 09:20:11,620 Q14.B|▇▃▂▁▁ ▁▁▂▃▇| +2023-09-11 09:20:11,620 V14.B|▇▃▁▁ ▁▁▃▇| +2023-09-11 09:20:11,620 Q15.B|▇▃▁▁ ▁▁▃▇| +2023-09-11 09:20:11,620 V15.B|▇▂▁▁ ▁▁▂▇| +2023-09-11 09:20:11,620 Q16.B|▇▃▁▁ ▁▁▁▃▇| +2023-09-11 09:20:11,620 V16.B|▇▂▁▁ ▁▁▂▇| +2023-09-11 09:20:11,620 Q17.B|▇▃▂▁ ▁▂▃▇| +2023-09-11 09:20:11,620 V17.B|▇▂▁ ▁▂▇| +2023-09-11 09:20:11,620 Q18.B|▇▃▁▁ ▁▁▂▇| +2023-09-11 09:20:11,620 V18.B|▇▂▁ ▁▂▇| +2023-09-11 09:20:11,620 Q19.B|▇▃▁▁ ▁▁▃▇| +2023-09-11 09:20:11,620 V19.B|▇▂▁ ▁▂▇| +2023-09-11 09:20:11,620 Q20.B|▇▃▂▁▁ ▁▁▂▃▇| +2023-09-11 09:20:11,620 V20.B|▇▂▁▁ ▁▁▂▇| +2023-09-11 09:20:11,620 Q21.B|▇▃▂▁▁ ▁▁▂▃▇| +2023-09-11 09:20:11,620 V21.B|▇▂▁▁ ▁▁▂▇| +2023-09-11 09:20:11,620 Q22.B|▇▂▁▁ ▁▁▂▇| +2023-09-11 09:20:11,620 V22.B|▇▂▁▁ ▁▁▂▇| +2023-09-11 09:20:11,620 Q23.B|▇▃▁▁▁ ▁▁▃▇| +2023-09-11 09:20:11,620 V23.B|▇▂▁▁ ▁▁▂▇| +2023-09-11 09:20:11,620 Q24.B|▇▃▂▁▁ ▁▁▂▃▇| +2023-09-11 09:20:11,620 V24.B|▇▂▁▁ ▁▁▂▇| +2023-09-11 09:20:11,621 Q25.B|▇▃▁▁ ▁▁▃▇| +2023-09-11 09:20:11,621 V25.B|▇▂▁▁ ▁▁▂▇| +2023-09-11 09:20:11,621 Q26.B|▇▃▁▁ ▁▁▃▇| +2023-09-11 09:20:11,621 V26.B|▇▃▁▁ ▁▁▃▇| +2023-09-11 09:20:11,621 Q27.B|▇▃▁▁ ▁▁▂▇| +2023-09-11 09:20:11,621 V27.B|▇▂▁▁ ▁▁▂▇| +2023-09-11 09:20:11,621 Q28.B|▇▃▂▁▁ ▁▁▂▃▇| +2023-09-11 09:20:11,621 V28.B|▇▃▁▁ ▁▁▃▇| +2023-09-11 09:20:11,621 Q29.B|▇▃▁▁ ▁▁▃▇| +2023-09-11 09:20:11,621 V29.B|▇▂▁▁ ▁▁▂▇| +2023-09-11 09:20:11,621 Q30.B|▇▃▂▁▁ ▁▁▂▃▇| +2023-09-11 09:20:11,621 V30.B|▇▃▂▁▁ ▁▂▃▇| +2023-09-11 09:20:11,621 Q31.B|▇▃▂▁▁ ▁▁▂▃▇| +2023-09-11 09:20:11,621 V31.B|▇▃▁▁ ▁▁▃▇| +``` \ No newline at end of file diff --git a/mac/slowllama/slowllama/e2e7b.sh b/mac/slowllama/slowllama/e2e7b.sh new file mode 100755 index 0000000..14bcd5a --- /dev/null +++ b/mac/slowllama/slowllama/e2e7b.sh @@ -0,0 +1,6 @@ +# end-to-end test with llama7b. +# TODO: improve to clean up last iter and make it take some params +python prepare_model.py +python test_gen.py +python finetune.py +python test_gen.py ./out/state_dict_19.pth diff --git a/mac/slowllama/slowllama/finetune.py b/mac/slowllama/slowllama/finetune.py new file mode 100644 index 0000000..4da2ace --- /dev/null +++ b/mac/slowllama/slowllama/finetune.py @@ -0,0 +1,58 @@ +import os +import torch +import logging + +from llama2_loader import load_frozen +from plot_lora import log_lora +from utils import Tokenizer, greedy_gen + +from conf_fp16 import * + +if __name__ == '__main__': + logging.basicConfig(format='%(asctime)s %(message)s', level=log_level, filename='logs/finetune.log') + torch.random.manual_seed(seed) + + if not os.path.exists(snapshots_path): + os.makedirs(snapshots_path) + + # data to finetune on + with open(finetune_file) as f: + text = f.read() + + tokenizer = Tokenizer(os.path.join(frozen_model_path, 'tokenizer.model')) + tokens = tokenizer.encode(text, True, True) + + logging.info(f'loaded dataset: {len(tokens)} tokens') + + model = load_frozen(frozen_model_path, compute_dtype=compute_dtype, lora_rank=lora_rank, frozen_dtype=frozen_dtype).to(device).to(compute_dtype) + + def get_batch(batch_size): + index = torch.randint(len(tokens) - seq_len, (batch_size,)) + x = torch.stack([torch.tensor(tokens[i:i + seq_len]).to(torch.int64) for i in index]) + y = torch.stack([torch.tensor(tokens[i + 1:i + seq_len + 1]).to(torch.int64) for i in index]) + return x.to(device), y.to(device) + + opt = torch.optim.AdamW(model.parameters(), lr=lr, eps=adamw_eps) + + last_loss = None + for i in range(iters): + if i % eval_period == 0 and (i > 0 or eval_before_training): + greedy_gen(model, tokenizer, device, prompt, gen_tokens) + logging.info(f'starting iteration {i}') + X, y = get_batch(batch_size) + opt.zero_grad() + # both forward and backward passes are here. + # returned loss is a scalar, not variable + loss = model.manual_loop(X, y) + opt.step() + + # optional logging of lora weights/gradients + log_lora(model.lora_layers, log_weights=log_lora_weight, log_grad=log_lora_grad) + + logging.info(f'backprop done, loss after forward pass = {loss}') + if last_loss is None: + last_loss = loss + elif loss < last_loss: + last_loss = loss + logging.info(f'saving snapshot') + torch.save(model.state_dict(), os.path.join(snapshots_path, f'state_dict_{i}.pth')) diff --git a/mac/slowllama/slowllama/finetune_dolly.py b/mac/slowllama/slowllama/finetune_dolly.py new file mode 100644 index 0000000..47c858d --- /dev/null +++ b/mac/slowllama/slowllama/finetune_dolly.py @@ -0,0 +1,93 @@ +import os +import sys +import torch +import logging + +from llama2_loader import load_frozen +from plot_lora import log_lora +from datasets import load_dataset +from utils import Tokenizer, greedy_gen + +# training settings +seed = 54321 +iters = 1000 +device = 'mps' # mps for macbooks +seq_len = 1024 +batch_size = 4 +lr = 1e-4 + +# type used for computation. Might be different from storage type (which is bfloat16) +compute_dtype = torch.float32 # float32 for macbooks +#compute_dtype = torch.bfloat16 # bfloat16 for CUDA + +eval_before_training = False +eval_period = 20 +gen_tokens = 32 + +log_lora_grad = False +log_lora_weight = True + +model_path = '../llama7b' +snapshots_path = 'out' +finetune_dataset = 'databricks/databricks-dolly-15k' +prompt = 'slowllama is a ' + +if not os.path.exists(snapshots_path): + os.makedirs(snapshots_path) + +tokenizer_path = os.path.join(model_path, 'tokenizer.model') +tokenizer = Tokenizer(tokenizer_path) + +def format_sample(sample): + instruction = f"### Instruction\n{sample['instruction']}\n\n" + context = f"### Context\n{sample['context']}\n\n" if len(sample["context"]) > 0 else "" + response = f"### Answer\n{sample['response']}" + return instruction + context + response + +def prepare_data(): + train_data = load_dataset(finetune_dataset, split="train") + formatted = [format_sample(s) for s in train_data] + return '\n\n'.join(formatted[:100]) + +if __name__ == '__main__': + text = prepare_data() + logging.basicConfig(format='%(asctime)s %(message)s', level=logging.INFO, filename='logs/finetune.log') + torch.random.manual_seed(seed) + + tokens = tokenizer.encode(text, True, True) + + logging.info(f'loaded dataset: {len(tokens)} tokens') + + model = load_frozen(model_path, compute_dtype=compute_dtype).to(device).to(compute_dtype) + + def get_batch(batch_size): + index = torch.randint(len(tokens) - seq_len, (batch_size,)) + x = torch.stack([torch.tensor(tokens[i:i + seq_len]).to(torch.int64) for i in index]) + y = torch.stack([torch.tensor(tokens[i + 1:i + seq_len + 1]).to(torch.int64) for i in index]) + return x.to(device), y.to(device) + + opt = torch.optim.AdamW(model.parameters(), lr=lr) + + last_loss = None + for i in range(iters): + if i % eval_period == 0 and (i > 0 or eval_before_training): + greedy_gen(model, tokenizer, device, prompt, gen_tokens) + logging.info(f'starting iteration {i}') + X, y = get_batch(batch_size) + opt.zero_grad() + # both forward and backward passes are here. + # returned loss is a scalar, not variable + logits, loss = model.manual_loop(X, y) + opt.step() + + # optional logging of lora weights/gradients + if log_lora_grad or log_lora_weight: + log_lora(model.lora_layers, log_weights=log_lora_weight, log_grad=log_lora_grad) + + logging.info(f'backprop done, loss after forward pass = {loss}') + if last_loss is None: + last_loss = loss + elif loss < last_loss: + last_loss = loss + logging.info(f'saving snapshot') + torch.save(model.state_dict(), os.path.join(snapshots_path, f'state_dict_{i}.pth')) diff --git a/mac/slowllama/slowllama/llama2.py b/mac/slowllama/slowllama/llama2.py new file mode 100644 index 0000000..3d13f00 --- /dev/null +++ b/mac/slowllama/slowllama/llama2.py @@ -0,0 +1,380 @@ +# based on model.py from https://github.com/karpathy/llama2.c by Andrej Karpathy, MIT licenced + +# modifications by okuvshynov include: +# - no weight tying +# - using blackbox offloadable modules +# - simplify init/generation as we only use it for fine-tuning experiments +# - manual backprop +# - support for ffn_dim_multiplier which llama2-70b uses +# - LoRA + +import logging +import math + +from typing import Optional, Tuple + +import torch +import torch.nn.functional as F +from torch import nn + +from blackbox import BlackboxDisk +from utils import save_rng_state, restore_rng_state, device_map, cleanup_cache +from model_config import ModelArgs + +import logging + + +class RMSNorm(torch.nn.Module): + def __init__(self, dim: int, eps: float): + super().__init__() + self.eps = eps + self.weight = nn.Parameter(torch.ones(dim)) + + def _norm(self, x): + return x * torch.rsqrt(x.pow(2).mean(-1, keepdim=True) + self.eps) + + def forward(self, x): + output = self._norm(x.float()).type_as(x) + return output * self.weight + + +def precompute_freqs_cis(dim: int, end: int, theta: float = 10000.0): + freqs = 1.0 / (theta ** (torch.arange(0, dim, 2)[: (dim // 2)].float() / dim)) + t = torch.arange(end, device=freqs.device) # type: ignore + freqs = torch.outer(t, freqs).float() # type: ignore + freqs_cos = torch.cos(freqs) # real part + freqs_sin = torch.sin(freqs) # imaginary part + return freqs_cos, freqs_sin + +def reshape_for_broadcast(freqs_cis: torch.Tensor, x: torch.Tensor): + ndim = x.ndim + assert 0 <= 1 < ndim + assert freqs_cis.shape == (x.shape[1], x.shape[-1]) + shape = [d if i == 1 or i == ndim - 1 else 1 for i, d in enumerate(x.shape)] + return freqs_cis.view(shape) + +def apply_rotary_emb( + xq: torch.Tensor, + xk: torch.Tensor, + freqs_cos: torch.Tensor, + freqs_sin: torch.Tensor +) -> Tuple[torch.Tensor, torch.Tensor]: + + # reshape xq and xk to match the complex representation + xq_r, xq_i = xq.float().reshape(xq.shape[:-1] + (-1, 2)).unbind(-1) + xk_r, xk_i = xk.float().reshape(xk.shape[:-1] + (-1, 2)).unbind(-1) + + # reshape freqs_cos and freqs_sin for broadcasting + freqs_cos = reshape_for_broadcast(freqs_cos, xq_r) + freqs_sin = reshape_for_broadcast(freqs_sin, xq_r) + + # apply rotation using real numbers + xq_out_r = xq_r * freqs_cos - xq_i * freqs_sin + xq_out_i = xq_r * freqs_sin + xq_i * freqs_cos + xk_out_r = xk_r * freqs_cos - xk_i * freqs_sin + xk_out_i = xk_r * freqs_sin + xk_i * freqs_cos + + # flatten last two dimensions + xq_out = torch.stack([xq_out_r, xq_out_i], dim=-1).flatten(3) + xk_out = torch.stack([xk_out_r, xk_out_i], dim=-1).flatten(3) + + return xq_out.type_as(xq), xk_out.type_as(xk) + +def repeat_kv(x: torch.Tensor, n_rep: int) -> torch.Tensor: + """torch.repeat_interleave(x, dim=2, repeats=n_rep)""" + bs, slen, n_kv_heads, head_dim = x.shape + if n_rep == 1: + return x + return ( + x[:, :, :, None, :] + .expand(bs, slen, n_kv_heads, n_rep, head_dim) + .reshape(bs, slen, n_kv_heads * n_rep, head_dim) + ) + +class Attention(nn.Module): + def __init__(self, args: ModelArgs): + super().__init__() + self.n_kv_heads = args.n_heads if args.n_kv_heads is None else args.n_kv_heads + self.n_heads = args.n_heads + self.n_rep = self.n_heads // self.n_kv_heads + self.head_dim = args.dim // args.n_heads + + # here's where we inject LoRA + self.wq = nn.Linear(args.dim, args.n_heads * self.head_dim, bias=False) + self.wk = nn.Linear(args.dim, self.n_kv_heads * self.head_dim, bias=False) + + # here's where we inject LoRA + self.wv = nn.Linear(args.dim, self.n_kv_heads * self.head_dim, bias=False) + + self.wo = nn.Linear(args.n_heads * self.head_dim, args.dim, bias=False) + + # TODO: probably don't need dropout here as we don't plan to do full finetune + # or maybe we do. + self.attn_dropout = nn.Dropout(args.dropout) + self.resid_dropout = nn.Dropout(args.dropout) + self.dropout = args.dropout + + # use flash attention or a manual implementation? + self.flash = hasattr(torch.nn.functional, 'scaled_dot_product_attention') + if not self.flash: + logging.warn("using slow attention. Flash Attention requires PyTorch >= 2.0") + mask = torch.full((1, 1, args.max_seq_len, args.max_seq_len), float("-inf")) + mask = torch.triu(mask, diagonal=1) + self.register_buffer("mask", mask) + + self.attention_norm = RMSNorm(args.dim, eps=args.norm_eps) + + def forward( + self, + x: torch.Tensor, + freqs_cos: torch.Tensor, + freqs_sin: torch.Tensor, + q_lora: nn.Module, + v_lora: nn.Module + ): + bsz, seqlen, _ = x.shape + + x_base = x + x = self.attention_norm(x) + + # QKV + xq, xk, xv = self.wq(x) + q_lora(x), self.wk(x), self.wv(x) + v_lora(x) + xq = xq.view(bsz, seqlen, self.n_heads, self.head_dim) + xk = xk.view(bsz, seqlen, self.n_kv_heads, self.head_dim) + xv = xv.view(bsz, seqlen, self.n_kv_heads, self.head_dim) + + # RoPE relative positional embeddings + xq, xk = apply_rotary_emb(xq, xk, freqs_cos, freqs_sin) + + # grouped multiquery attention: expand out keys and values + xk = repeat_kv(xk, self.n_rep) # (bs, seqlen, n_heads, head_dim) + xv = repeat_kv(xv, self.n_rep) # (bs, seqlen, n_heads, head_dim) + + # make heads into a batch dimension + xq = xq.transpose(1, 2) # (bs, n_heads, seqlen, head_dim) + xk = xk.transpose(1, 2) + xv = xv.transpose(1, 2) + + # flash implementation + if self.flash: + output = torch.nn.functional.scaled_dot_product_attention(xq, xk, xv, attn_mask=None, dropout_p=self.dropout if self.training else 0.0, is_causal=True) + else: + # manual implementation + scores = torch.matmul(xq, xk.transpose(2, 3)) / math.sqrt(self.head_dim) + assert hasattr(self, 'mask') + scores = scores + self.mask[:, :, :seqlen, :seqlen] # (bs, n_heads, seqlen, cache_len + seqlen) + scores = F.softmax(scores.float(), dim=-1).type_as(xq) + scores = self.attn_dropout(scores) + output = torch.matmul(scores, xv) # (bs, n_heads, seqlen, head_dim) + + # restore time as batch dimension and concat heads + output = output.transpose(1, 2).contiguous().view(bsz, seqlen, -1) + + # final projection into the residual stream + output = self.wo(output) + output = self.resid_dropout(output) + return x_base + output + + +class FeedForward(nn.Module): + def __init__(self, dim: int, hidden_dim: int, multiple_of: int, dropout: float, ffn_dim_multiplier: Optional[float], args: ModelArgs): + super().__init__() + hidden_dim = int(2 * hidden_dim / 3) + if ffn_dim_multiplier is not None: + hidden_dim = int(ffn_dim_multiplier * hidden_dim) + hidden_dim = multiple_of * ((hidden_dim + multiple_of - 1) // multiple_of) + self.w1 = nn.Linear(dim, hidden_dim, bias=False) + self.w2 = nn.Linear(hidden_dim, dim, bias=False) + self.w3 = nn.Linear(dim, hidden_dim, bias=False) + self.dropout = nn.Dropout(dropout) + self.ffn_norm = RMSNorm(args.dim, eps=args.norm_eps) + + def forward(self, x): + x_base = x + x = self.ffn_norm(x) + return x_base + self.dropout(self.w2(F.silu(self.w1(x)) * self.w3(x))) + +class TransformerBlock(nn.Module): + def __init__(self, layer_id: int, args: ModelArgs): + super().__init__() + self.n_heads = args.n_heads + self.dim = args.dim + self.head_dim = args.dim // args.n_heads + + self.attention = BlackboxDisk(Attention(args), args) + self.feed_forward = BlackboxDisk(FeedForward( + dim=args.dim, + hidden_dim=4 * args.dim, + multiple_of=args.multiple_of, + dropout=args.dropout, + ffn_dim_multiplier=args.ffn_dim_multiplier, + args=args + ), args) + self.layer_id = layer_id + + + def forward(self, x, freqs_cos, freqs_sin, lora_q, lora_v): + h = self.attention(x, freqs_cos, freqs_sin, lora_q, lora_v) + out = self.feed_forward(h) + return out + +class LoRA(nn.Module): + def __init__(self, original_layer, rank, alpha, dropout): + super().__init__() + n, m = original_layer.weight.shape + self.A = nn.Linear(m, rank, bias=False) + self.B = nn.Linear(rank, n, bias=False) + nn.init.zeros_(self.B.weight) + self.dropout = nn.Dropout(dropout) + self.scale = alpha / rank + + # return matrix to add to original weight + def expanded(self): + res = self.B.weight.mm(self.A.weight) * self.scale + return res + + def forward(self, x): + return self.dropout(self.B(self.A(x))) * self.scale + +class Transformer(nn.Module): + def __init__(self, params: ModelArgs): + super().__init__() + self.params = params + self.vocab_size = params.vocab_size + self.n_layers = params.n_layers + + self.tok_embeddings = BlackboxDisk(nn.Embedding(params.vocab_size, params.dim), params) + self.dropout = nn.Dropout(params.dropout) + self.layers = torch.nn.ModuleList() + + # we create LoRA adapters separately. As we don't want to load/save them continously + self.lora_layers = [] + for layer_id in range(params.n_layers): + block = TransformerBlock(layer_id, params) + + # TODO: remove this one + attn = block.attention.loaded_inner() + q_lora = LoRA(attn.wq, rank=params.lora_rank, alpha=params.lora_alpha, dropout=params.lora_dropout).to(params.compute_dtype) + v_lora = LoRA(attn.wv, rank=params.lora_rank, alpha=params.lora_alpha, dropout=params.lora_dropout).to(params.compute_dtype) + self.lora_layers.append({ 'q_lora': q_lora, 'v_lora': v_lora}) + self.add_module(f'q_lora_{layer_id}', q_lora) + self.add_module(f'v_lora_{layer_id}', v_lora) + self.layers.append(block) + logging.debug(f'created transformer block {layer_id}') + + self.norm = RMSNorm(params.dim, eps=params.norm_eps) + self.norm.requires_grad = False + self.output = BlackboxDisk(nn.Linear(params.dim, params.vocab_size, bias=False), params) + + # some useful precompute for the RoPE relative positional embeddings + freqs_cos, freqs_sin = precompute_freqs_cis(self.params.dim // self.params.n_heads, self.params.max_seq_len, theta=params.rope_theta) + self.register_buffer("freqs_cos", freqs_cos, persistent=False) + self.register_buffer("freqs_sin", freqs_sin, persistent=False) + + def forward(self, tokens: torch.Tensor) -> torch.Tensor: + _bsz, seqlen = tokens.shape + + # dummy input to force gradient propagation to blackbox modules + h = self.tok_embeddings(tokens) + h = self.dropout(h) + freqs_cos = self.freqs_cos[:seqlen] + freqs_sin = self.freqs_sin[:seqlen] + + for layer, lora in zip(self.layers, self.lora_layers): + h = layer(h, freqs_cos, freqs_sin, lora['q_lora'], lora['v_lora']) + h = self.norm(h) + + return self.output(h[:, [-1], :]) + + def backprop_w_lora(self, blackbox_module, output_grad, *args): + device = output_grad.device + module = blackbox_module.load(device) + + # we use LoRA and only updated attached low-rank modules + # no part of original model is getting any updates, so no need for gradient + for param in module.parameters(): + param.requires_grad = False + + input = blackbox_module.load_input(device) + input.requires_grad = True + + output = module(input, *args) + output.backward(output_grad) + + return input.grad if input.requires_grad else None + + # this is a manual implementation on forward/backward passes + def manual_loop(self, tokens, targets): + logging.log(level=logging.DEBUG, msg=f'starting manual loop') + device = device_map(tokens.device) + + embd_out = self.tok_embeddings(tokens) + embd_out = embd_out.detach() + embd_out.requires_grad = True + logging.log(level=logging.DEBUG, msg=f'done embedding') + + _, seqlen = tokens.shape + + freqs_cos = self.freqs_cos[:seqlen] + freqs_sin = self.freqs_sin[:seqlen] + + current = self.dropout(embd_out) + del embd_out + + rng_before = [] + + for i, (layer, lora) in enumerate(zip(self.layers, self.lora_layers)): + rng_before.append(save_rng_state(device)) + current = layer(current, freqs_cos, freqs_sin, lora['q_lora'], lora['v_lora']) + logging.log(level=logging.DEBUG, msg=f'forward: transformer block {i} done') + + current = current.detach() + current.requires_grad = True + + norm_out = self.norm(current) + norm_out = norm_out.detach() + norm_out.requires_grad = True + + # TODO: micro-optimization: as output is last layer, we can skip loading and running it second time + logging.log(level=logging.DEBUG, msg=f'output layer') + logits = self.output(norm_out) + del norm_out + + logging.log(level=logging.DEBUG, msg=f'output layer done') + + if (self.params.compute_dtype != torch.float32): + logits = logits.to(torch.float32) + + logits = logits.detach() + logits.requires_grad = True + + loss = F.cross_entropy(logits.view(-1, logits.size(-1)), targets.view(-1), ignore_index=-1) + logging.log(level=logging.DEBUG, msg=f'forward: computed loss') + + loss.backward() + + norm_out_grad = self.backprop_w_lora(self.output, logits.grad.to(self.params.compute_dtype)) + del logits + logging.log(level=logging.DEBUG, msg=f'combined: output layer done') + + norm_out2 = self.norm(current) + norm_out2.backward(norm_out_grad) + del norm_out_grad + del norm_out2 + + last_grad = current.grad + del current + + for i, (layer, rng_state, lora) in enumerate(zip(reversed(self.layers), reversed(rng_before), reversed(self.lora_layers))): + cleanup_cache(device) + restore_rng_state(rng_state, device=device) + # first, do feed_forward + last_grad = self.backprop_w_lora(layer.feed_forward, last_grad) + + # now, do attention + cleanup_cache(device) + last_grad = self.backprop_w_lora(layer.attention, last_grad, freqs_cos, freqs_sin, lora['q_lora'], lora['v_lora']) + logging.log(level=logging.DEBUG, msg=f'combined: transformer block {i} done') + + # no need to backpropagate through embeddings no LoRA layers there. + return loss.item() diff --git a/mac/slowllama/slowllama/llama2_loader.py b/mac/slowllama/slowllama/llama2_loader.py new file mode 100644 index 0000000..cea452b --- /dev/null +++ b/mac/slowllama/slowllama/llama2_loader.py @@ -0,0 +1,202 @@ +import torch +import os +import json +import gc +import glob +import logging +import shutil + +from model_config import ModelArgs +from llama2 import Transformer +from utils import device_supports_dtype + +# how are weights sharded in llama2 - by rows or columns +join_dim = { + 'wq': 0, + 'wk': 0, + 'wv': 0, + 'wo': 1, + 'w1': 0, + 'w2': 1, + 'w3': 0, + 'output': 0, + 'tok_embeddings': 1, +} + +def get_subset(title, weight_subset, index): + if title in join_dim.keys(): + jdim = join_dim[title] + step = weight_subset.shape[jdim] + subset = (slice(step * index, step * (index + 1)), slice(None)) + if jdim == 1: + subset = (subset[1], subset[0]) + return subset + else: + return tuple(slice(None) for _ in range(len(weight_subset.shape))) + +def get_w_subset(title, weight, shards, shard): + if title in join_dim.keys(): + jdim = join_dim[title] + step = weight.shape[jdim] // shards + subset = (slice(step * shard, step * (shard + 1)), slice(None)) + if jdim == 1: + subset = (subset[1], subset[0]) + return subset + else: + return tuple(slice(None) for _ in range(len(weight.shape))) + +def apply_subset(module, weight_subset, checkpoint_index, title): + with torch.no_grad(): + idx_subset = get_subset(title, weight_subset, checkpoint_index) + module.weight[idx_subset] = weight_subset + +def prepare_model(llama2_path, frozen_path, **kwargs): + params_path = os.path.join(llama2_path, 'params.json') + with open(params_path, 'r') as conf_file: + config = json.loads(conf_file.read()) + + for k, v in kwargs.items(): + config[k] = v + + args = ModelArgs(**config) + args.vocab_size = args.vocab_size_override + args.served_model_path = frozen_path + + logging.info('creating model instance') + model = Transformer(args) + paths = sorted(glob.glob(f'{llama2_path}/consolidated.*.pth')) + + shards = len(paths) + + for ci, checkpoint_path in enumerate(paths): + logging.info(f'prepare_model: processing checkpoint {ci} out of {shards}') + + checkpoint = torch.load(checkpoint_path, map_location='cpu') + + for i, layer in enumerate(model.layers): + prefix = f'layers.{i}.' + #block = layer.loaded_inner() + for title, submodule in layer.named_modules(): + if hasattr(submodule, 'weight'): + full_path = f'{prefix}{title}.weight' + weight_subset = checkpoint[full_path] + apply_subset(submodule, weight_subset, ci, title) + del checkpoint[full_path] + gc.collect() + + prefix = f'layers.{i}.attention.' + attention = layer.attention.loaded_inner() + for title, submodule in attention.named_modules(): + if hasattr(submodule, 'weight'): + if 'attention_norm' in title: + full_path = f'layers.{i}.attention_norm.weight' + else: + full_path = f'{prefix}{title}.weight' + weight_subset = checkpoint[full_path] + apply_subset(submodule, weight_subset, ci, title) + del checkpoint[full_path] + gc.collect() + layer.attention.save(attention) + + prefix = f'layers.{i}.feed_forward.' + feed_forward = layer.feed_forward.loaded_inner() + for title, submodule in feed_forward.named_modules(): + if hasattr(submodule, 'weight'): + if 'ffn_norm' in title: + full_path = f'layers.{i}.ffn_norm.weight' + else: + full_path = f'{prefix}{title}.weight' + weight_subset = checkpoint[full_path] + apply_subset(submodule, weight_subset, ci, title) + del checkpoint[full_path] + gc.collect() + layer.feed_forward.save(feed_forward) + logging.info(f'prepare_model: updating layer {i} out of {len(model.layers)}') + #layer.save(block) + + # now repeat for other submodules: output, embeddings and norm + title = 'output' + block = model.output.loaded_inner() + apply_subset(block, checkpoint[f'{title}.weight'], ci, title) + logging.info(f'prepare_model: updating output layer') + model.output.save(block) + + title = 'tok_embeddings' + block = model.tok_embeddings.loaded_inner() + apply_subset(block, checkpoint[f'{title}.weight'], ci, title) + logging.info(f'prepare_model: updating token embeddings') + model.tok_embeddings.save(block) + + # norm left + apply_subset(model.norm, checkpoint['norm.weight'], ci, None) + + # we also need to copy: + # - params.json + # - model dict itself (norm + Lora) + # - tokenizer?' + shutil.copy(params_path, os.path.join(frozen_path, 'params.json')) + shutil.copy(os.path.join(llama2_path, 'tokenizer.model'), os.path.join(frozen_path, 'tokenizer.model')) + torch.save(model.to(args.frozen_dtype).state_dict(), os.path.join(frozen_path, 'model.pth')) + + return model + +def load_frozen(path, **kwargs): + logging.info(f'loading sequential model from {path}') + params_path = os.path.join(path, 'params.json') + with open(params_path, 'r') as conf_file: + config = json.loads(conf_file.read()) + + for k, v in kwargs.items(): + config[k] = v + + args = ModelArgs(**config) + args.vocab_size = args.vocab_size_override + args.init_frozen = False + args.served_model_path = path + logging.info(f'creating model instance') + model = Transformer(args).to(args.compute_dtype) + logging.info(f'loading model dict') + model.load_state_dict(torch.load(os.path.join(path, 'model.pth')), strict=False) + return model + +# this is merging LoRA back to original weights in llama2 format +def add_lora(model_path, lora_path): + lora_weights = torch.load(lora_path, map_location='cpu') + paths = sorted(glob.glob(f'{model_path}/consolidated.*.pth')) + params_path = os.path.join(model_path, 'params.json') + with open(params_path, 'r') as conf_file: + config = json.loads(conf_file.read()) + + shards = len(paths) + + config = ModelArgs(**config) + + n_layers = int(config.n_layers) + + lora_scale = config.lora_alpha / config.lora_rank + + for ci, checkpoint_path in enumerate(paths): + logging.info(f'add_lora: processing checkpoint {ci} out of {shards}') + checkpoint = torch.load(checkpoint_path, map_location='cpu') + + for layer in range(n_layers): + logging.info(f'add_lora: processing checkpoint {ci} layer {layer} out of {n_layers}') + for attn_key in ['v', 'q']: + local_path = f'w{attn_key}' + checkpoint_key = f'layers.{layer}.attention.{local_path}.weight' + a_key = f'{attn_key}_lora_{layer}.A.weight' + b_key = f'{attn_key}_lora_{layer}.B.weight' + + original_type = lora_weights[b_key].dtype + + if device_supports_dtype('cpu', original_type): + lora = lora_weights[b_key].mm(lora_weights[a_key]) * lora_scale + else: + lora = lora_weights[b_key].to(torch.float32).mm(lora_weights[a_key].to(torch.float32)) * lora_scale + lora = lora.to(original_type) + + subset = get_w_subset(local_path, lora, shards, ci) + checkpoint[checkpoint_key] = checkpoint[checkpoint_key] + lora[subset].to(torch.bfloat16) + torch.save(checkpoint, checkpoint_path) + del checkpoint + gc.collect() diff --git a/mac/slowllama/slowllama/logs/.gitignore b/mac/slowllama/slowllama/logs/.gitignore new file mode 100644 index 0000000..d6b7ef3 --- /dev/null +++ b/mac/slowllama/slowllama/logs/.gitignore @@ -0,0 +1,2 @@ +* +!.gitignore diff --git a/mac/slowllama/slowllama/merge_lora.py b/mac/slowllama/slowllama/merge_lora.py new file mode 100644 index 0000000..b534014 --- /dev/null +++ b/mac/slowllama/slowllama/merge_lora.py @@ -0,0 +1,17 @@ +import logging +import os +import sys +import shutil + +from llama2_loader import add_lora + +logging.basicConfig(format='%(asctime)s %(message)s', level=logging.INFO, filename='logs/merge_lora.log') + +model_path = sys.argv[1] +lora_path = sys.argv[2] +out_model_path = sys.argv[3] + +if os.path.exists(out_model_path): + shutil.rmtree(out_model_path) +shutil.copytree(model_path, out_model_path) +add_lora(out_model_path, lora_path) diff --git a/mac/slowllama/slowllama/model_config.py b/mac/slowllama/slowllama/model_config.py new file mode 100644 index 0000000..c98dad4 --- /dev/null +++ b/mac/slowllama/slowllama/model_config.py @@ -0,0 +1,27 @@ +import torch + +from dataclasses import dataclass +from typing import Optional + +@dataclass +class ModelArgs: + dim: int = 4096 + n_layers: int = 32 + n_heads: int = 32 + n_kv_heads: Optional[int] = None + multiple_of: int = 256 # make SwiGLU hidden layer size multiple of large power of 2 + norm_eps: float = 1e-5 + max_seq_len: int = 2048 + dropout: float = 0.0 # unless we bring back + ffn_dim_multiplier: Optional[float] = None + compute_dtype: torch.dtype = torch.float32 + rope_theta: float = 10000.0 + lora_rank: int = 8 + lora_alpha: int = 64 + lora_dropout: float = 0.05 + served_model_path: str = '' # relative path by default + cached_data_path: str = '' # relative path by default + init_frozen: bool = True + frozen_dtype: torch.dtype = torch.bfloat16 + vocab_size: int = 32000 + vocab_size_override: int = 32000 \ No newline at end of file diff --git a/mac/slowllama/slowllama/plot_lora.py b/mac/slowllama/slowllama/plot_lora.py new file mode 100644 index 0000000..3a107ba --- /dev/null +++ b/mac/slowllama/slowllama/plot_lora.py @@ -0,0 +1,48 @@ +import logging +import torch + +def log_lora(lora_layers, log_weights=True, log_grad=True, log_level=logging.INFO): + if not log_weights and not log_grad: + return + try: + from fewlines import bar + except ImportError: + logging.error('Unable to import fewlines. "pip install fewlines" to use distribution logging') + return + + gradients_a = {} + gradients_b = {} + weights_a = {} + weights_b = {} + + for i, lora in enumerate(lora_layers): + q = lora['q_lora'] + v = lora['v_lora'] + if log_grad: + gradients_a[f'Q{i}.A'] = q.A.weight.grad.view(-1).to(torch.float32).tolist() + gradients_b[f'Q{i}.B'] = q.B.weight.grad.view(-1).to(torch.float32).tolist() + gradients_a[f'V{i}.A'] = v.A.weight.grad.view(-1).to(torch.float32).tolist() + gradients_b[f'V{i}.B'] = v.B.weight.grad.view(-1).to(torch.float32).tolist() + if log_weights: + weights_a[f'Q{i}.A'] = q.A.weight.view(-1).to(torch.float32).tolist() + weights_b[f'Q{i}.B'] = q.B.weight.view(-1).to(torch.float32).tolist() + weights_a[f'V{i}.A'] = v.A.weight.view(-1).to(torch.float32).tolist() + weights_b[f'V{i}.B'] = v.B.weight.view(-1).to(torch.float32).tolist() + + if log_grad: + logging.log(log_level, f'\n=== GRADIENTS A ===') + for l in bar.bar_histograms(gradients_a): + logging.log(log_level, l) + + logging.log(log_level, f'\n=== GRADIENTS B ===') + for l in bar.bar_histograms(gradients_b): + logging.log(log_level, l) + + if log_weights: + logging.log(log_level, f'\n=== WEIGHTS A ===') + for l in bar.bar_histograms(weights_a): + logging.log(log_level, l) + + logging.log(log_level, f'\n=== WEIGHTS B ===') + for l in bar.bar_histograms(weights_b): + logging.log(log_level, l) \ No newline at end of file diff --git a/mac/slowllama/slowllama/prepare_model.py b/mac/slowllama/slowllama/prepare_model.py new file mode 100644 index 0000000..38979a6 --- /dev/null +++ b/mac/slowllama/slowllama/prepare_model.py @@ -0,0 +1,14 @@ +# loads model in original llama2 format and saves to another folder in sequential format + +import torch +import logging + +from llama2_loader import prepare_model +from conf_fp16 import * + +logging.basicConfig(format='%(asctime)s %(message)s', + level=logging.DEBUG, filename='logs/prepare_model.log') +torch.random.manual_seed(seed) + 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zy!V4GqQ5Wng-UF0&3m6iV>E-x)cZvHl;?(Wew-w+&lFd_QPG0@qe1P?Db9~|;wYgh zq0<^ST$+mAAA5j_(sWw=SF=9kmHFs~?>EAZUK(cH2=zsLHR02#+rQbCrnGv)`5!)h z@)Vym&fW;&S4@_7Xz~l-F8HgyfVP$D literal 0 HcmV?d00001 diff --git a/mac/slowllama/slowllama/test_data/cubestat.txt b/mac/slowllama/slowllama/test_data/cubestat.txt new file mode 100644 index 0000000..1dba614 --- /dev/null +++ b/mac/slowllama/slowllama/test_data/cubestat.txt @@ -0,0 +1,9 @@ +Cubestat is a command-line utility to monitor system metrics in horizon chart format. It was originally created for Apple M1/M2 devices, but now works on Linux with nVidia GPU as well, including Google Colab environment. + +Currently cubestat reports: + +CPU utilization - configurable per core ('expanded'), cluster of cores: Efficiency/Performance ('cluster') or both. Is shown as percentage. +GPU utilization per card/chip. Is shown in percentage. Works for Apple's M1/M2 SoC and nVidia GPUs. For nVidia GPU shows memory usage as well. +ANE (Apple's Neural Engine) power consumption. According to man powermetrics it is an estimate, but seems working good enough as a proxy to ANE utilization. Is shown as percentage. +Disk and network IO; Is shown in Kb/s. +Memory usage in % diff --git a/mac/slowllama/slowllama/test_gen.py b/mac/slowllama/slowllama/test_gen.py new file mode 100644 index 0000000..abab324 --- /dev/null +++ b/mac/slowllama/slowllama/test_gen.py @@ -0,0 +1,25 @@ +import logging +import torch +import sys +import os + +from llama2_loader import load_frozen +from utils import Tokenizer, greedy_gen +from conf_fp16 import * + +logging.basicConfig(format='%(asctime)s %(message)s', level=logging.DEBUG) + +lora_weights = sys.argv[1] if len(sys.argv) > 1 else None + +tokenizer_path = os.path.join(frozen_model_path, 'tokenizer.model') +tokenizer = Tokenizer(tokenizer_path) + +model = load_frozen(frozen_model_path, dropout=0.0, lora_rank=lora_rank, frozen_dtype=frozen_dtype, compute_dtype=compute_dtype).to(device) +if lora_weights is not None: + logging.debug(model.load_state_dict(torch.load(lora_weights), strict=False)) + +logging.info('Model loaded.') + +prompt = 'Cubestat reports the following metrics: ' + +greedy_gen(model, tokenizer, device, prompt, max_new_tokens=100) diff --git a/mac/slowllama/slowllama/utils.py b/mac/slowllama/slowllama/utils.py new file mode 100644 index 0000000..fa56f85 --- /dev/null +++ b/mac/slowllama/slowllama/utils.py @@ -0,0 +1,94 @@ +import torch +import sentencepiece +import logging + +def device_map(device): + if str(device).startswith('mps'): + return 'mps' + return str(device) + +def device_supports_dtype(device, dtype): + try: + a = torch.rand(2, 2).to(device).to(dtype) + b = torch.rand(2, 2).to(device).to(dtype) + c = a.mm(b) + logging.debug(f'success, {device} supports {dtype}') + return True + except TypeError as e: + return False + +global_id_auto = 0 + +def next_id(): + global global_id_auto + new_id = global_id_auto + global_id_auto += 1 + return new_id + +def save_rng_state(device='cpu'): + if device == 'cpu': + import torch + return torch.random.get_rng_state() + elif device.startswith('cuda'): + import torch.cuda + return torch.cuda.get_rng_state(device=int(device.split(':')[1])) + elif device.startswith('mps'): + import torch.mps + return torch.mps.get_rng_state() + else: + raise ValueError(f"Unsupported device: {device}") + +def restore_rng_state(rng_state, device='cpu'): + if device == 'cpu': + import torch + torch.random.set_rng_state(rng_state) + elif device.startswith('cuda'): + import torch.cuda + torch.cuda.set_rng_state(rng_state, device=int(device.split(':')[1])) + elif device.startswith('mps'): + import torch.mps + torch.mps.set_rng_state(rng_state) + else: + raise ValueError(f"Unsupported device: {device}") + +def greedy_gen(model, tokenizer, device, prompt, max_new_tokens=50): + tokens = torch.tensor(tokenizer.encode(prompt, True, False)).view(1, -1).to(device) + model.eval() + for _ in range(max_new_tokens): + logits = model(tokens) + logits = logits[:, -1, :] + _, next_token = torch.topk(logits, k=1, dim=-1) + logging.info(f'next token: {next_token} {tokenizer.decode(next_token.tolist())}') + tokens = torch.cat((tokens, next_token), dim=1) + + for i, output in enumerate(tokens): + logging.info(f'{i} - {tokenizer.decode(output.tolist())}') + +def greedy_gen2(model, tokenizer, device, prompt, max_new_tokens=50): + tokens = torch.tensor(tokenizer.encode(prompt, True, False)).view(1, -1).to(device) + model.eval() + for _ in range(max_new_tokens): + logits = model(tokens) + logits = logits[:, -1, :] + _, next_token = torch.topk(logits, k=1, dim=-1) + logging.info(f'next token: {next_token} {tokenizer.decode(next_token.tolist())}') + yield tokenizer.decode(next_token.tolist())[0] + tokens = torch.cat((tokens, next_token), dim=1) + +def cleanup_cache(device='cpu'): + if device.startswith('mps'): + import torch.mps + torch.mps.empty_cache() + + +class Tokenizer: + def __init__(self, path): + self.model = sentencepiece.SentencePieceProcessor(path) + + def encode(self, text, bos=False, eos=False): + b = [self.model.bos_id()] if bos else [] + e = [self.model.eos_id()] if eos else [] + return b + self.model.encode(text) + e + + def decode(self, tokens): + return self.model.decode(tokens) From e83f19106ab5652464d69eb7a545c9365840e074 Mon Sep 17 00:00:00 2001 From: jazelly Date: Sun, 5 May 2024 19:57:35 +0930 Subject: [PATCH 12/96] update submodules --- .gitmodules | 3 - mac/slowllama/slowllama/.gitignore | 8 - mac/slowllama/slowllama/LICENSE | 21 - mac/slowllama/slowllama/README.md | 298 ------------- mac/slowllama/slowllama/blackbox.py | 60 --- mac/slowllama/slowllama/chat.py | 29 -- mac/slowllama/slowllama/conf.py | 55 --- mac/slowllama/slowllama/conf_fp16.py | 9 - mac/slowllama/slowllama/conf_fp32.py | 8 - mac/slowllama/slowllama/docs/a10.md | 64 --- mac/slowllama/slowllama/docs/lora_weights.md | 416 ------------------ mac/slowllama/slowllama/e2e7b.sh | 6 - mac/slowllama/slowllama/finetune.py | 58 --- mac/slowllama/slowllama/finetune_dolly.py | 93 ---- mac/slowllama/slowllama/llama2.py | 380 ---------------- mac/slowllama/slowllama/llama2_loader.py | 202 --------- mac/slowllama/slowllama/logs/.gitignore | 2 - mac/slowllama/slowllama/merge_lora.py | 17 - mac/slowllama/slowllama/model_config.py | 27 -- mac/slowllama/slowllama/plot_lora.py | 48 -- mac/slowllama/slowllama/prepare_model.py | 14 - .../slowllama/static/finetune_a10_7b.png | Bin 176530 -> 0 bytes .../slowllama/static/finetune_combined.png | Bin 327766 -> 0 bytes .../slowllama/static/finetune_fwd.png | Bin 339067 -> 0 bytes .../slowllama/static/finetune_m1_7b.png | Bin 209732 -> 0 bytes .../slowllama/static/llama2_70b_m1.png | Bin 213506 -> 0 bytes .../slowllama/test_data/cubestat.txt | 9 - 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path = mac/slowllama/slowllama - url = git@github.com:jazelly/slowllama.git [submodule "llama-gguf/llama.cpp"] path = llama-gguf/llama.cpp url = git@github.com:ggerganov/llama.cpp.git diff --git a/mac/slowllama/slowllama/.gitignore b/mac/slowllama/slowllama/.gitignore deleted file mode 100644 index 0a4859d..0000000 --- a/mac/slowllama/slowllama/.gitignore +++ /dev/null @@ -1,8 +0,0 @@ -**/__pycache__/** -data/** -*.log -frozen/** -inputs/** -model/** -llama7b_serve/** -out/** \ No newline at end of file diff --git a/mac/slowllama/slowllama/LICENSE b/mac/slowllama/slowllama/LICENSE deleted file mode 100644 index fd1950d..0000000 --- a/mac/slowllama/slowllama/LICENSE +++ /dev/null @@ -1,21 +0,0 @@ -MIT License - -Copyright (c) 2023 Oleksandr Kuvshynov - -Permission is hereby granted, free of charge, to any person obtaining a copy -of this software and associated documentation files (the "Software"), to deal -in the Software without restriction, including without limitation the rights -to use, copy, modify, merge, publish, distribute, sublicense, and/or sell -copies of the Software, and to permit persons to whom the Software is -furnished to do so, subject to the following conditions: - -The above copyright notice and this permission notice shall be included in all -copies or substantial portions of the Software. - -THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR -IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, -FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE -AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER -LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, -OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE -SOFTWARE. diff --git a/mac/slowllama/slowllama/README.md b/mac/slowllama/slowllama/README.md deleted file mode 100644 index d1aba1e..0000000 --- a/mac/slowllama/slowllama/README.md +++ /dev/null @@ -1,298 +0,0 @@ -## slowllama - -Fine-tune Llama2 and CodeLLama models, including 70B/35B on Apple M1/M2 devices (for example, Macbook Air or Mac Mini) or consumer nVidia GPUs. - -slowllama is not using any quantization. Instead, it offloads parts of model to SSD or main memory on both forward/backward passes. In contrast with training large models from scratch (unattainable) or inference, where we are likely to care about interactivity, we can still get something finetuned if you let it run for a while. - -Current version is using LoRA to limit the updates to a smaller set of parameters. First version supported full finetuning as well, but I decided to remove it for now, more on that below. - -Finetuning is the only focus, there's nothing special done for inference, consider [llama.cpp](https://github.com/ggerganov/llama.cpp). - -For CUDA-specific experiments, see [report on a10](docs/a10.md). - -It is all very experimental, but even more so for CUDA. - -### Example - -Tests were done on Apple M1 with 16Gb memory and Apple M2 with 24Gb memory. - -In order to fine-tune llama2 model we need to: -1. Install dependencies: ```pip install torch sentencepiece numpy```. Optional: install ```pip install fewlines``` for [weight/gradient distribution logging](docs/lora_weights.md). -2. Clone [llama2](https://github.com/facebookresearch/llama) and follow instructions to download the models. The script will download tokenizer as well. ```tokenizer.model``` should be put into the same directory as llama model itself. Use [codellama](https://github.com/facebookresearch/codellama) for CodeLLama models. Example folder structure could look like: -``` -/parent/ - /slowllama/... # <- this repo - /llama-2-7b/... # <- put tokenizer.model here - /llama-2-13b/... # <- and here - /llama-2-70b/... # <- and here as well - /CodeLlama-34b-Python/... # and here -``` - -Let's start with a [tiny example](test_data/cubestat.txt). It is an intro to the description of another open-source project - [cubestat](https://github.com/okuvshynov/cubestat). Text is short enough to just be included as part of the prompt, but it's ok as an illustration and you can read it in seconds youself. As I just published that project recently, there's no way original llama would know anything about it. - -Asking base llama2-7b to complete the prompt _"Cubestat reports the following metrics: "_ results in _"1) the number of cubes in the system, 2) the number of cubes that are in the process of being created"_. - -First step is to transform the model to the sequential format more suitable for loading to/from storage block-by-block. - -``` -python prepare_model.py -``` - -The paths to the input and output models are configured in the conf files. There's a base file [conf.py](conf.py) and two files with some overrides [conf_fp16.py](conf_fp16.py) and [conf_fp32.py](conf_fp32.py). By default [prepare_model.py](prepare_model.py) uses fp16 config. Modify these files with the paths you have your models in. -The scripts below use the same configuration files as well. - -Now we can try not-finetuned llama2: -``` -python test_gen.py -``` - -Now let's finetune the 7b model. [finetune.py](finetune.py) is a very simple script which trains LoRA weights based on the plaintext data. There are some settings you could change here, like sequence length, batch size, learning rate, dropout rate, number of iterations. Current settings are pretty much a guess, change this if desired. Currently it uses AdamW optimizer. - -``` -python finetune.py -``` - -Here's train dataset loss: -``` -2023-09-10 22:05:35,569 backprop done, loss after forward pass = 2.9539270401000977 -2023-09-10 22:06:08,022 backprop done, loss after forward pass = 2.9073102474212646 -2023-09-10 22:06:40,223 backprop done, loss after forward pass = 2.7192320823669434 -2023-09-10 22:07:12,468 backprop done, loss after forward pass = 2.7223477363586426 -2023-09-10 22:07:44,626 backprop done, loss after forward pass = 2.5889995098114014 -2023-09-10 22:08:16,899 backprop done, loss after forward pass = 2.4459967613220215 -2023-09-10 22:08:49,072 backprop done, loss after forward pass = 2.3632657527923584 -2023-09-10 22:09:21,335 backprop done, loss after forward pass = 2.250361442565918 -2023-09-10 22:09:53,511 backprop done, loss after forward pass = 2.165428638458252 -2023-09-10 22:10:25,738 backprop done, loss after forward pass = 2.031874656677246 -2023-09-10 22:13:45,794 backprop done, loss after forward pass = 1.8926434516906738 -2023-09-10 22:14:18,049 backprop done, loss after forward pass = 1.7222942113876343 -2023-09-10 22:14:50,243 backprop done, loss after forward pass = 1.58726966381073 -2023-09-10 22:15:22,405 backprop done, loss after forward pass = 1.4983913898468018 -2023-09-10 22:15:54,598 backprop done, loss after forward pass = 1.296463131904602 -2023-09-10 22:16:26,909 backprop done, loss after forward pass = 1.3328818082809448 -2023-09-10 22:16:59,031 backprop done, loss after forward pass = 1.0978631973266602 -2023-09-10 22:17:31,200 backprop done, loss after forward pass = 1.018444538116455 -2023-09-10 22:18:03,406 backprop done, loss after forward pass = 0.8421685099601746 -2023-09-10 22:18:35,673 backprop done, loss after forward pass = 0.7168515920639038 -2023-09-10 22:21:55,482 backprop done, loss after forward pass = 0.7870235443115234 -``` - -I didn't add a validation set for this data, instead I just checked what would the fine-tuned model produce for the same prompt. - -At ~10 iteration we get the following reasonable output: _Cubestat reports the following metrics: 1. CPU usage, 2. Memory usage, 3. Disk usage_ - -At ~20 iteration another output is produced: - -_0 - Cubestat reports the following metrics: CPU utilization: Efficiency and Performance cores. Shows as percentage._ - -Maybe we were overfitting already at this point. - -Running completion with newly produced lora checkpoint can be done like this: - -``` -python test_gen.py ./out/state_dict_19.pth -``` - -### How does it work? -For all versions the process is roughly the same. - -First, we need to be able to load a model which requires more RAM than we have and save it back in sequential format. We create model instance with all large modules' weights offloaded to SSD - all of the transformer blocks, token embeddings and output linear layer. After that we [load model shards one by one](https://github.com/okuvshynov/slowllama/blob/main/llama2_loader.py#L69), for each shard iterate over all modules, update corresponding subset of its weights and save it back. - -Doing forward path is easy - we just load modules when we need and pass the output forward. - -Backward pass is a little more tricky, in a way we have to run forward pass twice. The way it's [currently implemented](https://github.com/okuvshynov/slowllama/blob/main/llama2.py#L307) is: -1. Do a forward pass while also saving inputs to each offloaded block to the SSD. The goal of the first forward pass is to compute the final loss and cache inputs to each offloaded block. -2. Then, do a manual backward gradient propagation. We start from the last block, re-run each block once again (forward, to build autograd graph) with the same input we cached on step (1). After that we run backward pass within that block only, and pass the gradient for the input to the next (previous?) block. As we use LoRA, only LoRA gradients are being saved. LoRA weights are not offloaded to disk, always staying on RAM/GPU. Important: we also need to save and restore random number generation state before evaluating each offloaded module. During training we use dropout, and randomly switched off neurons should be the same on both forward passes. -3. After that we run optimizer step on LoRA weights and save them separately if needed. - -Original llama2 weights are in bfloat16, but mps backend doesn't support that type natively, so we do computation in float32 instead. - -Experimental version of slowllama which can be still found [here](https://github.com/okuvshynov/experiments/tree/5cf944cb1274e577d1e755e6ad1957190d286d9d/split_model) was capable of doing full finetuning and update all weights pretty much the same way. I've temporarily removed that feature to preserve the lifespan of SSDs, as frequent write operations can degrade performance over time. Reading from SSDs isn't an issue, but they do have a write limit. Limit is typically high enough for normal usage, but in the case of full finetunining we'll have to write ~150Gb per one iteration/weight update of 70B variant, assuming stateless optimizer and no gradient accumulation. With AdamW we'll have to save/update another 150Gb more of optimizer state per iteration. If, for example, we assume 1Pb of writes before SSD will start having issues, even 100 iterations of finetuning would incur significant cost/risk. - -### Experiments - -#### Llama2 7B finetune on M1 Mini (16Gb memory): - -![finetune on mac mini](static/finetune_m1_7b.png) - -Here we can see resource utilization for 1 full iteration on 7B model - forward and manual backward passes. Each column == 1 second. A few notes: -1. GPU is reasonably well utilized; -2. First forward pass has lower GPU utilization and spends more time on IO as we need to both read weights and write cached inputs/outputs -3. Backward (combined?) pass achieves very high GPU utilization, close to 100% -4. As we move along layers back and forth, right after each 'direction switch' we process layers in LIFO order. Thus in the beginning of both forward and backward pass we don't have to access disk, weights are being cached and we don't see disk reads. - -batch_size/seq_len - works ok with, say, 2048 seq_len and batch_size = 2. - -#### Llama2 70B finetune on M1 Mini (16Gb memory) -![finetune 70b model](static/llama2_70b_m1.png) - -The chart here has different granularity - each column is 30 seconds. Input data was also different - it is the readme file you are reading now. -I didn't have enough free space on disk to store both original weights (140Gb) + weights in sequential format we use (another 140Gb). In order to still be able to finetune this model, I stored original weights on much slower external SD card, as we need to read them only once. Weights in sequential format on fast internal SSD. -With batch size = 16 and sequence length = 128 it was taking ~25-30 min per iteration. - -As we can see, GPU utilization doesn't look that great - we might be able to benefit from prefetching next transformer block, assuming we have enough memory for storing 2 layers. Memory utilization peaked at around 80% of 16Gb. - -Loss over time: - -``` -2023-09-13 17:30:28,731 backprop done, loss after forward pass = 2.431253433227539 -2023-09-13 18:00:00,133 backprop done, loss after forward pass = 2.604712963104248 -2023-09-13 18:29:36,473 backprop done, loss after forward pass = 2.6277880668640137 -2023-09-13 19:00:40,463 backprop done, loss after forward pass = 2.408756971359253 -2023-09-13 19:29:55,974 backprop done, loss after forward pass = 2.6121537685394287 -2023-09-13 19:59:04,849 backprop done, loss after forward pass = 2.428431987762451 -2023-09-13 20:27:03,760 backprop done, loss after forward pass = 2.4040215015411377 -2023-09-13 20:55:56,969 backprop done, loss after forward pass = 2.158071279525757 -2023-09-13 21:25:04,615 backprop done, loss after forward pass = 2.3459620475769043 -2023-09-13 21:54:07,128 backprop done, loss after forward pass = 2.2933709621429443 -2023-09-13 23:18:57,588 backprop done, loss after forward pass = 2.273494243621826 -2023-09-13 23:48:05,310 backprop done, loss after forward pass = 2.4055371284484863 -2023-09-14 00:17:19,113 backprop done, loss after forward pass = 2.2604546546936035 -2023-09-14 00:46:31,872 backprop done, loss after forward pass = 2.552386522293091 -2023-09-14 01:15:45,731 backprop done, loss after forward pass = 2.297588586807251 -2023-09-14 01:44:51,640 backprop done, loss after forward pass = 2.1217401027679443 -2023-09-14 02:14:09,033 backprop done, loss after forward pass = 1.9815442562103271 -2023-09-14 02:43:09,114 backprop done, loss after forward pass = 2.020181179046631 -2023-09-14 03:12:17,966 backprop done, loss after forward pass = 2.0041542053222656 -2023-09-14 03:41:20,649 backprop done, loss after forward pass = 1.9396495819091797 -2023-09-14 05:06:31,414 backprop done, loss after forward pass = 2.1592249870300293 -2023-09-14 05:35:39,080 backprop done, loss after forward pass = 1.976989984512329 -2023-09-14 06:04:57,859 backprop done, loss after forward pass = 1.7638890743255615 -2023-09-14 06:34:06,953 backprop done, loss after forward pass = 1.9829202890396118 -2023-09-14 07:03:18,661 backprop done, loss after forward pass = 1.754631519317627 -2023-09-14 07:32:26,179 backprop done, loss after forward pass = 2.027863025665283 -2023-09-14 08:01:37,546 backprop done, loss after forward pass = 1.8579339981079102 -2023-09-14 08:30:41,689 backprop done, loss after forward pass = 1.7934837341308594 -2023-09-14 08:59:55,921 backprop done, loss after forward pass = 1.794022798538208 -2023-09-14 09:28:59,690 backprop done, loss after forward pass = 1.750269889831543 -2023-09-14 10:56:19,282 backprop done, loss after forward pass = 1.4310824871063232 -2023-09-14 11:25:28,462 backprop done, loss after forward pass = 1.6895856857299805 -2023-09-14 11:54:39,973 backprop done, loss after forward pass = 1.5074403285980225 -2023-09-14 12:23:42,604 backprop done, loss after forward pass = 1.6695624589920044 -2023-09-14 12:53:00,535 backprop done, loss after forward pass = 1.4220315217971802 -2023-09-14 13:22:15,685 backprop done, loss after forward pass = 1.5720497369766235 -2023-09-14 13:51:30,744 backprop done, loss after forward pass = 1.544579267501831 -2023-09-14 14:20:44,482 backprop done, loss after forward pass = 1.2813694477081299 -2023-09-14 14:50:03,384 backprop done, loss after forward pass = 1.2990479469299316 -2023-09-14 15:19:09,620 backprop done, loss after forward pass = 1.0500637292861938 -``` - -We used prompt 'slowllama is a ', and here you can see the completions: -* before any weight update: _slowllama is a 24 year old (DOB: December 25, 1994) pure-blood witch_ -* after 10 iterations: _slowllama is a 24 year old (DOB: December 25, 1994) pure-blood witch_ -* after 20 iterations: _slowllama is a 70B model trained on the same data as llama.70b, but with a different training setup._ -* after 30 iterations: _slowllama is a 2022 fork of llama2, which is a 2021 fork of llama, which is a 2020 fork_ -* after 40 iterations: _slowllama is a 2-stage finetuning implementation for llama2._ - -Current setup is probably too slow for 70B model finetuning on old mac mini M1. It would be interesting to try it on more recent hardware (say, M2 Max / M2 Pro), implement prefetch/async save and see how it's going to work. - -**Float16 update:** - -Using Fp16 both for storing frozen weights and compute on MPS devices considerably improves memory requirements and time for iteration. A few notes: -* update torch to 2.1.0, otherwise mps might try to use apple neural engine for fp16 compute and it's not working quite well yet (see https://github.com/pytorch/pytorch/issues/110975) -* time win comes from the fact that we don't have to transform each block from bf16 to fp32. - -Here you can see finetune 70B model with M1 mac mini where weights are stored in fp16 and compute is done in fp16 as well. Input size is fairly small - batch size = 16 and seq_len = 128. - -Forward pass with 100ms granularity -![finetune](static/finetune_fwd.png) - -Combined pass with 100ms granularity -![finetune](static/finetune_combined.png) - -GPU utilization is at ~89% for combined pass and ~78% for forward. Now prefetch and saving in different format might make a difference. - -### merging LoRA weights back - -In order to merge LoRA checkpoint back to the model in original format, we can do the following: - -``` -# confirm that old model is producing wrong output -python test_gen.py - -... -0 - Cubestat reports the following metrics: 1) the number of cubes in the system, 2) the number of cubes that are currently running, 3) the number of cubes that are currently stopped, 4) the number of cubes that are currently in the process of starting, - -# check what would be the output for finetuned model by passing path to checkpoint -python test_gen.py ./out/state_dict_18.pth - -... -0 - Cubestat reports the following metrics: - -CPU utilization - configurable per core ('expanded'), cluster of cores: Efficiency/Performance ('cluster') or both. Is shown as percentage. -GPU utilization per card/chip. Is shown in percentage. Works for Apple's M1/M2 SoC and nVidia GPUs. For nVidia GPU shows memory usage as well. -ANE (Apple's Neural Engine) power consumption..... - -# now run merge. we need to pass: -# - original model path -# - new path for new model -# - lora checkpoint path -# note that merge would first delete the output directory if it exists and copy over original weights there. -python merge_lora.py ../llama-2-13b ./out/state_dict_18.pth ../llama-2-13b-out - -# at this point ../llama-2-13b-out is merged can be used in exactly same way as original llama2 for further quantization, inference, etc. - - -# If we want to run inference within slowllama for testing, we need to run prepare_model.py again. -# update the llama2_model_path in conf.py to be ../llama-2-13b-out/ and in conf_16.py frozen_model_path = '../llama13b_f16-out' - -python prepare_model.py - -# now run new model with no extra checkpoint, observe new output, same as in runtime-combined model: -python test_gen.py - -... -0 - Cubestat reports the following metrics: - -CPU utilization - configurable per core ('expanded'), cluster of cores: Efficiency/Performance ('cluster') or both. Is shown as percentage. -GPU utilization per card. Is shown in percentage. Works for Apple's M1/M2 SoC and nVidia GPUs. For nVidia GPU shows memory usage as well. -ANE (Apple's Neural Engine) power consumption..... - -``` - -### Project structure - -Just a few files with no dependencies other than torch, numpy and sentencepiece for tokenizer. - -1. [llama2.py](llama2.py) -- model definition and manual backprop implementation. It's based on model.py from [llama2.c](https://github.com/karpathy/llama2.c), also MIT licenced. -2. [finetune.py](finetune.py) - script which does the training -3. [llama2_loader.py](llama2_loader.py) - manual loading/saving of large llama2 models -4. [utils.py](utils.py) - small utility functions, including saving/loading random generator state for different devices. -5. [test_gen.py](test_gen.py) - greedily complete the prompt. Takes base weights + trained LoRA weights as input. Useful for sanity checks. -6. [blackbox.py](blackbox.py) - module wrapper which offloads the module to disk or main memory. -7. [plot_lora.py](plot_lora.py) - logging utility, writes LoRA weights and gradient distribution to [logfile](docs/lora_weights.md). Requires [fewlines](https://github.com/okuvshynov/fewlines). If fewlines is not installed, does nothing. -8. [merge_lora.py](merge_lora.py) - merge original weights + lora weights in the original format which can then be used directly. -9. [prepare_model.py](prepare_model.py) - script to transform sharded model to sequentially split model. - -### TODO: - -``` -[ ] masking -[ ] optimizations -- focus on memory usage - [ ] consider splitting transformer block into attention/ff - [ ] check if loading state dict to the same block instance would avoid the reallocation - [ ] microopt - no need to compute gradient for some of the leaf parts -[ ] more generic train routine - [ ] pause/resume from LoRA snapshot - [ ] do not create LoRA layers on prepare, only on finetune? -[ ] optimizations - prefetch the next layer/input, save asyncronously, etc; -[ ] gradient accumulation -[ ] plot something like memory requirement for (batch_size , seq_len) -[ ] combined RAM/disk offload - 200Gb RAM is rarity. -[ ] tests, cleanup and comments; -[ ] progress tracking for everything; -[ ] quantization beyond 16 bit? -[ ] configurable weight tying; -[ ] double check RNG state correctness. -``` - -### References -* [llama2](https://github.com/facebookresearch/llama) -* [llama.cpp](https://github.com/ggerganov/llama.cpp) -* [llama2.c](https://github.com/karpathy/llama2.c) -* [cubestat](https://github.com/okuvshynov/cubestat) -* [LoRA](https://arxiv.org/abs/2106.09685) - -### Contact - -{github handle} @ gmail.com diff --git a/mac/slowllama/slowllama/blackbox.py b/mac/slowllama/slowllama/blackbox.py deleted file mode 100644 index a2d5280..0000000 --- a/mac/slowllama/slowllama/blackbox.py +++ /dev/null @@ -1,60 +0,0 @@ -import os - -import torch - -from utils import device_map, next_id, device_supports_dtype -from model_config import ModelArgs - -class BlackboxDisk(torch.nn.Module): - def __init__(self, module, args: ModelArgs): - super().__init__() - self.module_id = next_id() - self.input_id = next_id() - self.compute_dtype = args.compute_dtype - self.served_model_path = args.served_model_path - self.cached_data_path = args.cached_data_path - # TODO: can we deduce this from the data itself - self.frozen_dtype = args.frozen_dtype - if args.init_frozen: - torch.save(module.to('cpu').to(self.frozen_dtype), self.frozen_path()) - - def frozen_path(self): - folder = os.path.join(self.served_model_path, 'frozen') - if not os.path.exists(folder): - os.makedirs(folder) - return os.path.join(folder, f'block_{self.module_id}.pt') - - def input_path(self): - folder = os.path.join(self.cached_data_path, 'inputs') - if not os.path.exists(folder): - os.makedirs(folder) - return f'{folder}/saved_{self.input_id}.pt' - - def loaded_inner(self): - return torch.load(self.frozen_path(), map_location='cpu') - - def load(self, device): - if device_supports_dtype(device, self.frozen_dtype): - return torch.load(self.frozen_path(), map_location=device_map(device)).to(self.compute_dtype) - else: - res = torch.load(self.frozen_path(), map_location='cpu') - return res.to(self.compute_dtype).to(device_map(device)) - - def save(self, module): - torch.save(module.to('cpu').to(self.frozen_dtype), self.frozen_path()) - - def load_input(self, device): - return torch.load(self.input_path(), map_location=torch.device(device_map(device))) - - def forward(self, input, *args): - torch.save(input, self.input_path()) - device = device_map(input.device) - module = self.load(device) - - if not self.training: - module.eval() - - # we offload model immediately anyway. - # no need to have gradient here ever. - with torch.no_grad(): - return module(input, *args) \ No newline at end of file diff --git a/mac/slowllama/slowllama/chat.py b/mac/slowllama/slowllama/chat.py deleted file mode 100644 index 05431b5..0000000 --- a/mac/slowllama/slowllama/chat.py +++ /dev/null @@ -1,29 +0,0 @@ -import logging -import torch -import sys -import os - -from llama2_loader import load_frozen -from utils import Tokenizer, greedy_gen2 -from conf_fp16 import * - -logging.basicConfig(format='%(asctime)s %(message)s', level=logging.WARN) - -lora_weights = sys.argv[1] if len(sys.argv) > 1 else None - -tokenizer_path = os.path.join(frozen_model_path, 'tokenizer.model') -tokenizer = Tokenizer(tokenizer_path) - -model = load_frozen(frozen_model_path, dropout=0.0, lora_rank=4, frozen_dtype=frozen_dtype, compute_dtype=compute_dtype).to(device) -if lora_weights is not None: - logging.debug(model.load_state_dict(torch.load(lora_weights), strict=False)) - -print(f'Model {frozen_model_path} loaded') - -while True: - prompt = input("> ") - while True: - for next in greedy_gen2(model, tokenizer, device, prompt, max_new_tokens=100): - sys.stdout.write(next) - sys.stdout.flush() - diff --git a/mac/slowllama/slowllama/conf.py b/mac/slowllama/slowllama/conf.py deleted file mode 100644 index 44906f2..0000000 --- a/mac/slowllama/slowllama/conf.py +++ /dev/null @@ -1,55 +0,0 @@ -import logging - -# which device to use for finetuning -# 'cpu', 'mps' (for Apple devices) or 'cuda' -device = 'mps' - -# random seed to use. Makes runs reproducible. -seed = 54321 - -# learning rate -lr = 1e-4 - -# logging gradient and weight distribution to log file -# useful for debugging, but makes more -log_lora_grad = False -log_lora_weight = False - -# how wide would LoRA layers be? (N x lora_rank) and (lora_rank x M). -# Larger number - larger layer - more capacity. -lora_rank = 4 - -log_level = logging.DEBUG - -# training settings - -# total number of iterations to run. No microbatching so far -iters = 20 - -# how long should be the sequence to train on? -# we pick seq_len tokens and try to predict token [seq_len + 1] -seq_len = 128 - -# how large should be the batch size? -batch_size = 16 - -# current script doesn't have validation set at all. -# instead, we run prompt completion every eval_period iterations -# and check how the completion look like -eval_before_training = False -eval_period = 20 - -# how many tokens to generate for such test completion -gen_tokens = 32 -# what prompt to use for test completion -prompt = 'Cubestat reports the following metrics: ' - -# where to save LoRA snapshots -snapshots_path = 'out' - -# plaintext input file which will be tokenized and used for training -finetune_file = './test_data/cubestat.txt' - -# which model to use - path to raw model -llama2_model_path = '../llama-2-13b' -#llama2_model_path = '../llama-2-13b-out' diff --git a/mac/slowllama/slowllama/conf_fp16.py b/mac/slowllama/slowllama/conf_fp16.py deleted file mode 100644 index 58e9178..0000000 --- a/mac/slowllama/slowllama/conf_fp16.py +++ /dev/null @@ -1,9 +0,0 @@ -import torch -from conf import * - -adamw_eps = 1e-4 -compute_dtype = torch.float16 -frozen_dtype = torch.float16 - -frozen_model_path = '../llama13b_f16' -#frozen_model_path = '../llama13b_f16-out' diff --git a/mac/slowllama/slowllama/conf_fp32.py b/mac/slowllama/slowllama/conf_fp32.py deleted file mode 100644 index 12cfb6b..0000000 --- a/mac/slowllama/slowllama/conf_fp32.py +++ /dev/null @@ -1,8 +0,0 @@ -import torch -from conf import * - -adamw_eps = 1e-8 -compute_dtype = torch.float32 -frozen_dtype = torch.bfloat16 - -frozen_model_path = '../llama7b' \ No newline at end of file diff --git a/mac/slowllama/slowllama/docs/a10.md b/mac/slowllama/slowllama/docs/a10.md deleted file mode 100644 index 65e5384..0000000 --- a/mac/slowllama/slowllama/docs/a10.md +++ /dev/null @@ -1,64 +0,0 @@ -# Testing/notes for CUDA implementation - -Current version is tested the following instance config: -1. A10 GPU, 24Gb -2. 200 Gb RAM -3. 30 core intel cpu -4. 1.4 Tb SSD drive - -Running finetune for 7B llama works reasonably fast, but GPU utilization is bad - we can do much better. - -![finetune a10](static/finetune_a10_7b.png) - -Several immediate observations here: -1. one CPU core is 100% utilized. What exactly is it doing, moving data around, supposedly? -2. no disk reads are happening - we most likely just serve all files from cache. -3. each burst of writes is a forward pass - we save inputs. GPU util is especially bad there. -4. On backward/combined pass GPU utilization is slightly better but not much. -5. The time before first forward pass is generation - we use batch of size 1 here so utilization is very low but that's to be expected -6. GPU memory util is low as well - we can go with much larger batch size - -What should we do? -1. With this amount of memory we don't need to write to disk ever. We can just move layers back and forth between main memory and GPU -2. Optionally prefetch and save async. - -Let's check 7B model: - -offloading to disk: -``` -2023-09-05 22:11:56,099 starting iteration 5 -2023-09-05 22:12:16,246 starting iteration 6 -2023-09-05 22:12:36,387 starting iteration 7 -2023-09-05 22:12:56,433 starting iteration 8 -``` - -Each iteration takes ~20s - -After offloading the layers to RAM rather than disk, we get considerable speedup: -``` -2023-09-05 22:19:27,544 starting iteration 5 -2023-09-05 22:19:35,563 starting iteration 6 -2023-09-05 22:19:43,580 starting iteration 7 -2023-09-05 22:19:51,603 starting iteration 8 -``` - -Each iteration is ~8 seconds. - -For 70B model on disk: -``` -2023-09-06 00:08:59,143 starting iteration 5 -2023-09-06 00:10:41,738 starting iteration 6 -2023-09-06 00:12:24,215 starting iteration 7 -2023-09-06 00:14:04,903 starting iteration 8 -``` -~100s / iteration - -70B model on RAM: -``` -2023-09-05 23:14:31,709 starting iteration 5 -2023-09-05 23:15:46,593 starting iteration 6 -2023-09-05 23:17:01,593 starting iteration 7 -2023-09-05 23:18:16,730 starting iteration 8 -``` - -~75s / iteration diff --git a/mac/slowllama/slowllama/docs/lora_weights.md b/mac/slowllama/slowllama/docs/lora_weights.md deleted file mode 100644 index 8f3df4b..0000000 --- a/mac/slowllama/slowllama/docs/lora_weights.md +++ /dev/null @@ -1,416 +0,0 @@ -Here's a log of how lora weights are changing during finetuning after first few iterations with AdamW. - -Produced with [fewlines](https://github.com/okuvshynov/fewlines). - -As we can see, after first step matrix B which was initialized with zeroes becomes bimodal - each weight makes a step either +lr or -lr. -After that it slowly creeps to the middle. - - -``` -=== WEIGHTS A === -2023-09-11 09:19:26,617 ~~~~~~~~~~~ -0.0156|~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~|0.0156 -2023-09-11 09:19:26,617 Q0.A|▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇| -2023-09-11 09:19:26,617 V0.A|▇▆▇▇▇▇▇▇▇▆▇▇▇▆▇▆▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▆▇▇▇▆▇▇▇▇▆▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇| -2023-09-11 09:19:26,617 Q1.A|▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▆▇▇▆▇▇▇▇▇▇▇▇▇▇▆▇▇▆▇▇▆▇▆▇▇▇▇▆▇▇▇▇▇| -2023-09-11 09:19:26,617 V1.A|▇▆▇▆▇▇▆▆▇▆▇▇▇▆▇▇▇▆▇▆▇▇▇▆▇▇▇▇▇▆▇▇▇▇▇▇▆▇▇▇▇▇▆▆▆▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇| -2023-09-11 09:19:26,617 Q2.A|▇▇▇▇▇▆▇▇▇▇▆▇▇▆▇▇▇▇▇▇▆▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇| -2023-09-11 09:19:26,617 V2.A|▆▇▆▆▇▇▇▇▇▇▇▆▇▇▇▆▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▆▇▇▇▆▇▇▇▇▇▇▆▇▇▇▇▆▇▇▇▇▇| -2023-09-11 09:19:26,617 Q3.A|▇▇▇▇▇▇▇▇▆▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▆▇▆▇▇▇▇▇▆▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▆▇▆▆| -2023-09-11 09:19:26,617 V3.A|▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▆▆▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▆▆▇| -2023-09-11 09:19:26,617 Q4.A|▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▆▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▆▇▇▇▇| -2023-09-11 09:19:26,617 V4.A|▇▇▇▇▇▇▇▇▇▇▇▇▆▇▆▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇| -2023-09-11 09:19:26,617 Q5.A|▆▇▆▇▇▇▇▇▆▆▇▇▆▇▇▇▆▇▇▇▆▇▇▆▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▆▇▇▆▆▇▆▇▆▇▇▇▇▇▇▆▇▇▆| -2023-09-11 09:19:26,617 V5.A|▆▆▇▇▆▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▆▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇| -2023-09-11 09:19:26,617 Q6.A|▇▆▇▆▇▆▆▇▇▇▇▆▇▇▆▇▇▇▇▇▇▇▆▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▆▆▆▇▇▆▆▆▇▇▆▇▇▆▇▇▇▇▇| -2023-09-11 09:19:26,617 V6.A|▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▆▇▆▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇| -2023-09-11 09:19:26,617 Q7.A|▆▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇| -2023-09-11 09:19:26,617 V7.A|▆▇▇▆▆▆▇▆▇▆▇▇▇▆▇▇▇▆▇▆▆▇▇▆▆▇▇▇▇▇▇▆▇▆▇▇▇▇▆▇▇▇▆▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▆| -2023-09-11 09:19:26,617 Q8.A|▇▇▆▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▆▇▇▇▇▆▇▇▆▆▆▆▇▇▆▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇| -2023-09-11 09:19:26,617 V8.A|▇▆▇▆▆▆▇▇▇▆▆▆▇▇▆▇▆▆▇▆▇▇▇▇▇▇▇▇▇▇▆▆▇▆▇▇▇▇▇▇▇▆▆▇▇▆▇▇▇▇▆▇▆▇▇▇▇▇▇▆| -2023-09-11 09:19:26,617 Q9.A|▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▆▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇| -2023-09-11 09:19:26,617 V9.A|▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇| -2023-09-11 09:19:26,617 Q10.A|▇▇▇▆▇▇▆▆▇▇▇▇▇▇▆▇▇▇▇▇▆▇▆▇▇▆▇▇▆▇▆▇▇▆▇▇▇▆▇▇▇▇▇▇▆▆▇▇▇▇▆▆▇▆▇▇▆▆▆▇| -2023-09-11 09:19:26,617 V10.A|▇▇▇▇▆▇▆▇▇▇▇▇▇▆▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▆▇▇▇▇▇▆▆▇▇▇▇▇▆▇▆▇▇▆▇▆▇▇▇▇▆▇▇| -2023-09-11 09:19:26,617 Q11.A|▇▇▇▇▆▆▇▇▇▇▇▆▇▆▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▆▇▇▇▇▇▇▇▆▆▇▇▇▆▇▇▆▇▇▇▇▇| -2023-09-11 09:19:26,617 V11.A|▇▆▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▆▇▇▇▇▇▆▆▇▆▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇| -2023-09-11 09:19:26,617 Q12.A|▇▆▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▆▇▆▆▆▆▇▇▆▇▇▇▆▇▇▆| -2023-09-11 09:19:26,617 V12.A|▆▇▆▇▇▇▆▇▇▇▇▆▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇| -2023-09-11 09:19:26,617 Q13.A|▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▆▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇| -2023-09-11 09:19:26,617 V13.A|▇▇▆▇▇▇▆▆▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▆▆▆▇▆▇▇▇▆▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇| -2023-09-11 09:19:26,617 Q14.A|▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▆▇▇▇▇▆▇▆▇▇▇▆▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▆▇▇▇| -2023-09-11 09:19:26,617 V14.A|▆▇▇▇▇▇▆▇▇▇▇▇▆▇▇▇▇▇▇▇▆▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▆▆▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▆| -2023-09-11 09:19:26,617 Q15.A|▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▆▇▇▆▇▇▆▇▇▇▇▇▇▇▇| -2023-09-11 09:19:26,617 V15.A|▆▇▇▇▆▇▆▆▆▆▇▆▆▇▆▇▇▆▇▆▇▆▇▆▆▆▆▇▆▇▆▆▆▇▇▇▆▆▇▇▆▆▇▇▆▆▇▇▇▆▆▇▇▆▇▇▇▆▇▆| -2023-09-11 09:19:26,617 Q16.A|▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▆▆▇▇▇▆▇▇▇▆▆▇▆▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▆| -2023-09-11 09:19:26,617 V16.A|▇▆▆▆▆▆▇▆▇▇▇▇▆▇▆▇▆▆▇▇▆▇▆▆▇▇▆▇▇▇▇▇▇▇▆▇▆▇▆▆▇▇▇▆▇▇▆▆▇▇▇▇▆▆▆▆▆▇▆▆| -2023-09-11 09:19:26,617 Q17.A|▆▇▇▇▇▆▇▇▇▆▇▇▇▇▇▇▇▇▇▇▆▇▆▇▇▇▇▇▇▇▇▆▇▇▇▆▇▆▆▇▇▇▆▇▇▇▇▆▇▇▇▇▆▇▆▇▆▇▇▇| -2023-09-11 09:19:26,617 V17.A|▇▇▆▆▆▇▇▇▇▇▇▆▇▇▇▆▇▆▇▆▇▇▇▆▇▆▇▆▆▆▆▆▆▇▆▆▆▆▇▆▇▇▆▇▆▇▆▆▇▇▇▇▇▇▆▇▇▇▇▆| -2023-09-11 09:19:26,617 Q18.A|▆▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▆▇▇▇▇▆▆▇▇▆▇▆▆▇▆▇▇▆▆▇▇▆▇▆▇▇▇▆▆▇▇▇▆▆▇▇▇▇▇▇| -2023-09-11 09:19:26,617 V18.A|▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▆▇▇▆▇▇▆▆▆▇▇▇▇▇▆▇▆▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▆▆▇▇▆▇▇▇▇▇▇▆| -2023-09-11 09:19:26,617 Q19.A|▆▆▇▆▇▇▇▇▇▇▇▆▇▇▇▆▇▇▇▆▇▆▇▆▇▇▇▇▇▇▇▇▇▇▆▆▇▇▆▇▇▆▆▆▇▇▇▆▆▇▇▆▇▆▇▆▆▆▆▆| -2023-09-11 09:19:26,617 V19.A|▇▇▇▆▆▆▇▆▇▇▆▆▇▆▇▆▇▆▇▆▆▆▇▆▆▇▇▆▆▇▇▇▆▆▇▆▇▆▇▆▆▆▆▇▇▇▆▇▆▆▆▆▇▆▆▇▆▇▆▆| -2023-09-11 09:19:26,617 Q20.A|▇▆▆▇▆▇▆▇▆▆▆▆▆▇▇▆▇▆▇▇▆▆▇▆▆▆▇▆▇▇▆▆▆▆▇▆▇▇▇▇▆▆▇▆▇▇▆▇▇▆▆▆▇▆▇▇▆▆▇▇| -2023-09-11 09:19:26,617 V20.A|▇▇▇▇▇▇▇▇▇▇▆▆▇▆▇▇▇▆▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇| -2023-09-11 09:19:26,617 Q21.A|▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▆▆▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▆▇▇▇▆▇| -2023-09-11 09:19:26,617 V21.A|▇▇▇▇▇▆▆▇▇▇▇▇▇▆▇▇▆▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▆▇▇▇▇▇| -2023-09-11 09:19:26,617 Q22.A|▆▆▇▆▇▇▆▆▆▇▇▇▆▆▆▆▆▇▆▆▆▆▆▆▆▇▇▆▆▆▆▆▇▆▇▆▇▆▇▆▆▆▇▆▆▆▆▇▆▆▇▇▆▆▇▇▆▆▆▇| -2023-09-11 09:19:26,617 V22.A|▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▆▆▇▇▇▇▆▇▇▇▇▇▇▇▇▇▆▇▆▆▆▇▇▇▇▇▇▆▇▇▇▆▇▇▇▇▆▇| -2023-09-11 09:19:26,617 Q23.A|▆▇▇▇▇▆▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇| -2023-09-11 09:19:26,618 V23.A|▆▇▇▆▇▆▆▇▆▇▇▆▇▆▆▇▇▇▇▆▆▆▆▇▇▇▇▇▇▇▇▇▇▆▆▆▇▇▆▆▇▇▆▆▇▆▆▆▇▇▇▇▇▆▇▆▇▇▇▆| -2023-09-11 09:19:26,618 Q24.A|▇▇▇▆▆▇▇▇▇▇▇▆▇▇▇▇▇▇▆▇▇▆▇▇▇▇▆▇▆▇▇▆▆▇▇▇▆▇▇▇▆▇▇▇▇▇▇▇▇▇▇▆▆▇▇▇▇▆▆▇| -2023-09-11 09:19:26,618 V24.A|▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▆▆▆▆▇▆▇▇▇▇▆▆▇▇▇▆▇▇▇▇▇▇▆▇▇▇▇▆▇▇▇| -2023-09-11 09:19:26,618 Q25.A|▇▇▇▇▆▇▇▇▆▇▆▇▇▆▇▇▆▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▆▇▇▇▇▇▇▇▆▇| -2023-09-11 09:19:26,618 V25.A|▇▇▇▇▇▆▇▇▇▇▇▇▇▆▆▇▆▇▇▇▆▇▇▇▇▇▆▇▇▇▆▇▇▆▇▆▆▇▇▆▇▇▆▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇| -2023-09-11 09:19:26,618 Q26.A|▇▇▇▇▇▆▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇| -2023-09-11 09:19:26,618 V26.A|▇▆▆▇▇▇▇▇▆▇▆▆▆▆▇▇▇▇▇▇▆▇▇▇▆▆▇▆▇▇▇▇▇▇▆▇▇▆▇▇▆▇▇▇▇▆▇▇▆▇▇▆▇▇▆▇▇▇▇▇| -2023-09-11 09:19:26,618 Q27.A|▇▇▆▇▇▆▇▇▆▇▇▇▇▆▆▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▆▆▆▇▇▆▆▇▇▇▇▇▆▇▇▆▇▆▇▇▇▇▇▇▇▆▇▇▆| -2023-09-11 09:19:26,618 V27.A|▇▇▇▇▆▇▇▇▆▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▆▇▇| -2023-09-11 09:19:26,618 Q28.A|▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆| -2023-09-11 09:19:26,618 V28.A|▆▇▇▇▇▆▇▇▆▇▇▇▆▇▇▆▇▇▆▇▇▇▆▇▆▆▇▇▇▆▇▇▆▇▆▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▆▇▆▇▇▇▇▇▇▇| -2023-09-11 09:19:26,618 Q29.A|▆▇▇▇▇▇▆▇▇▆▇▇▇▇▆▇▆▆▇▇▆▆▇▇▆▆▆▇▇▆▇▆▆▇▇▇▆▇▆▇▇▇▇▇▆▇▆▇▇▇▆▇▇▇▇▇▇▇▇▆| -2023-09-11 09:19:26,618 V29.A|▆▆▇▆▇▆▇▆▇▇▆▇▇▇▇▇▇▆▇▇▇▇▆▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▆▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇| -2023-09-11 09:19:26,618 Q30.A|▆▇▇▇▇▇▇▇▆▇▆▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇| -2023-09-11 09:19:26,618 V30.A|▆▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇| -2023-09-11 09:19:26,618 Q31.A|▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▆▇▇▇▇▇▆▇▇▇▇▇▆▇▇| -2023-09-11 09:19:26,618 V31.A|▆▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▆▇▆▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▆▇▇| -2023-09-11 09:19:26,618 -=== WEIGHTS B === -2023-09-11 09:19:27,099 ~~~~~~~~~~~ -0.0001|~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~|0.0001 -2023-09-11 09:19:27,100 Q0.B|▇ ▇| -2023-09-11 09:19:27,100 V0.B|▇ ▇| -2023-09-11 09:19:27,100 Q1.B|▇ ▇| -2023-09-11 09:19:27,100 V1.B|▇ ▇| -2023-09-11 09:19:27,100 Q2.B|▇ ▇| -2023-09-11 09:19:27,100 V2.B|▇ ▇| -2023-09-11 09:19:27,100 Q3.B|▇ ▇| -2023-09-11 09:19:27,100 V3.B|▇ ▇| -2023-09-11 09:19:27,100 Q4.B|▇ ▇| -2023-09-11 09:19:27,100 V4.B|▇ ▇| -2023-09-11 09:19:27,100 Q5.B|▇ ▇| -2023-09-11 09:19:27,100 V5.B|▇ ▇| -2023-09-11 09:19:27,100 Q6.B|▇ ▇| -2023-09-11 09:19:27,100 V6.B|▇ ▇| -2023-09-11 09:19:27,100 Q7.B|▇ ▇| -2023-09-11 09:19:27,100 V7.B|▇ ▇| -2023-09-11 09:19:27,100 Q8.B|▇ ▇| -2023-09-11 09:19:27,100 V8.B|▇ ▇| -2023-09-11 09:19:27,100 Q9.B|▇ ▇| -2023-09-11 09:19:27,100 V9.B|▇ ▇| -2023-09-11 09:19:27,100 Q10.B|▇ ▇| -2023-09-11 09:19:27,100 V10.B|▇ ▇| -2023-09-11 09:19:27,100 Q11.B|▇ ▇| -2023-09-11 09:19:27,100 V11.B|▇ ▇| -2023-09-11 09:19:27,100 Q12.B|▇ ▇| -2023-09-11 09:19:27,100 V12.B|▇ ▇| -2023-09-11 09:19:27,100 Q13.B|▇ ▇| -2023-09-11 09:19:27,100 V13.B|▇ ▇| -2023-09-11 09:19:27,100 Q14.B|▇ ▇| -2023-09-11 09:19:27,100 V14.B|▇ ▇| -2023-09-11 09:19:27,100 Q15.B|▇ ▇| -2023-09-11 09:19:27,100 V15.B|▇ ▇| -2023-09-11 09:19:27,100 Q16.B|▇ ▇| -2023-09-11 09:19:27,100 V16.B|▇ ▇| -2023-09-11 09:19:27,100 Q17.B|▇ ▇| -2023-09-11 09:19:27,100 V17.B|▇ ▇| -2023-09-11 09:19:27,100 Q18.B|▇ ▇| -2023-09-11 09:19:27,100 V18.B|▇ ▇| -2023-09-11 09:19:27,100 Q19.B|▇ ▇| -2023-09-11 09:19:27,100 V19.B|▇ ▇| -2023-09-11 09:19:27,100 Q20.B|▇ ▇| -2023-09-11 09:19:27,100 V20.B|▇ ▇| -2023-09-11 09:19:27,100 Q21.B|▇ ▇| -2023-09-11 09:19:27,100 V21.B|▇ ▇| -2023-09-11 09:19:27,100 Q22.B|▇ ▇| -2023-09-11 09:19:27,100 V22.B|▇ ▇| -2023-09-11 09:19:27,100 Q23.B|▇ ▇| -2023-09-11 09:19:27,100 V23.B|▇ ▇| -2023-09-11 09:19:27,100 Q24.B|▇ ▇| -2023-09-11 09:19:27,100 V24.B|▇ ▇| -2023-09-11 09:19:27,100 Q25.B|▇ ▇| -2023-09-11 09:19:27,101 V25.B|▇ ▇| -2023-09-11 09:19:27,101 Q26.B|▇ ▇| -2023-09-11 09:19:27,101 V26.B|▇ ▇| -2023-09-11 09:19:27,101 Q27.B|▇ ▇| -2023-09-11 09:19:27,101 V27.B|▇ ▇| -2023-09-11 09:19:27,101 Q28.B|▇ ▇| -2023-09-11 09:19:27,101 V28.B|▇ ▇| -2023-09-11 09:19:27,101 Q29.B|▇ ▇| -2023-09-11 09:19:27,101 V29.B|▇ ▇| -2023-09-11 09:19:27,101 Q30.B|▇ ▇| -2023-09-11 09:19:27,101 V30.B|▇ ▇| -2023-09-11 09:19:27,101 Q31.B|▇ ▇| -2023-09-11 09:19:27,101 V31.B|▇ ▇| -2023-09-11 09:19:27,119 backprop done, loss after forward pass = 2.9539270401000977 -2023-09-11 09:19:27,119 starting iteration 1 -2023-09-11 09:19:48,372 -=== WEIGHTS A === -2023-09-11 09:19:48,840 ~~~~~~~~~~~ -0.0157|~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~|0.0157 -2023-09-11 09:19:48,841 Q0.A|▆▇▇▇▇▇▇▇▇▇▇▇▇▆▇▆▇▇▆▇▇▇▇▆▇▇▇▇▇▇▆▇▇▆▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▆| -2023-09-11 09:19:48,841 V0.A|▆▆▇▇▇▇▇▇▆▆▆▇▇▆▆▆▇▆▆▇▇▆▇▆▇▇▆▇▇▇▆▆▇▆▆▇▇▆▇▇▇▆▆▇▇▆▇▇▇▆▇▇▇▇▇▇▇▇▇▅| -2023-09-11 09:19:48,841 Q1.A|▆▇▇▇▇▇▇▇▇▇▆▇▇▇▇▆▇▇▇▆▇▇▇▇▇▆▇▆▇▆▇▇▇▇▇▇▇▇▇▆▇▆▇▇▇▇▇▆▇▆▇▇▇▇▆▇▇▇▇▆| -2023-09-11 09:19:48,841 V1.A|▆▆▇▆▇▇▆▇▇▆▇▇▇▆▇▇▆▇▇▆▇▇▇▆▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▆▇▇▆▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆| -2023-09-11 09:19:48,841 Q2.A|▆▇▇▇▇▆▇▇▇▇▆▇▆▆▇▇▇▇▇▇▆▇▇▇▇▆▇▇▆▇▇▇▇▆▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▆| -2023-09-11 09:19:48,841 V2.A|▅▇▆▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆| -2023-09-11 09:19:48,841 Q3.A|▆▇▇▆▇▆▇▇▆▇▇▇▆▇▇▇▆▇▇▇▇▆▇▇▇▆▇▇▇▇▇▆▇▆▇▇▇▆▇▆▇▇▇▇▇▇▆▇▆▇▇▇▆▇▇▇▆▇▆▅| -2023-09-11 09:19:48,841 V3.A|▆▇▇▇▇▇▇▇▇▆▇▇▆▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▆▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▆▇▆▆| -2023-09-11 09:19:48,841 Q4.A|▆▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▆▇▇▆▇▆▇▇▆▇▇▆▇▆▆▇▆▇▇▇▇▇▇▆▇▇▇▆▆| -2023-09-11 09:19:48,841 V4.A|▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▆| -2023-09-11 09:19:48,841 Q5.A|▆▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▆▇▇▅| -2023-09-11 09:19:48,841 V5.A|▅▆▇▇▆▇▆▆▇▆▇▇▆▇▇▇▆▇▇▇▇▆▇▇▆▇▆▇▇▇▆▇▇▇▇▇▆▇▆▆▆▆▆▇▇▆▆▇▇▆▇▇▇▇▇▇▇▇▇▆| -2023-09-11 09:19:48,841 Q6.A|▆▆▇▇▇▆▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▆▆▇▇▇▆▇▇▇▇▇▇▇▆| -2023-09-11 09:19:48,841 V6.A|▅▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▆▆▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▆▇▇▇▆| -2023-09-11 09:19:48,841 Q7.A|▅▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▆▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▆▇▇▇▇▇▇▆| -2023-09-11 09:19:48,841 V7.A|▆▇▇▆▇▆▇▇▇▇▇▇▇▆▇▇▇▇▇▆▇▆▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▅| -2023-09-11 09:19:48,841 Q8.A|▆▇▆▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▆▇▆▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▆▇▇▆| -2023-09-11 09:19:48,841 V8.A|▆▆▇▆▆▆▇▇▇▆▆▆▇▇▇▇▆▆▇▆▇▇▇▆▇▇▇▇▇▇▆▆▇▆▇▇▇▇▇▇▆▇▆▇▇▆▇▇▇▆▆▇▆▇▇▆▇▇▇▅| -2023-09-11 09:19:48,841 Q9.A|▆▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆| -2023-09-11 09:19:48,841 V9.A|▆▇▇▆▇▇▇▆▇▇▇▆▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▆▆▇▇▆▇▇▇▆▇▇▇▇▇▆▇▇▇▆▇▇▇▇▆▇▇▆| -2023-09-11 09:19:48,841 Q10.A|▆▇▇▆▆▆▇▆▇▇▇▇▆▇▇▇▇▇▇▇▆▇▆▇▇▆▇▇▆▇▆▇▇▆▇▇▇▆▆▇▇▇▇▇▆▆▇▇▇▇▆▆▇▆▇▇▆▆▆▆| -2023-09-11 09:19:48,841 V10.A|▆▇▇▇▆▇▆▇▇▇▇▇▇▇▆▆▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▆▆▇▇▇▇▇▆▇▆▇▇▆▇▇▇▇▇▇▇▇▆| -2023-09-11 09:19:48,841 Q11.A|▆▇▇▇▇▇▇▇▇▇▇▆▇▇▆▇▇▇▇▇▇▇▆▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▆▇▇▇▇▇▇▇▇▆| -2023-09-11 09:19:48,841 V11.A|▆▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▆▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▆▇▇▆| -2023-09-11 09:19:48,841 Q12.A|▆▆▆▆▇▇▇▇▇▆▇▆▇▇▆▆▇▆▇▇▇▇▆▇▇▇▆▆▇▇▇▇▆▇▇▆▇▇▆▇▇▆▇▇▆▇▆▆▆▆▆▇▆▆▇▆▇▆▇▅| -2023-09-11 09:19:48,841 V12.A|▅▇▇▇▇▇▇▆▇▇▇▆▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆| -2023-09-11 09:19:48,841 Q13.A|▆▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▆▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▆▇▇▆▇▇▇▆▇▇▇▆▇▇▇▆▆| -2023-09-11 09:19:48,841 V13.A|▆▇▆▇▇▇▆▆▇▇▇▇▇▇▇▆▇▇▇▆▇▆▆▇▆▆▇▇▇▇▆▇▇▇▇▇▆▆▆▇▆▇▆▇▆▇▆▇▇▇▇▇▇▇▆▇▇▇▇▆| -2023-09-11 09:19:48,841 Q14.A|▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▆▆▇▇▇▇▆▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▆▇▇▇▆▇▇▆| -2023-09-11 09:19:48,841 V14.A|▅▆▇▇▆▇▆▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆| -2023-09-11 09:19:48,841 Q15.A|▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▆| -2023-09-11 09:19:48,841 V15.A|▅▆▇▇▆▇▆▆▆▆▆▇▇▆▆▇▇▆▇▆▇▆▆▆▆▆▇▇▆▆▆▆▆▆▇▇▆▆▇▇▆▆▆▆▆▆▆▇▇▆▆▇▇▆▇▇▆▆▇▅| -2023-09-11 09:19:48,841 Q16.A|▆▇▆▇▇▆▇▇▇▇▇▇▇▇▆▇▆▇▇▇▆▇▇▇▇▆▇▇▇▆▆▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▆▅| -2023-09-11 09:19:48,841 V16.A|▆▆▇▆▇▇▇▇▇▇▇▇▇▇▆▇▆▆▇▇▇▇▆▆▇▇▆▇▇▇▇▇▇▇▆▇▆▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▆▇▆▇▇▇▇▅| -2023-09-11 09:19:48,841 Q17.A|▅▇▇▆▆▆▇▇▆▇▇▇▇▇▇▇▇▇▇▇▆▇▆▇▆▇▇▇▆▇▇▆▇▇▇▆▇▆▆▇▇▇▆▇▆▇▇▆▇▇▇▇▆▇▆▇▆▇▇▆| -2023-09-11 09:19:48,841 V17.A|▆▇▆▆▆▇▇▇▇▇▆▆▇▇▇▆▇▇▆▆▇▇▇▆▇▆▇▆▆▇▆▆▇▆▆▆▇▆▇▆▇▇▆▇▆▇▆▇▇▇▇▆▇▆▇▇▇▇▇▅| -2023-09-11 09:19:48,841 Q18.A|▆▇▆▇▇▇▆▇▇▇▆▇▇▇▇▇▆▆▇▇▆▆▇▇▇▇▆▆▇▆▇▇▆▇▇▇▇▆▆▇▇▆▇▆▇▇▇▆▇▆▇▇▆▇▆▇▇▇▇▆| -2023-09-11 09:19:48,841 V18.A|▆▇▇▇▇▇▇▇▇▇▆▇▇▆▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▆▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▆▇▇▆▇▇▇▇▇▇▅| -2023-09-11 09:19:48,841 Q19.A|▅▆▆▇▇▇▇▇▇▇▇▆▇▇▇▆▆▇▆▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▆▆▇▆▆▆▇▆▆▆▇▇▇▆▆▆▇▇▇▆▇▆▇▆▆▅| -2023-09-11 09:19:48,841 V19.A|▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▆▇▇▇▇▆▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▆▆▇▇▇▇▇▇▆▇▆▇▆▇▇▇▇▇▆| -2023-09-11 09:19:48,841 Q20.A|▆▆▆▆▆▇▆▇▇▆▆▆▆▇▇▇▇▆▇▇▆▆▇▆▆▆▇▆▇▇▆▆▆▆▆▆▇▇▇▇▆▆▇▇▇▆▆▇▇▆▆▆▆▇▇▇▇▆▇▆| -2023-09-11 09:19:48,841 V20.A|▆▆▇▇▆▇▇▇▇▇▆▆▆▆▇▇▆▇▆▇▆▆▆▆▇▇▇▇▇▇▇▆▆▇▆▇▇▇▆▆▆▇▇▇▇▆▇▇▇▇▇▆▇▇▇▇▇▆▆▆| -2023-09-11 09:19:48,841 Q21.A|▆▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▆▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▆▇▇▇▇▇▇▇▇▆▇▇▆▇▆| -2023-09-11 09:19:48,841 V21.A|▆▆▇▆▇▆▆▆▇▇▇▇▇▆▆▇▆▆▇▆▇▇▇▆▆▇▇▇▇▆▆▇▇▆▇▇▆▆▇▇▇▇▇▇▇▇▇▇▆▇▆▇▆▆▆▇▇▇▇▅| -2023-09-11 09:19:48,841 Q22.A|▆▇▇▇▇▇▆▇▇▇▇▇▆▆▇▇▇▇▇▇▆▆▇▆▆▇▇▆▆▆▇▇▇▇▇▇▇▇▇▆▇▇▇▆▇▇▇▇▆▆▇▇▆▇▇▇▇▆▇▆| -2023-09-11 09:19:48,841 V22.A|▅▇▇▇▆▆▇▆▇▇▇▇▇▇▆▇▇▆▆▆▇▆▆▇▆▇▇▆▆▇▇▇▇▇▇▇▇▇▆▇▆▆▆▇▇▇▆▇▆▆▇▇▇▆▇▇▆▇▆▆| -2023-09-11 09:19:48,841 Q23.A|▆▇▇▇▇▆▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆| -2023-09-11 09:19:48,841 V23.A|▅▆▇▆▇▆▆▇▇▇▇▆▇▆▆▇▇▇▇▆▆▇▆▇▇▇▇▆▇▇▇▇▇▆▆▇▇▇▆▆▇▇▆▇▇▇▆▇▇▇▇▇▇▇▇▆▇▇▇▅| -2023-09-11 09:19:48,841 Q24.A|▆▇▇▆▆▇▇▇▇▇▇▇▇▇▆▇▇▇▆▇▇▆▇▇▇▇▆▇▆▇▇▆▆▆▇▇▆▇▆▇▇▆▇▇▇▇▇▇▇▆▇▆▆▇▇▇▇▆▇▆| -2023-09-11 09:19:48,841 V24.A|▆▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▆▆▆▇▇▇▇▇▇▇▆▇▆▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆| -2023-09-11 09:19:48,841 Q25.A|▆▇▇▇▆▇▇▆▆▇▆▇▇▆▆▇▆▆▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▆▇▇▇▇▇▆▇▇▆▇▇▇▇▇▆| -2023-09-11 09:19:48,841 V25.A|▆▇▆▇▇▆▇▇▆▇▆▇▇▆▆▇▆▇▆▆▇▇▇▇▇▇▆▇▆▇▇▆▇▆▇▆▆▇▇▆▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▆| -2023-09-11 09:19:48,841 Q26.A|▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▆▇▇▇▇▇▇▇▇▇▇▇▇▆| -2023-09-11 09:19:48,841 V26.A|▆▆▇▇▇▇▇▇▇▆▇▆▆▇▇▇▇▇▇▇▆▇▇▇▇▆▇▇▆▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▆▇▇▇▇▇▆▇▇▇▇▆| -2023-09-11 09:19:48,841 Q27.A|▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▅| -2023-09-11 09:19:48,841 V27.A|▆▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▆▇▇▇▆▇▇▇▇▇▇▇▆▇▇▇▇▇▇▆| -2023-09-11 09:19:48,841 Q28.A|▆▇▇▇▇▇▇▇▇▇▇▇▆▆▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▆▇▆▇▇▇▇▇▇▆▇▇▇▇▇▇▇▆▇▇▇▇▆▇▇▇▅| -2023-09-11 09:19:48,841 V28.A|▆▇▇▇▇▆▇▇▆▇▇▇▆▇▇▆▇▇▆▇▆▇▆▇▇▆▇▇▆▆▇▇▆▇▆▇▇▆▇▇▇▇▇▆▇▇▇▇▆▇▆▇▆▇▇▇▇▇▇▆| -2023-09-11 09:19:48,841 Q29.A|▆▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▆▆▇▇▇▇▆▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▅| -2023-09-11 09:19:48,841 V29.A|▆▆▇▆▇▇▇▆▆▇▆▇▇▇▇▇▇▆▇▆▇▇▆▇▇▇▇▇▆▇▇▆▇▇▇▇▇▇▆▇▇▇▆▇▆▇▇▇▇▇▆▇▇▇▇▇▆▇▇▆| -2023-09-11 09:19:48,841 Q30.A|▅▇▇▇▇▆▇▇▆▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▆| -2023-09-11 09:19:48,841 V30.A|▅▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▆▆▇▇▆▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▆| -2023-09-11 09:19:48,841 Q31.A|▅▇▇▇▆▆▇▇▇▇▇▆▇▆▇▆▇▆▇▇▇▆▇▇▇▆▇▇▆▇▇▆▇▇▇▇▇▆▆▆▇▆▇▇▆▆▇▇▇▆▇▆▇▇▆▇▇▆▇▆| -2023-09-11 09:19:48,842 V31.A|▅▆▇▆▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▆▇▆▆▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▆▆▇▇▇▇▇▇▇▆▇▆| -2023-09-11 09:19:48,842 -=== WEIGHTS B === -2023-09-11 09:19:49,326 ~~~~~~~~~~~ -0.0002|~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~|0.0002 -2023-09-11 09:19:49,326 Q0.B|▇▂▁▁ ▁▁▂▇| -2023-09-11 09:19:49,326 V0.B|▇▂▁▁ ▁▂▇| -2023-09-11 09:19:49,326 Q1.B|▇▂▁▁ ▁▁▂▇| -2023-09-11 09:19:49,326 V1.B|▇▂▁ ▁▂▇| -2023-09-11 09:19:49,326 Q2.B|▇▂▁▁ ▁▁▂▇| -2023-09-11 09:19:49,326 V2.B|▇▂▁ ▁▂▇| -2023-09-11 09:19:49,326 Q3.B|▇▂▁▁ ▁▁▂▇| -2023-09-11 09:19:49,326 V3.B|▇▂▁ ▁▂▇| -2023-09-11 09:19:49,326 Q4.B|▇▂▁▁ ▁▁▂▇| -2023-09-11 09:19:49,326 V4.B|▇▂▁ ▁▂▇| -2023-09-11 09:19:49,326 Q5.B|▇▂▁▁ ▁▁▂▇| -2023-09-11 09:19:49,326 V5.B|▇▂▁ ▁▂▇| -2023-09-11 09:19:49,326 Q6.B|▇▂▁ ▁▁▂▇| -2023-09-11 09:19:49,326 V6.B|▇▂▁ ▁▂▇| -2023-09-11 09:19:49,326 Q7.B|▇▂▁▁ ▁▁▂▇| -2023-09-11 09:19:49,326 V7.B|▇▂▁ ▁▁▇| -2023-09-11 09:19:49,326 Q8.B|▇▂▁ ▁▂▇| -2023-09-11 09:19:49,326 V8.B|▇▂▁ ▁▂▇| -2023-09-11 09:19:49,326 Q9.B|▇▂▁▁ ▁▂▇| -2023-09-11 09:19:49,326 V9.B|▇▂▁ ▁▁▇| -2023-09-11 09:19:49,326 Q10.B|▇▂▁ ▁▂▇| -2023-09-11 09:19:49,326 V10.B|▇▂▁ ▁▂▇| -2023-09-11 09:19:49,326 Q11.B|▇▂▁ ▁▂▇| -2023-09-11 09:19:49,326 V11.B|▇▂▁ ▁▂▇| -2023-09-11 09:19:49,326 Q12.B|▇▂▁ ▁▂▇| -2023-09-11 09:19:49,326 V12.B|▇▁▁ ▁▂▇| -2023-09-11 09:19:49,326 Q13.B|▇▂▁ ▁▂▇| -2023-09-11 09:19:49,326 V13.B|▇▁▁ ▁▁▇| -2023-09-11 09:19:49,326 Q14.B|▇▂▁ ▁▂▇| -2023-09-11 09:19:49,326 V14.B|▇▂▁ ▁▂▇| -2023-09-11 09:19:49,326 Q15.B|▇▂▁ ▁▂▇| -2023-09-11 09:19:49,326 V15.B|▇▁▁ ▁▁▇| -2023-09-11 09:19:49,326 Q16.B|▇▂▁ ▁▂▇| -2023-09-11 09:19:49,326 V16.B|▇▁▁ ▁▁▇| -2023-09-11 09:19:49,326 Q17.B|▇▂▁ ▁▂▇| -2023-09-11 09:19:49,326 V17.B|▇▁ ▁▇| -2023-09-11 09:19:49,326 Q18.B|▇▂▁ ▁▂▇| -2023-09-11 09:19:49,326 V18.B|▇▁▁ ▁▁▇| -2023-09-11 09:19:49,326 Q19.B|▇▂▁ ▁▂▇| -2023-09-11 09:19:49,326 V19.B|▇▁ ▁▇| -2023-09-11 09:19:49,326 Q20.B|▇▂▁ ▁▂▇| -2023-09-11 09:19:49,326 V20.B|▇▁▁ ▁▁▇| -2023-09-11 09:19:49,326 Q21.B|▇▂▁ ▁▂▇| -2023-09-11 09:19:49,326 V21.B|▇▁▁ ▁▁▇| -2023-09-11 09:19:49,326 Q22.B|▇▁▁ ▁▁▇| -2023-09-11 09:19:49,326 V22.B|▇▁▁ ▁▁▇| -2023-09-11 09:19:49,326 Q23.B|▇▂▁ ▁▂▇| -2023-09-11 09:19:49,326 V23.B|▇▁▁ ▁▁▇| -2023-09-11 09:19:49,327 Q24.B|▇▂▁ ▁▂▇| -2023-09-11 09:19:49,327 V24.B|▇▁ ▁▁▇| -2023-09-11 09:19:49,327 Q25.B|▇▂▁ ▁▂▇| -2023-09-11 09:19:49,327 V25.B|▇▁▁ ▁▁▇| -2023-09-11 09:19:49,327 Q26.B|▇▂▁ ▁▂▇| -2023-09-11 09:19:49,327 V26.B|▇▁▁ ▁▂▇| -2023-09-11 09:19:49,327 Q27.B|▇▂▁ ▁▂▇| -2023-09-11 09:19:49,327 V27.B|▇▁▁ ▁▂▇| -2023-09-11 09:19:49,327 Q28.B|▇▂▁ ▁▂▇| -2023-09-11 09:19:49,327 V28.B|▇▂▁ ▁▂▇| -2023-09-11 09:19:49,327 Q29.B|▇▂▁ ▁▂▇| -2023-09-11 09:19:49,327 V29.B|▇▂▁ ▁▁▇| -2023-09-11 09:19:49,327 Q30.B|▇▂▁ ▁▂▇| -2023-09-11 09:19:49,327 V30.B|▇▂▁ ▁▂▇| -2023-09-11 09:19:49,327 Q31.B|▇▂▁ ▁▂▇| -2023-09-11 09:19:49,327 V31.B|▇▂▁ ▁▂▇| -2023-09-11 09:19:49,345 backprop done, loss after forward pass = 2.9073104858398438 -2023-09-11 09:19:49,345 saving snapshot -2023-09-11 09:19:49,392 starting iteration 2 -2023-09-11 09:20:10,670 -=== WEIGHTS A === -2023-09-11 09:20:11,137 ~~~~~~~~~~~ -0.0158|~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~|0.0158 -2023-09-11 09:20:11,138 Q0.A|▅▇▇▇▇▇▆▇▇▆▆▇▇▆▇▆▇▇▆▇▆▇▇▆▇▆▇▇▇▇▆▇▇▆▇▆▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▆▇▅| -2023-09-11 09:20:11,138 V0.A|▅▇▇▇▆▇▇▇▇▇▆▇▇▆▆▆▇▆▇▇▇▇▇▇▇▇▇▇▇▇▆▆▇▆▆▇▇▇▇▇▇▇▆▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▅| -2023-09-11 09:20:11,138 Q1.A|▅▇▇▇▇▇▇▇▇▇▆▇▇▇▇▆▇▆▇▆▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▅| -2023-09-11 09:20:11,138 V1.A|▅▆▇▆▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▅| -2023-09-11 09:20:11,138 Q2.A|▅▇▇▇▇▆▇▇▇▇▆▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▅| -2023-09-11 09:20:11,138 V2.A|▄▇▆▇▇▇▇▆▇▇▇▆▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▅| -2023-09-11 09:20:11,138 Q3.A|▅▇▇▆▇▇▇▇▆▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▆▆▇▇▇▇▇▆▇▇▇▇▇▇▆▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▆▆▇▇▄| -2023-09-11 09:20:11,138 V3.A|▅▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▆▅| -2023-09-11 09:20:11,138 Q4.A|▅▇▇▇▆▆▇▇▆▇▇▆▇▆▇▆▇▆▆▇▇▆▇▆▇▇▇▇▇▇▇▆▆▇▆▇▆▇▇▆▇▇▆▇▆▆▇▆▆▇▆▇▇▆▆▆▆▇▆▅| -2023-09-11 09:20:11,138 V4.A|▅▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▆▇▇▆▇▇▇▆▆▇▇▇▇▇▇▇▇▇▇▆▆▇▇▇▇▇▇▇▇▇▇▇▇▆▅| -2023-09-11 09:20:11,138 Q5.A|▄▇▇▇▇▇▇▇▇▆▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▆▇▆▇▇▇▄| -2023-09-11 09:20:11,138 V5.A|▄▆▇▇▆▇▇▆▇▆▇▇▇▇▇▇▆▇▇▇▇▆▇▇▇▇▆▇▇▇▇▇▇▇▇▇▆▇▆▆▇▆▆▇▇▆▆▇▇▆▇▇▇▆▇▇▇▇▇▅| -2023-09-11 09:20:11,138 Q6.A|▅▆▇▇▇▇▇▆▇▇▇▇▇▇▆▇▇▇▇▇▇▇▆▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▆▆▇▇▇▇▇▇▆▇▇▇▇▅| -2023-09-11 09:20:11,138 V6.A|▄▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▆▇▇▆▇▆▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▆▇▇▇▇▅| -2023-09-11 09:20:11,138 Q7.A|▄▇▇▇▆▇▇▇▇▆▇▇▇▇▇▇▇▇▆▆▆▇▇▆▇▆▆▇▇▇▆▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▆▇▇▇▇▇▇▅| -2023-09-11 09:20:11,138 V7.A|▄▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▆▆▇▆▇▆▆▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▄| -2023-09-11 09:20:11,138 Q8.A|▅▆▇▇▇▇▆▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▆▆▇▆▆▆▆▇▆▆▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▆▇▇▄| -2023-09-11 09:20:11,138 V8.A|▅▇▇▇▆▇▇▇▇▇▇▆▇▇▇▇▆▆▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▆▇▇▇▇▇▇▆▆▇▇▇▇▆▇▇▇▅| -2023-09-11 09:20:11,138 Q9.A|▅▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▆▆▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▅| -2023-09-11 09:20:11,138 V9.A|▅▇▇▆▇▇▆▆▇▇▇▆▆▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▆▇▆▆▇▇▆▇▇▇▆▇▇▇▇▇▆▇▇▇▆▇▇▆▇▆▇▇▅| -2023-09-11 09:20:11,138 Q10.A|▅▇▇▇▆▆▆▆▇▆▇▇▆▇▇▇▇▇▇▆▆▇▆▇▇▆▇▇▆▇▆▇▇▇▇▆▇▆▆▆▇▇▇▆▆▆▇▆▇▇▆▆▆▆▇▇▆▆▆▅| -2023-09-11 09:20:11,138 V10.A|▅▇▇▇▆▇▆▇▇▆▇▇▇▇▆▆▇▇▇▇▇▇▇▇▇▇▆▇▆▇▇▇▆▆▇▇▇▇▆▆▆▇▆▇▆▆▇▇▆▆▆▇▆▇▇▇▇▆▇▅| -2023-09-11 09:20:11,138 Q11.A|▅▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▆▇▇▇▇▇▆▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▆▇▇▇▆▇▇▇▇▇▇▇▇▅| -2023-09-11 09:20:11,138 V11.A|▅▆▇▆▇▆▇▆▇▇▇▇▇▇▇▇▆▆▇▇▆▇▇▇▇▇▇▆▇▆▇▆▇▆▇▇▆▇▇▇▇▇▇▆▇▇▆▇▆▇▇▇▇▇▇▇▆▇▇▄| -2023-09-11 09:20:11,138 Q12.A|▅▇▇▆▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▆▆▆▇▇▇▇▇▇▆▇▇▇▅| -2023-09-11 09:20:11,138 V12.A|▄▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▅| -2023-09-11 09:20:11,138 Q13.A|▅▇▇▇▇▇▆▇▇▇▇▇▇▇▇▆▆▇▇▇▇▇▇▇▇▇▇▇▆▇▇▆▇▆▇▇▇▇▇▇▇▇▆▇▇▇▆▇▆▇▇▇▇▇▆▇▇▇▆▅| -2023-09-11 09:20:11,138 V13.A|▄▇▆▇▇▇▆▆▇▇▇▇▇▇▇▆▇▇▇▆▇▆▆▇▆▆▇▇▆▇▆▇▇▆▇▇▆▆▆▇▆▇▇▇▆▇▇▇▇▇▇▇▆▆▇▇▆▆▇▅| -2023-09-11 09:20:11,138 Q14.A|▅▆▆▇▇▆▇▇▆▆▇▇▇▆▇▇▇▇▆▆▆▇▆▇▆▆▆▆▆▇▇▆▆▆▆▆▆▇▆▇▆▇▆▆▇▇▇▇▆▆▆▆▆▇▆▆▆▇▇▄| -2023-09-11 09:20:11,138 V14.A|▄▆▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▄| -2023-09-11 09:20:11,138 Q15.A|▅▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▆▇▇▆▇▇▇▇▇▇▇▇▇▇▅| -2023-09-11 09:20:11,138 V15.A|▄▇▇▇▆▇▆▇▆▆▆▇▇▇▆▇▇▆▇▆▇▆▆▇▆▆▆▇▇▇▆▆▆▆▇▇▆▇▆▇▆▆▇▆▆▆▇▇▇▆▆▇▇▇▇▇▆▆▇▄| -2023-09-11 09:20:11,138 Q16.A|▅▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▆▆▇▇▆▇▇▇▇▆▇▇▇▆▇▇▆▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▆▇▇▆▄| -2023-09-11 09:20:11,138 V16.A|▅▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▆▇▆▇▇▇▆▇▇▇▆▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▅| -2023-09-11 09:20:11,138 Q17.A|▄▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▅| -2023-09-11 09:20:11,138 V17.A|▄▇▆▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▆▇▆▆▇▆▆▇▆▇▇▇▇▆▇▇▇▇▇▇▇▇▆▇▆▇▇▇▇▇▅| -2023-09-11 09:20:11,138 Q18.A|▄▇▆▇▆▇▆▇▇▇▆▇▇▇▇▆▇▇▇▇▇▆▇▇▇▆▇▆▆▆▇▇▆▇▇▇▇▆▆▇▇▆▇▆▇▇▆▆▇▆▇▇▇▆▆▇▇▇▇▅| -2023-09-11 09:20:11,138 V18.A|▄▇▇▆▇▆▇▇▇▇▇▇▆▆▇▆▇▆▆▇▇▇▆▆▆▇▇▇▇▆▇▆▇▇▆▇▇▇▇▆▇▇▇▆▇▇▆▇▆▆▇▇▆▇▇▆▇▆▆▄| -2023-09-11 09:20:11,138 Q19.A|▄▇▆▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▆▆▇▇▇▇▆▇▆▇▇▆▇▇▆▇▆▆▄| -2023-09-11 09:20:11,138 V19.A|▅▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▅| -2023-09-11 09:20:11,138 Q20.A|▅▇▆▇▇▇▆▇▇▇▆▆▆▇▇▇▇▇▇▇▇▆▇▇▆▇▇▆▇▇▇▆▆▆▇▇▇▇▇▇▆▇▇▇▇▆▇▇▇▇▆▇▇▇▇▇▇▇▇▅| -2023-09-11 09:20:11,138 V20.A|▄▇▆▇▆▇▆▇▆▇▆▆▆▆▇▇▆▇▆▇▆▆▆▆▇▇▇▇▇▇▇▆▇▇▆▆▇▇▇▆▆▇▇▇▇▆▇▇▇▇▇▆▇▇▇▇▇▆▆▅| -2023-09-11 09:20:11,138 Q21.A|▅▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▆▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▆▇▅| -2023-09-11 09:20:11,138 V21.A|▄▇▇▇▇▆▆▇▇▆▇▇▇▇▆▇▆▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▆▆▇▇▇▇▇▄| -2023-09-11 09:20:11,138 Q22.A|▅▇▇▇▇▇▆▇▇▇▇▇▆▆▇▇▇▇▇▇▆▆▇▆▆▇▇▇▆▆▇▇▇▆▇▇▇▇▇▆▇▇▇▆▇▆▇▇▇▆▇▇▇▇▇▇▇▆▇▅| -2023-09-11 09:20:11,138 V22.A|▅▇▇▇▆▇▆▇▇▇▇▇▇▇▇▇▇▇▆▆▇▆▇▇▆▇▆▇▆▇▇▇▆▇▇▇▇▇▆▇▆▆▇▇▇▇▆▆▇▆▇▇▇▆▇▇▇▇▆▅| -2023-09-11 09:20:11,138 Q23.A|▅▆▇▇▇▆▆▆▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▅| -2023-09-11 09:20:11,138 V23.A|▅▇▇▇▇▇▆▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▆▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▅| -2023-09-11 09:20:11,138 Q24.A|▅▇▇▆▆▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▆▇▇▇▇▆▇▇▇▇▆▆▇▇▇▇▇▆▇▇▆▇▇▇▇▇▇▇▆▇▆▆▇▇▇▆▆▇▅| -2023-09-11 09:20:11,138 V24.A|▅▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▆▆▆▆▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▅| -2023-09-11 09:20:11,138 Q25.A|▅▇▇▇▆▇▇▆▇▇▆▇▇▆▆▆▇▆▇▇▇▆▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▆▇▇▆▇▇▇▇▇▆▇▇▆▇▇▇▇▇▅| -2023-09-11 09:20:11,138 V25.A|▅▇▇▆▇▆▇▇▆▇▆▇▇▆▆▇▇▇▇▆▇▇▇▇▇▇▇▇▆▇▇▆▇▆▇▆▆▇▇▆▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▅| -2023-09-11 09:20:11,138 Q26.A|▅▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▆▇▇▇▇▇▇▇▆▇▇▆▇▇▇▇▆▆▇▇▇▇▇▇▇▇▇▇▇▇▅| -2023-09-11 09:20:11,138 V26.A|▅▇▆▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▅| -2023-09-11 09:20:11,138 Q27.A|▅▇▇▇▇▇▇▇▆▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▆▆▇▇▆▇▇▇▇▆▇▇▇▇▆▆▇▇▇▇▇▇▆▇▇▇▇▄| -2023-09-11 09:20:11,138 V27.A|▄▇▇▇▆▇▇▇▆▇▇▇▇▇▇▇▆▇▇▇▇▇▇▆▇▆▇▇▇▇▇▇▇▇▇▇▆▇▇▆▆▇▇▇▆▇▇▇▇▇▇▇▆▇▇▇▇▇▇▅| -2023-09-11 09:20:11,138 Q28.A|▅▇▇▇▇▇▇▇▆▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▄| -2023-09-11 09:20:11,138 V28.A|▅▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▅| -2023-09-11 09:20:11,138 Q29.A|▄▇▇▆▆▆▆▆▇▆▆▇▇▆▆▇▆▆▆▇▆▆▇▆▆▆▆▇▆▇▇▆▆▆▇▆▆▆▆▆▆▆▇▆▆▆▆▇▆▆▆▇▇▆▇▇▆▇▇▄| -2023-09-11 09:20:11,138 V29.A|▄▆▇▆▇▇▇▆▇▇▆▇▇▇▇▇▇▇▇▆▇▇▆▇▇▇▇▇▆▆▇▆▇▇▇▇▇▇▆▇▇▇▆▆▇▇▆▇▇▇▆▇▇▇▇▇▇▇▇▅| -2023-09-11 09:20:11,138 Q30.A|▄▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▅| -2023-09-11 09:20:11,138 V30.A|▄▇▇▇▆▇▇▇▇▇▇▇▇▆▇▇▇▇▆▇▇▆▇▇▇▆▇▇▆▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▆▇▇▅| -2023-09-11 09:20:11,138 Q31.A|▄▇▇▇▆▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▆▇▇▇▇▇▆▇▇▇▆▇▇▇▆▇▇▇▇▇▇▇▇▆▇▇▇▇▅| -2023-09-11 09:20:11,138 V31.A|▄▆▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▇▆▇▇▆▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇▆▇▇▇▇▇▇▇▆▇▅| -2023-09-11 09:20:11,139 -=== WEIGHTS B === -2023-09-11 09:20:11,620 ~~~~~~~~~~~ -0.0003|~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~|0.0003 -2023-09-11 09:20:11,620 Q0.B|▇▄▃▂▁▁▁▁ ▁▁▁▁▂▂▄▇| -2023-09-11 09:20:11,620 V0.B|▇▄▃▂▁▁ ▁▁▂▂▄▇| -2023-09-11 09:20:11,620 Q1.B|▇▅▃▂▁▁▁▁ ▁▁▁▁▂▃▄▇| -2023-09-11 09:20:11,620 V1.B|▇▃▂▁▁ ▁▁▂▃▇| -2023-09-11 09:20:11,620 Q2.B|▇▄▃▂▁▁▁ ▁▁▁▂▃▄▇| -2023-09-11 09:20:11,620 V2.B|▇▃▂▁▁ ▁▁▂▃▇| -2023-09-11 09:20:11,620 Q3.B|▇▄▂▂▁▁▁ ▁▁▁▂▂▄▇| -2023-09-11 09:20:11,620 V3.B|▇▃▂▁ ▁▂▃▇| -2023-09-11 09:20:11,620 Q4.B|▇▄▂▂▁▁ ▁▁▂▂▄▇| -2023-09-11 09:20:11,620 V4.B|▇▃▂▁ ▁▂▃▇| -2023-09-11 09:20:11,620 Q5.B|▇▃▂▂▁▁ ▁▁▂▂▃▇| -2023-09-11 09:20:11,620 V5.B|▇▃▂▁ ▁▂▃▇| -2023-09-11 09:20:11,620 Q6.B|▇▃▂▁▁ ▁▁▂▃▇| -2023-09-11 09:20:11,620 V6.B|▇▃▂▁ ▁▁▂▃▇| -2023-09-11 09:20:11,620 Q7.B|▇▃▂▁▁▁ ▁▁▁▂▃▇| -2023-09-11 09:20:11,620 V7.B|▇▃▁▁ ▁▁▂▇| -2023-09-11 09:20:11,620 Q8.B|▇▃▂▁▁ ▁▁▂▃▇| -2023-09-11 09:20:11,620 V8.B|▇▃▁▁ ▁▁▃▇| -2023-09-11 09:20:11,620 Q9.B|▇▃▂▁▁ ▁▁▂▃▇| -2023-09-11 09:20:11,620 V9.B|▇▂▁▁ ▁▁▂▇| -2023-09-11 09:20:11,620 Q10.B|▇▃▂▁▁ ▁▁▂▃▇| -2023-09-11 09:20:11,620 V10.B|▇▃▂▁ ▁▂▃▇| -2023-09-11 09:20:11,620 Q11.B|▇▃▂▁▁ ▁▁▂▃▇| -2023-09-11 09:20:11,620 V11.B|▇▂▁▁ ▁▁▂▇| -2023-09-11 09:20:11,620 Q12.B|▇▃▂▁▁ ▁▁▂▃▇| -2023-09-11 09:20:11,620 V12.B|▇▂▁▁ ▁▁▃▇| -2023-09-11 09:20:11,620 Q13.B|▇▃▂▁▁ ▁▂▃▇| -2023-09-11 09:20:11,620 V13.B|▇▂▁▁ ▁▁▂▇| -2023-09-11 09:20:11,620 Q14.B|▇▃▂▁▁ ▁▁▂▃▇| -2023-09-11 09:20:11,620 V14.B|▇▃▁▁ ▁▁▃▇| -2023-09-11 09:20:11,620 Q15.B|▇▃▁▁ ▁▁▃▇| -2023-09-11 09:20:11,620 V15.B|▇▂▁▁ ▁▁▂▇| -2023-09-11 09:20:11,620 Q16.B|▇▃▁▁ ▁▁▁▃▇| -2023-09-11 09:20:11,620 V16.B|▇▂▁▁ ▁▁▂▇| -2023-09-11 09:20:11,620 Q17.B|▇▃▂▁ ▁▂▃▇| -2023-09-11 09:20:11,620 V17.B|▇▂▁ ▁▂▇| -2023-09-11 09:20:11,620 Q18.B|▇▃▁▁ ▁▁▂▇| -2023-09-11 09:20:11,620 V18.B|▇▂▁ ▁▂▇| -2023-09-11 09:20:11,620 Q19.B|▇▃▁▁ ▁▁▃▇| -2023-09-11 09:20:11,620 V19.B|▇▂▁ ▁▂▇| -2023-09-11 09:20:11,620 Q20.B|▇▃▂▁▁ ▁▁▂▃▇| -2023-09-11 09:20:11,620 V20.B|▇▂▁▁ ▁▁▂▇| -2023-09-11 09:20:11,620 Q21.B|▇▃▂▁▁ ▁▁▂▃▇| -2023-09-11 09:20:11,620 V21.B|▇▂▁▁ ▁▁▂▇| -2023-09-11 09:20:11,620 Q22.B|▇▂▁▁ ▁▁▂▇| -2023-09-11 09:20:11,620 V22.B|▇▂▁▁ ▁▁▂▇| -2023-09-11 09:20:11,620 Q23.B|▇▃▁▁▁ ▁▁▃▇| -2023-09-11 09:20:11,620 V23.B|▇▂▁▁ ▁▁▂▇| -2023-09-11 09:20:11,620 Q24.B|▇▃▂▁▁ ▁▁▂▃▇| -2023-09-11 09:20:11,620 V24.B|▇▂▁▁ ▁▁▂▇| -2023-09-11 09:20:11,621 Q25.B|▇▃▁▁ ▁▁▃▇| -2023-09-11 09:20:11,621 V25.B|▇▂▁▁ ▁▁▂▇| -2023-09-11 09:20:11,621 Q26.B|▇▃▁▁ ▁▁▃▇| -2023-09-11 09:20:11,621 V26.B|▇▃▁▁ ▁▁▃▇| -2023-09-11 09:20:11,621 Q27.B|▇▃▁▁ ▁▁▂▇| -2023-09-11 09:20:11,621 V27.B|▇▂▁▁ ▁▁▂▇| -2023-09-11 09:20:11,621 Q28.B|▇▃▂▁▁ ▁▁▂▃▇| -2023-09-11 09:20:11,621 V28.B|▇▃▁▁ ▁▁▃▇| -2023-09-11 09:20:11,621 Q29.B|▇▃▁▁ ▁▁▃▇| -2023-09-11 09:20:11,621 V29.B|▇▂▁▁ ▁▁▂▇| -2023-09-11 09:20:11,621 Q30.B|▇▃▂▁▁ ▁▁▂▃▇| -2023-09-11 09:20:11,621 V30.B|▇▃▂▁▁ ▁▂▃▇| -2023-09-11 09:20:11,621 Q31.B|▇▃▂▁▁ ▁▁▂▃▇| -2023-09-11 09:20:11,621 V31.B|▇▃▁▁ ▁▁▃▇| -``` \ No newline at end of file diff --git a/mac/slowllama/slowllama/e2e7b.sh b/mac/slowllama/slowllama/e2e7b.sh deleted file mode 100755 index 14bcd5a..0000000 --- a/mac/slowllama/slowllama/e2e7b.sh +++ /dev/null @@ -1,6 +0,0 @@ -# end-to-end test with llama7b. -# TODO: improve to clean up last iter and make it take some params -python prepare_model.py -python test_gen.py -python finetune.py -python test_gen.py ./out/state_dict_19.pth diff --git a/mac/slowllama/slowllama/finetune.py b/mac/slowllama/slowllama/finetune.py deleted file mode 100644 index 4da2ace..0000000 --- a/mac/slowllama/slowllama/finetune.py +++ /dev/null @@ -1,58 +0,0 @@ -import os -import torch -import logging - -from llama2_loader import load_frozen -from plot_lora import log_lora -from utils import Tokenizer, greedy_gen - -from conf_fp16 import * - -if __name__ == '__main__': - logging.basicConfig(format='%(asctime)s %(message)s', level=log_level, filename='logs/finetune.log') - torch.random.manual_seed(seed) - - if not os.path.exists(snapshots_path): - os.makedirs(snapshots_path) - - # data to finetune on - with open(finetune_file) as f: - text = f.read() - - tokenizer = Tokenizer(os.path.join(frozen_model_path, 'tokenizer.model')) - tokens = tokenizer.encode(text, True, True) - - logging.info(f'loaded dataset: {len(tokens)} tokens') - - model = load_frozen(frozen_model_path, compute_dtype=compute_dtype, lora_rank=lora_rank, frozen_dtype=frozen_dtype).to(device).to(compute_dtype) - - def get_batch(batch_size): - index = torch.randint(len(tokens) - seq_len, (batch_size,)) - x = torch.stack([torch.tensor(tokens[i:i + seq_len]).to(torch.int64) for i in index]) - y = torch.stack([torch.tensor(tokens[i + 1:i + seq_len + 1]).to(torch.int64) for i in index]) - return x.to(device), y.to(device) - - opt = torch.optim.AdamW(model.parameters(), lr=lr, eps=adamw_eps) - - last_loss = None - for i in range(iters): - if i % eval_period == 0 and (i > 0 or eval_before_training): - greedy_gen(model, tokenizer, device, prompt, gen_tokens) - logging.info(f'starting iteration {i}') - X, y = get_batch(batch_size) - opt.zero_grad() - # both forward and backward passes are here. - # returned loss is a scalar, not variable - loss = model.manual_loop(X, y) - opt.step() - - # optional logging of lora weights/gradients - log_lora(model.lora_layers, log_weights=log_lora_weight, log_grad=log_lora_grad) - - logging.info(f'backprop done, loss after forward pass = {loss}') - if last_loss is None: - last_loss = loss - elif loss < last_loss: - last_loss = loss - logging.info(f'saving snapshot') - torch.save(model.state_dict(), os.path.join(snapshots_path, f'state_dict_{i}.pth')) diff --git a/mac/slowllama/slowllama/finetune_dolly.py b/mac/slowllama/slowllama/finetune_dolly.py deleted file mode 100644 index 47c858d..0000000 --- a/mac/slowllama/slowllama/finetune_dolly.py +++ /dev/null @@ -1,93 +0,0 @@ -import os -import sys -import torch -import logging - -from llama2_loader import load_frozen -from plot_lora import log_lora -from datasets import load_dataset -from utils import Tokenizer, greedy_gen - -# training settings -seed = 54321 -iters = 1000 -device = 'mps' # mps for macbooks -seq_len = 1024 -batch_size = 4 -lr = 1e-4 - -# type used for computation. Might be different from storage type (which is bfloat16) -compute_dtype = torch.float32 # float32 for macbooks -#compute_dtype = torch.bfloat16 # bfloat16 for CUDA - -eval_before_training = False -eval_period = 20 -gen_tokens = 32 - -log_lora_grad = False -log_lora_weight = True - -model_path = '../llama7b' -snapshots_path = 'out' -finetune_dataset = 'databricks/databricks-dolly-15k' -prompt = 'slowllama is a ' - -if not os.path.exists(snapshots_path): - os.makedirs(snapshots_path) - -tokenizer_path = os.path.join(model_path, 'tokenizer.model') -tokenizer = Tokenizer(tokenizer_path) - -def format_sample(sample): - instruction = f"### Instruction\n{sample['instruction']}\n\n" - context = f"### Context\n{sample['context']}\n\n" if len(sample["context"]) > 0 else "" - response = f"### Answer\n{sample['response']}" - return instruction + context + response - -def prepare_data(): - train_data = load_dataset(finetune_dataset, split="train") - formatted = [format_sample(s) for s in train_data] - return '\n\n'.join(formatted[:100]) - -if __name__ == '__main__': - text = prepare_data() - logging.basicConfig(format='%(asctime)s %(message)s', level=logging.INFO, filename='logs/finetune.log') - torch.random.manual_seed(seed) - - tokens = tokenizer.encode(text, True, True) - - logging.info(f'loaded dataset: {len(tokens)} tokens') - - model = load_frozen(model_path, compute_dtype=compute_dtype).to(device).to(compute_dtype) - - def get_batch(batch_size): - index = torch.randint(len(tokens) - seq_len, (batch_size,)) - x = torch.stack([torch.tensor(tokens[i:i + seq_len]).to(torch.int64) for i in index]) - y = torch.stack([torch.tensor(tokens[i + 1:i + seq_len + 1]).to(torch.int64) for i in index]) - return x.to(device), y.to(device) - - opt = torch.optim.AdamW(model.parameters(), lr=lr) - - last_loss = None - for i in range(iters): - if i % eval_period == 0 and (i > 0 or eval_before_training): - greedy_gen(model, tokenizer, device, prompt, gen_tokens) - logging.info(f'starting iteration {i}') - X, y = get_batch(batch_size) - opt.zero_grad() - # both forward and backward passes are here. - # returned loss is a scalar, not variable - logits, loss = model.manual_loop(X, y) - opt.step() - - # optional logging of lora weights/gradients - if log_lora_grad or log_lora_weight: - log_lora(model.lora_layers, log_weights=log_lora_weight, log_grad=log_lora_grad) - - logging.info(f'backprop done, loss after forward pass = {loss}') - if last_loss is None: - last_loss = loss - elif loss < last_loss: - last_loss = loss - logging.info(f'saving snapshot') - torch.save(model.state_dict(), os.path.join(snapshots_path, f'state_dict_{i}.pth')) diff --git a/mac/slowllama/slowllama/llama2.py b/mac/slowllama/slowllama/llama2.py deleted file mode 100644 index 3d13f00..0000000 --- a/mac/slowllama/slowllama/llama2.py +++ /dev/null @@ -1,380 +0,0 @@ -# based on model.py from https://github.com/karpathy/llama2.c by Andrej Karpathy, MIT licenced - -# modifications by okuvshynov include: -# - no weight tying -# - using blackbox offloadable modules -# - simplify init/generation as we only use it for fine-tuning experiments -# - manual backprop -# - support for ffn_dim_multiplier which llama2-70b uses -# - LoRA - -import logging -import math - -from typing import Optional, Tuple - -import torch -import torch.nn.functional as F -from torch import nn - -from blackbox import BlackboxDisk -from utils import save_rng_state, restore_rng_state, device_map, cleanup_cache -from model_config import ModelArgs - -import logging - - -class RMSNorm(torch.nn.Module): - def __init__(self, dim: int, eps: float): - super().__init__() - self.eps = eps - self.weight = nn.Parameter(torch.ones(dim)) - - def _norm(self, x): - return x * torch.rsqrt(x.pow(2).mean(-1, keepdim=True) + self.eps) - - def forward(self, x): - output = self._norm(x.float()).type_as(x) - return output * self.weight - - -def precompute_freqs_cis(dim: int, end: int, theta: float = 10000.0): - freqs = 1.0 / (theta ** (torch.arange(0, dim, 2)[: (dim // 2)].float() / dim)) - t = torch.arange(end, device=freqs.device) # type: ignore - freqs = torch.outer(t, freqs).float() # type: ignore - freqs_cos = torch.cos(freqs) # real part - freqs_sin = torch.sin(freqs) # imaginary part - return freqs_cos, freqs_sin - -def reshape_for_broadcast(freqs_cis: torch.Tensor, x: torch.Tensor): - ndim = x.ndim - assert 0 <= 1 < ndim - assert freqs_cis.shape == (x.shape[1], x.shape[-1]) - shape = [d if i == 1 or i == ndim - 1 else 1 for i, d in enumerate(x.shape)] - return freqs_cis.view(shape) - -def apply_rotary_emb( - xq: torch.Tensor, - xk: torch.Tensor, - freqs_cos: torch.Tensor, - freqs_sin: torch.Tensor -) -> Tuple[torch.Tensor, torch.Tensor]: - - # reshape xq and xk to match the complex representation - xq_r, xq_i = xq.float().reshape(xq.shape[:-1] + (-1, 2)).unbind(-1) - xk_r, xk_i = xk.float().reshape(xk.shape[:-1] + (-1, 2)).unbind(-1) - - # reshape freqs_cos and freqs_sin for broadcasting - freqs_cos = reshape_for_broadcast(freqs_cos, xq_r) - freqs_sin = reshape_for_broadcast(freqs_sin, xq_r) - - # apply rotation using real numbers - xq_out_r = xq_r * freqs_cos - xq_i * freqs_sin - xq_out_i = xq_r * freqs_sin + xq_i * freqs_cos - xk_out_r = xk_r * freqs_cos - xk_i * freqs_sin - xk_out_i = xk_r * freqs_sin + xk_i * freqs_cos - - # flatten last two dimensions - xq_out = torch.stack([xq_out_r, xq_out_i], dim=-1).flatten(3) - xk_out = torch.stack([xk_out_r, xk_out_i], dim=-1).flatten(3) - - return xq_out.type_as(xq), xk_out.type_as(xk) - -def repeat_kv(x: torch.Tensor, n_rep: int) -> torch.Tensor: - """torch.repeat_interleave(x, dim=2, repeats=n_rep)""" - bs, slen, n_kv_heads, head_dim = x.shape - if n_rep == 1: - return x - return ( - x[:, :, :, None, :] - .expand(bs, slen, n_kv_heads, n_rep, head_dim) - .reshape(bs, slen, n_kv_heads * n_rep, head_dim) - ) - -class Attention(nn.Module): - def __init__(self, args: ModelArgs): - super().__init__() - self.n_kv_heads = args.n_heads if args.n_kv_heads is None else args.n_kv_heads - self.n_heads = args.n_heads - self.n_rep = self.n_heads // self.n_kv_heads - self.head_dim = args.dim // args.n_heads - - # here's where we inject LoRA - self.wq = nn.Linear(args.dim, args.n_heads * self.head_dim, bias=False) - self.wk = nn.Linear(args.dim, self.n_kv_heads * self.head_dim, bias=False) - - # here's where we inject LoRA - self.wv = nn.Linear(args.dim, self.n_kv_heads * self.head_dim, bias=False) - - self.wo = nn.Linear(args.n_heads * self.head_dim, args.dim, bias=False) - - # TODO: probably don't need dropout here as we don't plan to do full finetune - # or maybe we do. - self.attn_dropout = nn.Dropout(args.dropout) - self.resid_dropout = nn.Dropout(args.dropout) - self.dropout = args.dropout - - # use flash attention or a manual implementation? - self.flash = hasattr(torch.nn.functional, 'scaled_dot_product_attention') - if not self.flash: - logging.warn("using slow attention. Flash Attention requires PyTorch >= 2.0") - mask = torch.full((1, 1, args.max_seq_len, args.max_seq_len), float("-inf")) - mask = torch.triu(mask, diagonal=1) - self.register_buffer("mask", mask) - - self.attention_norm = RMSNorm(args.dim, eps=args.norm_eps) - - def forward( - self, - x: torch.Tensor, - freqs_cos: torch.Tensor, - freqs_sin: torch.Tensor, - q_lora: nn.Module, - v_lora: nn.Module - ): - bsz, seqlen, _ = x.shape - - x_base = x - x = self.attention_norm(x) - - # QKV - xq, xk, xv = self.wq(x) + q_lora(x), self.wk(x), self.wv(x) + v_lora(x) - xq = xq.view(bsz, seqlen, self.n_heads, self.head_dim) - xk = xk.view(bsz, seqlen, self.n_kv_heads, self.head_dim) - xv = xv.view(bsz, seqlen, self.n_kv_heads, self.head_dim) - - # RoPE relative positional embeddings - xq, xk = apply_rotary_emb(xq, xk, freqs_cos, freqs_sin) - - # grouped multiquery attention: expand out keys and values - xk = repeat_kv(xk, self.n_rep) # (bs, seqlen, n_heads, head_dim) - xv = repeat_kv(xv, self.n_rep) # (bs, seqlen, n_heads, head_dim) - - # make heads into a batch dimension - xq = xq.transpose(1, 2) # (bs, n_heads, seqlen, head_dim) - xk = xk.transpose(1, 2) - xv = xv.transpose(1, 2) - - # flash implementation - if self.flash: - output = torch.nn.functional.scaled_dot_product_attention(xq, xk, xv, attn_mask=None, dropout_p=self.dropout if self.training else 0.0, is_causal=True) - else: - # manual implementation - scores = torch.matmul(xq, xk.transpose(2, 3)) / math.sqrt(self.head_dim) - assert hasattr(self, 'mask') - scores = scores + self.mask[:, :, :seqlen, :seqlen] # (bs, n_heads, seqlen, cache_len + seqlen) - scores = F.softmax(scores.float(), dim=-1).type_as(xq) - scores = self.attn_dropout(scores) - output = torch.matmul(scores, xv) # (bs, n_heads, seqlen, head_dim) - - # restore time as batch dimension and concat heads - output = output.transpose(1, 2).contiguous().view(bsz, seqlen, -1) - - # final projection into the residual stream - output = self.wo(output) - output = self.resid_dropout(output) - return x_base + output - - -class FeedForward(nn.Module): - def __init__(self, dim: int, hidden_dim: int, multiple_of: int, dropout: float, ffn_dim_multiplier: Optional[float], args: ModelArgs): - super().__init__() - hidden_dim = int(2 * hidden_dim / 3) - if ffn_dim_multiplier is not None: - hidden_dim = int(ffn_dim_multiplier * hidden_dim) - hidden_dim = multiple_of * ((hidden_dim + multiple_of - 1) // multiple_of) - self.w1 = nn.Linear(dim, hidden_dim, bias=False) - self.w2 = nn.Linear(hidden_dim, dim, bias=False) - self.w3 = nn.Linear(dim, hidden_dim, bias=False) - self.dropout = nn.Dropout(dropout) - self.ffn_norm = RMSNorm(args.dim, eps=args.norm_eps) - - def forward(self, x): - x_base = x - x = self.ffn_norm(x) - return x_base + self.dropout(self.w2(F.silu(self.w1(x)) * self.w3(x))) - -class TransformerBlock(nn.Module): - def __init__(self, layer_id: int, args: ModelArgs): - super().__init__() - self.n_heads = args.n_heads - self.dim = args.dim - self.head_dim = args.dim // args.n_heads - - self.attention = BlackboxDisk(Attention(args), args) - self.feed_forward = BlackboxDisk(FeedForward( - dim=args.dim, - hidden_dim=4 * args.dim, - multiple_of=args.multiple_of, - dropout=args.dropout, - ffn_dim_multiplier=args.ffn_dim_multiplier, - args=args - ), args) - self.layer_id = layer_id - - - def forward(self, x, freqs_cos, freqs_sin, lora_q, lora_v): - h = self.attention(x, freqs_cos, freqs_sin, lora_q, lora_v) - out = self.feed_forward(h) - return out - -class LoRA(nn.Module): - def __init__(self, original_layer, rank, alpha, dropout): - super().__init__() - n, m = original_layer.weight.shape - self.A = nn.Linear(m, rank, bias=False) - self.B = nn.Linear(rank, n, bias=False) - nn.init.zeros_(self.B.weight) - self.dropout = nn.Dropout(dropout) - self.scale = alpha / rank - - # return matrix to add to original weight - def expanded(self): - res = self.B.weight.mm(self.A.weight) * self.scale - return res - - def forward(self, x): - return self.dropout(self.B(self.A(x))) * self.scale - -class Transformer(nn.Module): - def __init__(self, params: ModelArgs): - super().__init__() - self.params = params - self.vocab_size = params.vocab_size - self.n_layers = params.n_layers - - self.tok_embeddings = BlackboxDisk(nn.Embedding(params.vocab_size, params.dim), params) - self.dropout = nn.Dropout(params.dropout) - self.layers = torch.nn.ModuleList() - - # we create LoRA adapters separately. As we don't want to load/save them continously - self.lora_layers = [] - for layer_id in range(params.n_layers): - block = TransformerBlock(layer_id, params) - - # TODO: remove this one - attn = block.attention.loaded_inner() - q_lora = LoRA(attn.wq, rank=params.lora_rank, alpha=params.lora_alpha, dropout=params.lora_dropout).to(params.compute_dtype) - v_lora = LoRA(attn.wv, rank=params.lora_rank, alpha=params.lora_alpha, dropout=params.lora_dropout).to(params.compute_dtype) - self.lora_layers.append({ 'q_lora': q_lora, 'v_lora': v_lora}) - self.add_module(f'q_lora_{layer_id}', q_lora) - self.add_module(f'v_lora_{layer_id}', v_lora) - self.layers.append(block) - logging.debug(f'created transformer block {layer_id}') - - self.norm = RMSNorm(params.dim, eps=params.norm_eps) - self.norm.requires_grad = False - self.output = BlackboxDisk(nn.Linear(params.dim, params.vocab_size, bias=False), params) - - # some useful precompute for the RoPE relative positional embeddings - freqs_cos, freqs_sin = precompute_freqs_cis(self.params.dim // self.params.n_heads, self.params.max_seq_len, theta=params.rope_theta) - self.register_buffer("freqs_cos", freqs_cos, persistent=False) - self.register_buffer("freqs_sin", freqs_sin, persistent=False) - - def forward(self, tokens: torch.Tensor) -> torch.Tensor: - _bsz, seqlen = tokens.shape - - # dummy input to force gradient propagation to blackbox modules - h = self.tok_embeddings(tokens) - h = self.dropout(h) - freqs_cos = self.freqs_cos[:seqlen] - freqs_sin = self.freqs_sin[:seqlen] - - for layer, lora in zip(self.layers, self.lora_layers): - h = layer(h, freqs_cos, freqs_sin, lora['q_lora'], lora['v_lora']) - h = self.norm(h) - - return self.output(h[:, [-1], :]) - - def backprop_w_lora(self, blackbox_module, output_grad, *args): - device = output_grad.device - module = blackbox_module.load(device) - - # we use LoRA and only updated attached low-rank modules - # no part of original model is getting any updates, so no need for gradient - for param in module.parameters(): - param.requires_grad = False - - input = blackbox_module.load_input(device) - input.requires_grad = True - - output = module(input, *args) - output.backward(output_grad) - - return input.grad if input.requires_grad else None - - # this is a manual implementation on forward/backward passes - def manual_loop(self, tokens, targets): - logging.log(level=logging.DEBUG, msg=f'starting manual loop') - device = device_map(tokens.device) - - embd_out = self.tok_embeddings(tokens) - embd_out = embd_out.detach() - embd_out.requires_grad = True - logging.log(level=logging.DEBUG, msg=f'done embedding') - - _, seqlen = tokens.shape - - freqs_cos = self.freqs_cos[:seqlen] - freqs_sin = self.freqs_sin[:seqlen] - - current = self.dropout(embd_out) - del embd_out - - rng_before = [] - - for i, (layer, lora) in enumerate(zip(self.layers, self.lora_layers)): - rng_before.append(save_rng_state(device)) - current = layer(current, freqs_cos, freqs_sin, lora['q_lora'], lora['v_lora']) - logging.log(level=logging.DEBUG, msg=f'forward: transformer block {i} done') - - current = current.detach() - current.requires_grad = True - - norm_out = self.norm(current) - norm_out = norm_out.detach() - norm_out.requires_grad = True - - # TODO: micro-optimization: as output is last layer, we can skip loading and running it second time - logging.log(level=logging.DEBUG, msg=f'output layer') - logits = self.output(norm_out) - del norm_out - - logging.log(level=logging.DEBUG, msg=f'output layer done') - - if (self.params.compute_dtype != torch.float32): - logits = logits.to(torch.float32) - - logits = logits.detach() - logits.requires_grad = True - - loss = F.cross_entropy(logits.view(-1, logits.size(-1)), targets.view(-1), ignore_index=-1) - logging.log(level=logging.DEBUG, msg=f'forward: computed loss') - - loss.backward() - - norm_out_grad = self.backprop_w_lora(self.output, logits.grad.to(self.params.compute_dtype)) - del logits - logging.log(level=logging.DEBUG, msg=f'combined: output layer done') - - norm_out2 = self.norm(current) - norm_out2.backward(norm_out_grad) - del norm_out_grad - del norm_out2 - - last_grad = current.grad - del current - - for i, (layer, rng_state, lora) in enumerate(zip(reversed(self.layers), reversed(rng_before), reversed(self.lora_layers))): - cleanup_cache(device) - restore_rng_state(rng_state, device=device) - # first, do feed_forward - last_grad = self.backprop_w_lora(layer.feed_forward, last_grad) - - # now, do attention - cleanup_cache(device) - last_grad = self.backprop_w_lora(layer.attention, last_grad, freqs_cos, freqs_sin, lora['q_lora'], lora['v_lora']) - logging.log(level=logging.DEBUG, msg=f'combined: transformer block {i} done') - - # no need to backpropagate through embeddings no LoRA layers there. - return loss.item() diff --git a/mac/slowllama/slowllama/llama2_loader.py b/mac/slowllama/slowllama/llama2_loader.py deleted file mode 100644 index cea452b..0000000 --- a/mac/slowllama/slowllama/llama2_loader.py +++ /dev/null @@ -1,202 +0,0 @@ -import torch -import os -import json -import gc -import glob -import logging -import shutil - -from model_config import ModelArgs -from llama2 import Transformer -from utils import device_supports_dtype - -# how are weights sharded in llama2 - by rows or columns -join_dim = { - 'wq': 0, - 'wk': 0, - 'wv': 0, - 'wo': 1, - 'w1': 0, - 'w2': 1, - 'w3': 0, - 'output': 0, - 'tok_embeddings': 1, -} - -def get_subset(title, weight_subset, index): - if title in join_dim.keys(): - jdim = join_dim[title] - step = weight_subset.shape[jdim] - subset = (slice(step * index, step * (index + 1)), slice(None)) - if jdim == 1: - subset = (subset[1], subset[0]) - return subset - else: - return tuple(slice(None) for _ in range(len(weight_subset.shape))) - -def get_w_subset(title, weight, shards, shard): - if title in join_dim.keys(): - jdim = join_dim[title] - step = weight.shape[jdim] // shards - subset = (slice(step * shard, step * (shard + 1)), slice(None)) - if jdim == 1: - subset = (subset[1], subset[0]) - return subset - else: - return tuple(slice(None) for _ in range(len(weight.shape))) - -def apply_subset(module, weight_subset, checkpoint_index, title): - with torch.no_grad(): - idx_subset = get_subset(title, weight_subset, checkpoint_index) - module.weight[idx_subset] = weight_subset - -def prepare_model(llama2_path, frozen_path, **kwargs): - params_path = os.path.join(llama2_path, 'params.json') - with open(params_path, 'r') as conf_file: - config = json.loads(conf_file.read()) - - for k, v in kwargs.items(): - config[k] = v - - args = ModelArgs(**config) - args.vocab_size = args.vocab_size_override - args.served_model_path = frozen_path - - logging.info('creating model instance') - model = Transformer(args) - paths = sorted(glob.glob(f'{llama2_path}/consolidated.*.pth')) - - shards = len(paths) - - for ci, checkpoint_path in enumerate(paths): - logging.info(f'prepare_model: processing checkpoint {ci} out of {shards}') - - checkpoint = torch.load(checkpoint_path, map_location='cpu') - - for i, layer in enumerate(model.layers): - prefix = f'layers.{i}.' - #block = layer.loaded_inner() - for title, submodule in layer.named_modules(): - if hasattr(submodule, 'weight'): - full_path = f'{prefix}{title}.weight' - weight_subset = checkpoint[full_path] - apply_subset(submodule, weight_subset, ci, title) - del checkpoint[full_path] - gc.collect() - - prefix = f'layers.{i}.attention.' - attention = layer.attention.loaded_inner() - for title, submodule in attention.named_modules(): - if hasattr(submodule, 'weight'): - if 'attention_norm' in title: - full_path = f'layers.{i}.attention_norm.weight' - else: - full_path = f'{prefix}{title}.weight' - weight_subset = checkpoint[full_path] - apply_subset(submodule, weight_subset, ci, title) - del checkpoint[full_path] - gc.collect() - layer.attention.save(attention) - - prefix = f'layers.{i}.feed_forward.' - feed_forward = layer.feed_forward.loaded_inner() - for title, submodule in feed_forward.named_modules(): - if hasattr(submodule, 'weight'): - if 'ffn_norm' in title: - full_path = f'layers.{i}.ffn_norm.weight' - else: - full_path = f'{prefix}{title}.weight' - weight_subset = checkpoint[full_path] - apply_subset(submodule, weight_subset, ci, title) - del checkpoint[full_path] - gc.collect() - layer.feed_forward.save(feed_forward) - logging.info(f'prepare_model: updating layer {i} out of {len(model.layers)}') - #layer.save(block) - - # now repeat for other submodules: output, embeddings and norm - title = 'output' - block = model.output.loaded_inner() - apply_subset(block, checkpoint[f'{title}.weight'], ci, title) - logging.info(f'prepare_model: updating output layer') - model.output.save(block) - - title = 'tok_embeddings' - block = model.tok_embeddings.loaded_inner() - apply_subset(block, checkpoint[f'{title}.weight'], ci, title) - logging.info(f'prepare_model: updating token embeddings') - model.tok_embeddings.save(block) - - # norm left - apply_subset(model.norm, checkpoint['norm.weight'], ci, None) - - # we also need to copy: - # - params.json - # - model dict itself (norm + Lora) - # - tokenizer?' - shutil.copy(params_path, os.path.join(frozen_path, 'params.json')) - shutil.copy(os.path.join(llama2_path, 'tokenizer.model'), os.path.join(frozen_path, 'tokenizer.model')) - torch.save(model.to(args.frozen_dtype).state_dict(), os.path.join(frozen_path, 'model.pth')) - - return model - -def load_frozen(path, **kwargs): - logging.info(f'loading sequential model from {path}') - params_path = os.path.join(path, 'params.json') - with open(params_path, 'r') as conf_file: - config = json.loads(conf_file.read()) - - for k, v in kwargs.items(): - config[k] = v - - args = ModelArgs(**config) - args.vocab_size = args.vocab_size_override - args.init_frozen = False - args.served_model_path = path - logging.info(f'creating model instance') - model = Transformer(args).to(args.compute_dtype) - logging.info(f'loading model dict') - model.load_state_dict(torch.load(os.path.join(path, 'model.pth')), strict=False) - return model - -# this is merging LoRA back to original weights in llama2 format -def add_lora(model_path, lora_path): - lora_weights = torch.load(lora_path, map_location='cpu') - paths = sorted(glob.glob(f'{model_path}/consolidated.*.pth')) - params_path = os.path.join(model_path, 'params.json') - with open(params_path, 'r') as conf_file: - config = json.loads(conf_file.read()) - - shards = len(paths) - - config = ModelArgs(**config) - - n_layers = int(config.n_layers) - - lora_scale = config.lora_alpha / config.lora_rank - - for ci, checkpoint_path in enumerate(paths): - logging.info(f'add_lora: processing checkpoint {ci} out of {shards}') - checkpoint = torch.load(checkpoint_path, map_location='cpu') - - for layer in range(n_layers): - logging.info(f'add_lora: processing checkpoint {ci} layer {layer} out of {n_layers}') - for attn_key in ['v', 'q']: - local_path = f'w{attn_key}' - checkpoint_key = f'layers.{layer}.attention.{local_path}.weight' - a_key = f'{attn_key}_lora_{layer}.A.weight' - b_key = f'{attn_key}_lora_{layer}.B.weight' - - original_type = lora_weights[b_key].dtype - - if device_supports_dtype('cpu', original_type): - lora = lora_weights[b_key].mm(lora_weights[a_key]) * lora_scale - else: - lora = lora_weights[b_key].to(torch.float32).mm(lora_weights[a_key].to(torch.float32)) * lora_scale - lora = lora.to(original_type) - - subset = get_w_subset(local_path, lora, shards, ci) - checkpoint[checkpoint_key] = checkpoint[checkpoint_key] + lora[subset].to(torch.bfloat16) - torch.save(checkpoint, checkpoint_path) - del checkpoint - gc.collect() diff --git a/mac/slowllama/slowllama/logs/.gitignore b/mac/slowllama/slowllama/logs/.gitignore deleted file mode 100644 index d6b7ef3..0000000 --- a/mac/slowllama/slowllama/logs/.gitignore +++ /dev/null @@ -1,2 +0,0 @@ -* -!.gitignore diff --git a/mac/slowllama/slowllama/merge_lora.py b/mac/slowllama/slowllama/merge_lora.py deleted file mode 100644 index b534014..0000000 --- a/mac/slowllama/slowllama/merge_lora.py +++ /dev/null @@ -1,17 +0,0 @@ -import logging -import os -import sys -import shutil - -from llama2_loader import add_lora - -logging.basicConfig(format='%(asctime)s %(message)s', level=logging.INFO, filename='logs/merge_lora.log') - -model_path = sys.argv[1] -lora_path = sys.argv[2] -out_model_path = sys.argv[3] - -if os.path.exists(out_model_path): - shutil.rmtree(out_model_path) -shutil.copytree(model_path, out_model_path) -add_lora(out_model_path, lora_path) diff --git a/mac/slowllama/slowllama/model_config.py b/mac/slowllama/slowllama/model_config.py deleted file mode 100644 index c98dad4..0000000 --- a/mac/slowllama/slowllama/model_config.py +++ /dev/null @@ -1,27 +0,0 @@ -import torch - -from dataclasses import dataclass -from typing import Optional - -@dataclass -class ModelArgs: - dim: int = 4096 - n_layers: int = 32 - n_heads: int = 32 - n_kv_heads: Optional[int] = None - multiple_of: int = 256 # make SwiGLU hidden layer size multiple of large power of 2 - norm_eps: float = 1e-5 - max_seq_len: int = 2048 - dropout: float = 0.0 # unless we bring back - ffn_dim_multiplier: Optional[float] = None - compute_dtype: torch.dtype = torch.float32 - rope_theta: float = 10000.0 - lora_rank: int = 8 - lora_alpha: int = 64 - lora_dropout: float = 0.05 - served_model_path: str = '' # relative path by default - cached_data_path: str = '' # relative path by default - init_frozen: bool = True - frozen_dtype: torch.dtype = torch.bfloat16 - vocab_size: int = 32000 - vocab_size_override: int = 32000 \ No newline at end of file diff --git a/mac/slowllama/slowllama/plot_lora.py b/mac/slowllama/slowllama/plot_lora.py deleted file mode 100644 index 3a107ba..0000000 --- a/mac/slowllama/slowllama/plot_lora.py +++ /dev/null @@ -1,48 +0,0 @@ -import logging -import torch - -def log_lora(lora_layers, log_weights=True, log_grad=True, log_level=logging.INFO): - if not log_weights and not log_grad: - return - try: - from fewlines import bar - except ImportError: - logging.error('Unable to import fewlines. "pip install fewlines" to use distribution logging') - return - - gradients_a = {} - gradients_b = {} - weights_a = {} - weights_b = {} - - for i, lora in enumerate(lora_layers): - q = lora['q_lora'] - v = lora['v_lora'] - if log_grad: - gradients_a[f'Q{i}.A'] = q.A.weight.grad.view(-1).to(torch.float32).tolist() - gradients_b[f'Q{i}.B'] = q.B.weight.grad.view(-1).to(torch.float32).tolist() - gradients_a[f'V{i}.A'] = v.A.weight.grad.view(-1).to(torch.float32).tolist() - gradients_b[f'V{i}.B'] = v.B.weight.grad.view(-1).to(torch.float32).tolist() - if log_weights: - weights_a[f'Q{i}.A'] = q.A.weight.view(-1).to(torch.float32).tolist() - weights_b[f'Q{i}.B'] = q.B.weight.view(-1).to(torch.float32).tolist() - weights_a[f'V{i}.A'] = v.A.weight.view(-1).to(torch.float32).tolist() - weights_b[f'V{i}.B'] = v.B.weight.view(-1).to(torch.float32).tolist() - - if log_grad: - logging.log(log_level, f'\n=== GRADIENTS A ===') - for l in bar.bar_histograms(gradients_a): - logging.log(log_level, l) - - logging.log(log_level, f'\n=== GRADIENTS B ===') - for l in bar.bar_histograms(gradients_b): - logging.log(log_level, l) - - if log_weights: - logging.log(log_level, f'\n=== WEIGHTS A ===') - for l in bar.bar_histograms(weights_a): - logging.log(log_level, l) - - logging.log(log_level, f'\n=== WEIGHTS B ===') - for l in bar.bar_histograms(weights_b): - logging.log(log_level, l) \ No newline at end of file diff --git a/mac/slowllama/slowllama/prepare_model.py b/mac/slowllama/slowllama/prepare_model.py deleted file mode 100644 index 38979a6..0000000 --- a/mac/slowllama/slowllama/prepare_model.py +++ /dev/null @@ -1,14 +0,0 @@ -# loads model in original llama2 format and saves to another folder in sequential format - -import torch -import logging - -from llama2_loader import prepare_model -from conf_fp16 import * - -logging.basicConfig(format='%(asctime)s %(message)s', - level=logging.DEBUG, filename='logs/prepare_model.log') -torch.random.manual_seed(seed) - 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zy!V4GqQ5Wng-UF0&3m6iV>E-x)cZvHl;?(Wew-w+&lFd_QPG0@qe1P?Db9~|;wYgh zq0<^ST$+mAAA5j_(sWw=SF=9kmHFs~?>EAZUK(cH2=zsLHR02#+rQbCrnGv)`5!)h z@)Vym&fW;&S4@_7Xz~l-F8HgyfVP$D diff --git a/mac/slowllama/slowllama/test_data/cubestat.txt b/mac/slowllama/slowllama/test_data/cubestat.txt deleted file mode 100644 index 1dba614..0000000 --- a/mac/slowllama/slowllama/test_data/cubestat.txt +++ /dev/null @@ -1,9 +0,0 @@ -Cubestat is a command-line utility to monitor system metrics in horizon chart format. It was originally created for Apple M1/M2 devices, but now works on Linux with nVidia GPU as well, including Google Colab environment. - -Currently cubestat reports: - -CPU utilization - configurable per core ('expanded'), cluster of cores: Efficiency/Performance ('cluster') or both. Is shown as percentage. -GPU utilization per card/chip. Is shown in percentage. Works for Apple's M1/M2 SoC and nVidia GPUs. For nVidia GPU shows memory usage as well. -ANE (Apple's Neural Engine) power consumption. According to man powermetrics it is an estimate, but seems working good enough as a proxy to ANE utilization. Is shown as percentage. -Disk and network IO; Is shown in Kb/s. -Memory usage in % diff --git a/mac/slowllama/slowllama/test_gen.py b/mac/slowllama/slowllama/test_gen.py deleted file mode 100644 index abab324..0000000 --- a/mac/slowllama/slowllama/test_gen.py +++ /dev/null @@ -1,25 +0,0 @@ -import logging -import torch -import sys -import os - -from llama2_loader import load_frozen -from utils import Tokenizer, greedy_gen -from conf_fp16 import * - -logging.basicConfig(format='%(asctime)s %(message)s', level=logging.DEBUG) - -lora_weights = sys.argv[1] if len(sys.argv) > 1 else None - -tokenizer_path = os.path.join(frozen_model_path, 'tokenizer.model') -tokenizer = Tokenizer(tokenizer_path) - -model = load_frozen(frozen_model_path, dropout=0.0, lora_rank=lora_rank, frozen_dtype=frozen_dtype, compute_dtype=compute_dtype).to(device) -if lora_weights is not None: - logging.debug(model.load_state_dict(torch.load(lora_weights), strict=False)) - -logging.info('Model loaded.') - -prompt = 'Cubestat reports the following metrics: ' - -greedy_gen(model, tokenizer, device, prompt, max_new_tokens=100) diff --git a/mac/slowllama/slowllama/utils.py b/mac/slowllama/slowllama/utils.py deleted file mode 100644 index fa56f85..0000000 --- a/mac/slowllama/slowllama/utils.py +++ /dev/null @@ -1,94 +0,0 @@ -import torch -import sentencepiece -import logging - -def device_map(device): - if str(device).startswith('mps'): - return 'mps' - return str(device) - -def device_supports_dtype(device, dtype): - try: - a = torch.rand(2, 2).to(device).to(dtype) - b = torch.rand(2, 2).to(device).to(dtype) - c = a.mm(b) - logging.debug(f'success, {device} supports {dtype}') - return True - except TypeError as e: - return False - -global_id_auto = 0 - -def next_id(): - global global_id_auto - new_id = global_id_auto - global_id_auto += 1 - return new_id - -def save_rng_state(device='cpu'): - if device == 'cpu': - import torch - return torch.random.get_rng_state() - elif device.startswith('cuda'): - import torch.cuda - return torch.cuda.get_rng_state(device=int(device.split(':')[1])) - elif device.startswith('mps'): - import torch.mps - return torch.mps.get_rng_state() - else: - raise ValueError(f"Unsupported device: {device}") - -def restore_rng_state(rng_state, device='cpu'): - if device == 'cpu': - import torch - torch.random.set_rng_state(rng_state) - elif device.startswith('cuda'): - import torch.cuda - torch.cuda.set_rng_state(rng_state, device=int(device.split(':')[1])) - elif device.startswith('mps'): - import torch.mps - torch.mps.set_rng_state(rng_state) - else: - raise ValueError(f"Unsupported device: {device}") - -def greedy_gen(model, tokenizer, device, prompt, max_new_tokens=50): - tokens = torch.tensor(tokenizer.encode(prompt, True, False)).view(1, -1).to(device) - model.eval() - for _ in range(max_new_tokens): - logits = model(tokens) - logits = logits[:, -1, :] - _, next_token = torch.topk(logits, k=1, dim=-1) - logging.info(f'next token: {next_token} {tokenizer.decode(next_token.tolist())}') - tokens = torch.cat((tokens, next_token), dim=1) - - for i, output in enumerate(tokens): - logging.info(f'{i} - {tokenizer.decode(output.tolist())}') - -def greedy_gen2(model, tokenizer, device, prompt, max_new_tokens=50): - tokens = torch.tensor(tokenizer.encode(prompt, True, False)).view(1, -1).to(device) - model.eval() - for _ in range(max_new_tokens): - logits = model(tokens) - logits = logits[:, -1, :] - _, next_token = torch.topk(logits, k=1, dim=-1) - logging.info(f'next token: {next_token} {tokenizer.decode(next_token.tolist())}') - yield tokenizer.decode(next_token.tolist())[0] - tokens = torch.cat((tokens, next_token), dim=1) - -def cleanup_cache(device='cpu'): - if device.startswith('mps'): - import torch.mps - torch.mps.empty_cache() - - -class Tokenizer: - def __init__(self, path): - self.model = sentencepiece.SentencePieceProcessor(path) - - def encode(self, text, bos=False, eos=False): - b = [self.model.bos_id()] if bos else [] - e = [self.model.eos_id()] if eos else [] - return b + self.model.encode(text) + e - - def decode(self, tokens): - return self.model.decode(tokens) From 62e6301a8abbd84b5cac116dd92e3b846ea45a99 Mon Sep 17 00:00:00 2001 From: jazelly Date: Sun, 5 May 2024 20:00:11 +0930 Subject: [PATCH 13/96] fix: submodule --- .gitmodules | 3 +++ mac/slowllama/slowllama | 1 + 2 files changed, 4 insertions(+) create mode 160000 mac/slowllama/slowllama diff --git a/.gitmodules b/.gitmodules index 50d5412..12c1994 100644 --- a/.gitmodules +++ b/.gitmodules @@ -1,3 +1,6 @@ [submodule "llama-gguf/llama.cpp"] path = llama-gguf/llama.cpp url = git@github.com:ggerganov/llama.cpp.git +[submodule "mac/slowllama/slowllama"] + path = mac/slowllama/slowllama + url = git@github.com:jazelly/slowllama.git diff --git a/mac/slowllama/slowllama b/mac/slowllama/slowllama new file mode 160000 index 0000000..0d8a4cf --- /dev/null +++ b/mac/slowllama/slowllama @@ -0,0 +1 @@ +Subproject commit 0d8a4cf5dc8767db81d019812f054a77ce68b31e From 16e8a9ee2a0d05f2b9faa0a2a8b6eac23ac507b1 Mon Sep 17 00:00:00 2001 From: jazelly Date: Sun, 5 May 2024 21:49:56 +0930 Subject: [PATCH 14/96] chore: setup slowllama --- .gitmodules | 2 +- mac/README.md | 6 ++---- mac/slowllama/llama2/README.md | 14 ++++++++++++-- mac/slowllama/llama2/slowllama.py | 19 ++++++++++--------- 4 files changed, 25 insertions(+), 16 deletions(-) diff --git a/.gitmodules b/.gitmodules index 12c1994..5b0f002 100644 --- a/.gitmodules +++ b/.gitmodules @@ -3,4 +3,4 @@ url = git@github.com:ggerganov/llama.cpp.git [submodule "mac/slowllama/slowllama"] path = mac/slowllama/slowllama - url = git@github.com:jazelly/slowllama.git + url = git@github.com:jazelly/slowllama.git \ No newline at end of file diff --git a/mac/README.md b/mac/README.md index 068334e..8f3ac0d 100644 --- a/mac/README.md +++ b/mac/README.md @@ -2,13 +2,11 @@ Currently there are 2 ways supported. -1. in slowllama - under this dir +1. in slowllama - under this dir, for LLAMA-2 only 2. in llama.cpp - refer to [llama-gguf/README.md](../llama-gguf/README.md) -Both only support LLAMA based models. - ## Slowllama -Slowllama is a python project purely focusing on finetuning LLAMA model on MacBook. It offloads weights to SSD to support training of large-sized model, i.e. 70B parameters. +Slowllama is a python project purely focusing on finetuning LLAMA-2 model on MacBook. It offloads weights to SSD to support training of large-sized model, i.e. 70B parameters. Please refer to `./slowllama/` for specific instructions of usage \ No newline at end of file diff --git a/mac/slowllama/llama2/README.md b/mac/slowllama/llama2/README.md index 18f3e2d..c6af363 100644 --- a/mac/slowllama/llama2/README.md +++ b/mac/slowllama/llama2/README.md @@ -12,6 +12,16 @@ project ``` - Download model from [meta-llama/llama](https://github.com/meta-llama/llama) to -this dir +this dir, and put it like `./llama-2-7b`, at the same level with this README -- Suppose the downloaded model is in dir `llama-2-7b` \ No newline at end of file +- Install submodules + ``` + git submodule init + git submodule update --init --recursive + ``` + +- Install llama as module + ``` + cd model + python setup.py install + ``` \ No newline at end of file diff --git a/mac/slowllama/llama2/slowllama.py b/mac/slowllama/llama2/slowllama.py index 8c5f0d4..b137333 100644 --- a/mac/slowllama/llama2/slowllama.py +++ b/mac/slowllama/llama2/slowllama.py @@ -10,7 +10,8 @@ import glob import shutil -from llama2 import Transformer +# from llama2 import Transformer +from model.llama import Transformer from dataclasses import dataclass from typing import Optional @@ -264,7 +265,6 @@ def add_lora(model_path, lora_path): del checkpoint gc.collect() - logging.basicConfig( format="%(asctime)s %(message)s", level=logging.DEBUG, @@ -272,10 +272,11 @@ def add_lora(model_path, lora_path): ) torch.random.manual_seed(seed) -prepare_model( - llama2_path=llama2_model_path, - frozen_path=frozen_model_path, - compute_dtype=compute_dtype, - lora_rank=lora_rank, - frozen_dtype=frozen_dtype, -) +if __name__ == '__main__' and __package__ is None: + prepare_model( + llama2_path=llama2_model_path, + frozen_path=frozen_model_path, + compute_dtype=compute_dtype, + lora_rank=lora_rank, + frozen_dtype=frozen_dtype, + ) From 8c52b8e7cc6b390c5e4b537c1b8f102b8ddc2d36 Mon Sep 17 00:00:00 2001 From: jazelly Date: Wed, 8 May 2024 23:01:57 +0930 Subject: [PATCH 15/96] feat: load llama 2 --- .gitmodules | 2 +- mac/slowllama/llama2/README.md | 7 ++-- .../llama2/{slowllama.py => load.py} | 33 ++++++++++++++----- mac/slowllama/{ => llama2}/slowllama | 0 4 files changed, 30 insertions(+), 12 deletions(-) rename mac/slowllama/llama2/{slowllama.py => load.py} (93%) rename mac/slowllama/{ => llama2}/slowllama (100%) diff --git a/.gitmodules b/.gitmodules index 5b0f002..ee42b95 100644 --- a/.gitmodules +++ b/.gitmodules @@ -2,5 +2,5 @@ path = llama-gguf/llama.cpp url = git@github.com:ggerganov/llama.cpp.git [submodule "mac/slowllama/slowllama"] - path = mac/slowllama/slowllama + path = mac/slowllama/llama2/slowllama url = git@github.com:jazelly/slowllama.git \ No newline at end of file diff --git a/mac/slowllama/llama2/README.md b/mac/slowllama/llama2/README.md index c6af363..bd27bb4 100644 --- a/mac/slowllama/llama2/README.md +++ b/mac/slowllama/llama2/README.md @@ -20,8 +20,9 @@ this dir, and put it like `./llama-2-7b`, at the same level with this README git submodule update --init --recursive ``` -- Install llama as module +- Update `config.py` to match model path + +- Prepare model first ``` - cd model - python setup.py install + python slowllama.py ``` \ No newline at end of file diff --git a/mac/slowllama/llama2/slowllama.py b/mac/slowllama/llama2/load.py similarity index 93% rename from mac/slowllama/llama2/slowllama.py rename to mac/slowllama/llama2/load.py index b137333..592db8a 100644 --- a/mac/slowllama/llama2/slowllama.py +++ b/mac/slowllama/llama2/load.py @@ -10,8 +10,30 @@ import glob import shutil -# from llama2 import Transformer -from model.llama import Transformer +import sys +from pathlib import Path + +logging.basicConfig( + format="%(asctime)s %(message)s", + level=logging.DEBUG, + filename="logs/prepare_model.log", +) + +file = Path(__file__).resolve() +temp_syspath_llama2 = str(file.parent) + "/slowllama" +sys.path.append(temp_syspath_llama2) +logging.info(f"Added syspath {temp_syspath_llama2}") + +from llama2 import Transformer + +try: + logging.info(f"Removing syspath {temp_syspath_llama2}") + sys.path.remove(temp_syspath_llama2) + logging.info(f"Removed syspath {temp_syspath_llama2}") +except ValueError: + logging.WARN(f"Error occurred while trying to remove syspath {temp_syspath_llama2}") + logging.WARN(ValueError) + pass from dataclasses import dataclass from typing import Optional @@ -265,14 +287,9 @@ def add_lora(model_path, lora_path): del checkpoint gc.collect() -logging.basicConfig( - format="%(asctime)s %(message)s", - level=logging.DEBUG, - filename="logs/prepare_model.log", -) torch.random.manual_seed(seed) -if __name__ == '__main__' and __package__ is None: +if __name__ == "__main__" and __package__ is None: prepare_model( llama2_path=llama2_model_path, frozen_path=frozen_model_path, diff --git a/mac/slowllama/slowllama b/mac/slowllama/llama2/slowllama similarity index 100% rename from mac/slowllama/slowllama rename to mac/slowllama/llama2/slowllama From 1b80d9614856a4661423d41b54ec634d317c58c6 Mon Sep 17 00:00:00 2001 From: jazelly Date: Thu, 9 May 2024 08:59:26 +0930 Subject: [PATCH 16/96] chore: update ignore --- .gitignore | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.gitignore b/.gitignore index d86ec6e..23f3a17 100644 --- a/.gitignore +++ b/.gitignore @@ -162,4 +162,4 @@ cython_debug/ checkpoint_dir/ results/ -llama-2-7b/ \ No newline at end of file +llama-2-7b*/ From 9a5e79fdab242a6c4692002ab97391f8a1ab794a Mon Sep 17 00:00:00 2001 From: jazelly Date: Thu, 9 May 2024 21:10:45 +0930 Subject: [PATCH 17/96] chore: update readme --- phi3/README.md | 16 ++++++++++++++++ phi3/script/sft.py | 15 --------------- 2 files changed, 16 insertions(+), 15 deletions(-) create mode 100644 phi3/README.md diff --git a/phi3/README.md b/phi3/README.md new file mode 100644 index 0000000..1ed031e --- /dev/null +++ b/phi3/README.md @@ -0,0 +1,16 @@ +A simple example on using SFTTrainer and Accelerate to finetune Phi-3 models. For +a more advanced example, please follow HF alignment-handbook/scripts/run_sft.py + +1. Install accelerate: + conda install -c conda-forge accelerate +2. Setup accelerate config: + accelerate config to simply use all the GPUs available: + ``` + python -c "from accelerate.utils import write_basic_config; write_basic_config(mixed_precision='bf16')" + ``` + check accelerate config: + `accelerate env` +3. Run the code: + ``` + accelerate launch script/sft.py + ``` \ No newline at end of file diff --git a/phi3/script/sft.py b/phi3/script/sft.py index 1e7e8bd..f6cf6a7 100644 --- a/phi3/script/sft.py +++ b/phi3/script/sft.py @@ -3,21 +3,6 @@ from trl import SFTTrainer from transformers import AutoModelForCausalLM, AutoTokenizer, TrainingArguments -""" -A simple example on using SFTTrainer and Accelerate to finetune Phi-3 models. For -a more advanced example, please follow HF alignment-handbook/scripts/run_sft.py -1. Install accelerate: - conda install -c conda-forge accelerate -2. Setup accelerate config: - accelerate config -to simply use all the GPUs available: - python -c "from accelerate.utils import write_basic_config; write_basic_config(mixed_precision='bf16')" -check accelerate config: - accelerate env -3. Run the code: - accelerate launch sample_finetune.py -""" - ################### # Hyper-parameters ################### From 5b4484fdc2f740d99d8cdfb84fd6e179f114bf16 Mon Sep 17 00:00:00 2001 From: jazelly Date: Thu, 9 May 2024 21:10:57 +0930 Subject: [PATCH 18/96] chore: update readme --- README.md | 14 ++++++++++++++ 1 file changed, 14 insertions(+) diff --git a/README.md b/README.md index c8dd57c..3db13c5 100644 --- a/README.md +++ b/README.md @@ -5,6 +5,20 @@ This repo aims to provide the finest collection of all tuning scripts that can b Every training script in this repo is tested across multiple platforms. +## Supported finetuning techniques + +There are still a lot to implement, so stay tuned. + +| Model | SFT | DPO | ORPO | KTO | PRO | +|------------|-----|-----|------|-----|-----| +| llama 2 | ✅ | ❌ | ❌ | ❌ | ❌ | +| llama 3 | ✅ | ❌ | ✅ | ❌ | ❌ | +| llama-gguf | ✅ | ❌ | ❌ | ❌ | ❌ | +| llama-ggml | ❌ | ❌ | ❌ | ❌ | ❌ | +| phi-3 | ✅ | ❌ | ❌ | ❌ | ❌ | +| Mistral | ✅ | ✅ | ❌ | ❌ | ❌ | + + ## General Setup - Install pytorch From 7cbfab83ddf386764e2a65020a85494a19c7d6e4 Mon Sep 17 00:00:00 2001 From: jazelly Date: Sat, 11 May 2024 22:27:43 +0930 Subject: [PATCH 19/96] feat: support slowllama --- mac/slowllama/llama2/README.md | 7 +- mac/slowllama/llama2/config.py | 10 +- mac/slowllama/llama2/finetune.py | 107 ++++++++++++++++++ mac/slowllama/llama2/infer.py | 25 ++++ .../llama2/{load.py => load_model.py} | 16 +-- mac/slowllama/llama2/utils.py | 94 +++++++++++++++ 6 files changed, 247 insertions(+), 12 deletions(-) create mode 100644 mac/slowllama/llama2/finetune.py create mode 100644 mac/slowllama/llama2/infer.py rename mac/slowllama/llama2/{load.py => load_model.py} (96%) create mode 100644 mac/slowllama/llama2/utils.py diff --git a/mac/slowllama/llama2/README.md b/mac/slowllama/llama2/README.md index bd27bb4..03bfda6 100644 --- a/mac/slowllama/llama2/README.md +++ b/mac/slowllama/llama2/README.md @@ -24,5 +24,10 @@ this dir, and put it like `./llama-2-7b`, at the same level with this README - Prepare model first ``` - python slowllama.py + python load_model.py + ``` + +- Once it's done, you can finetune it by + ``` + python finetune.py ``` \ No newline at end of file diff --git a/mac/slowllama/llama2/config.py b/mac/slowllama/llama2/config.py index 6da85a5..6dec628 100644 --- a/mac/slowllama/llama2/config.py +++ b/mac/slowllama/llama2/config.py @@ -49,14 +49,18 @@ snapshots_path = 'out' # plaintext input file which will be tokenized and used for training -finetune_file = '../slowllama/test_data/cubestat.txt' +finetune_file = './slowllama/test_data/cubestat.txt' # which model to use - path to raw model -llama2_model_path = './llama-2-7b' +llama2_model_path = './llama-2-7b-chat' adamw_eps = 1e-4 compute_dtype = torch.float16 frozen_dtype = torch.float16 # trained model to store -frozen_model_path = './llama-2-7b_f16' \ No newline at end of file +frozen_model_path = llama2_model_path + '_f16' + +adamw_eps = 1e-4 +compute_dtype = torch.float16 +frozen_dtype = torch.float16 diff --git a/mac/slowllama/llama2/finetune.py b/mac/slowllama/llama2/finetune.py new file mode 100644 index 0000000..e6b4bfa --- /dev/null +++ b/mac/slowllama/llama2/finetune.py @@ -0,0 +1,107 @@ +import os +import torch +import logging +from load_model import load_frozen +from config import * +from utils import Tokenizer, greedy_gen + +logging.basicConfig( + format="%(asctime)s %(message)s", + level=logging.DEBUG, + filename="logs/finetune.log", +) + +def log_lora(lora_layers, log_weights=True, log_grad=True, log_level=logging.INFO): + if not log_weights and not log_grad: + return + try: + from fewlines import bar + except ImportError: + logging.error('Unable to import fewlines. "pip install fewlines" to use distribution logging') + return + + gradients_a = {} + gradients_b = {} + weights_a = {} + weights_b = {} + + for i, lora in enumerate(lora_layers): + q = lora['q_lora'] + v = lora['v_lora'] + if log_grad: + gradients_a[f'Q{i}.A'] = q.A.weight.grad.view(-1).to(torch.float32).tolist() + gradients_b[f'Q{i}.B'] = q.B.weight.grad.view(-1).to(torch.float32).tolist() + gradients_a[f'V{i}.A'] = v.A.weight.grad.view(-1).to(torch.float32).tolist() + gradients_b[f'V{i}.B'] = v.B.weight.grad.view(-1).to(torch.float32).tolist() + if log_weights: + weights_a[f'Q{i}.A'] = q.A.weight.view(-1).to(torch.float32).tolist() + weights_b[f'Q{i}.B'] = q.B.weight.view(-1).to(torch.float32).tolist() + weights_a[f'V{i}.A'] = v.A.weight.view(-1).to(torch.float32).tolist() + weights_b[f'V{i}.B'] = v.B.weight.view(-1).to(torch.float32).tolist() + + if log_grad: + logging.log(log_level, f'\n=== GRADIENTS A ===') + for l in bar.bar_histograms(gradients_a): + logging.log(log_level, l) + + logging.log(log_level, f'\n=== GRADIENTS B ===') + for l in bar.bar_histograms(gradients_b): + logging.log(log_level, l) + + if log_weights: + logging.log(log_level, f'\n=== WEIGHTS A ===') + for l in bar.bar_histograms(weights_a): + logging.log(log_level, l) + + logging.log(log_level, f'\n=== WEIGHTS B ===') + for l in bar.bar_histograms(weights_b): + logging.log(log_level, l) + +if __name__ == '__main__': + logging.basicConfig(format='%(asctime)s %(message)s', level=log_level, filename='logs/finetune.log') + torch.random.manual_seed(seed) + + if not os.path.exists(snapshots_path): + os.makedirs(snapshots_path) + + # data to finetune on + with open(finetune_file) as f: + text = f.read() + + tokenizer = Tokenizer(os.path.join(frozen_model_path, 'tokenizer.model')) + tokens = tokenizer.encode(text, True, True) + + logging.info(f'loaded dataset: {len(tokens)} tokens') + + model = load_frozen(frozen_model_path, compute_dtype=compute_dtype, lora_rank=lora_rank, frozen_dtype=frozen_dtype).to(device).to(compute_dtype) + + def get_batch(batch_size): + index = torch.randint(len(tokens) - seq_len, (batch_size,)) + x = torch.stack([torch.tensor(tokens[i:i + seq_len]).to(torch.int64) for i in index]) + y = torch.stack([torch.tensor(tokens[i + 1:i + seq_len + 1]).to(torch.int64) for i in index]) + return x.to(device), y.to(device) + + opt = torch.optim.AdamW(model.parameters(), lr=lr, eps=adamw_eps) + + last_loss = None + for i in range(iters): + if i % eval_period == 0 and (i > 0 or eval_before_training): + greedy_gen(model, tokenizer, device, prompt, gen_tokens) + logging.info(f'starting iteration {i}') + X, y = get_batch(batch_size) + opt.zero_grad() + # both forward and backward passes are here. + # returned loss is a scalar, not variable + loss = model.manual_loop(X, y) + opt.step() + + # optional logging of lora weights/gradients + log_lora(model.lora_layers, log_weights=log_lora_weight, log_grad=log_lora_grad) + + logging.info(f'backprop done, loss after forward pass = {loss}') + if last_loss is None: + last_loss = loss + elif loss < last_loss: + last_loss = loss + logging.info(f'saving snapshot') + torch.save(model.state_dict(), os.path.join(snapshots_path, f'state_dict_{i}.pth')) diff --git a/mac/slowllama/llama2/infer.py b/mac/slowllama/llama2/infer.py new file mode 100644 index 0000000..bc8d764 --- /dev/null +++ b/mac/slowllama/llama2/infer.py @@ -0,0 +1,25 @@ +import logging +import torch +import sys +import os + +from load_model import load_frozen +from utils import Tokenizer, greedy_gen +from config import * + +logging.basicConfig(format='%(asctime)s %(message)s', level=logging.DEBUG) + +lora_weights = sys.argv[1] if len(sys.argv) > 1 else None + +tokenizer_path = os.path.join(frozen_model_path, 'tokenizer.model') +tokenizer = Tokenizer(tokenizer_path) + +model = load_frozen(frozen_model_path, dropout=0.0, lora_rank=lora_rank, frozen_dtype=frozen_dtype, compute_dtype=compute_dtype).to(device) +if lora_weights is not None: + logging.debug(model.load_state_dict(torch.load(lora_weights), strict=False)) + +logging.info('Model loaded.') + +prompt = 'Cubestat reports the following metrics: ' + +greedy_gen(model, tokenizer, device, prompt, max_new_tokens=100) diff --git a/mac/slowllama/llama2/load.py b/mac/slowllama/llama2/load_model.py similarity index 96% rename from mac/slowllama/llama2/load.py rename to mac/slowllama/llama2/load_model.py index 592db8a..39239a5 100644 --- a/mac/slowllama/llama2/load.py +++ b/mac/slowllama/llama2/load_model.py @@ -16,22 +16,22 @@ logging.basicConfig( format="%(asctime)s %(message)s", level=logging.DEBUG, - filename="logs/prepare_model.log", + filename="logs/load_model.log", ) file = Path(__file__).resolve() -temp_syspath_llama2 = str(file.parent) + "/slowllama" -sys.path.append(temp_syspath_llama2) -logging.info(f"Added syspath {temp_syspath_llama2}") +temp_syspath_slowllama = str(file.parent) + "/slowllama" +sys.path.append(temp_syspath_slowllama) +logging.debug(f"Added syspath {temp_syspath_slowllama}") from llama2 import Transformer try: - logging.info(f"Removing syspath {temp_syspath_llama2}") - sys.path.remove(temp_syspath_llama2) - logging.info(f"Removed syspath {temp_syspath_llama2}") + logging.debug(f"Removing syspath {temp_syspath_slowllama}") + sys.path.remove(temp_syspath_slowllama) + logging.debug(f"Removed syspath {temp_syspath_slowllama}") except ValueError: - logging.WARN(f"Error occurred while trying to remove syspath {temp_syspath_llama2}") + logging.WARN(f"Error occurred while trying to remove syspath {temp_syspath_slowllama}") logging.WARN(ValueError) pass diff --git a/mac/slowllama/llama2/utils.py b/mac/slowllama/llama2/utils.py new file mode 100644 index 0000000..fa56f85 --- /dev/null +++ b/mac/slowllama/llama2/utils.py @@ -0,0 +1,94 @@ +import torch +import sentencepiece +import logging + +def device_map(device): + if str(device).startswith('mps'): + return 'mps' + return str(device) + +def device_supports_dtype(device, dtype): + try: + a = torch.rand(2, 2).to(device).to(dtype) + b = torch.rand(2, 2).to(device).to(dtype) + c = a.mm(b) + logging.debug(f'success, {device} supports {dtype}') + return True + except TypeError as e: + return False + +global_id_auto = 0 + +def next_id(): + global global_id_auto + new_id = global_id_auto + global_id_auto += 1 + return new_id + +def save_rng_state(device='cpu'): + if device == 'cpu': + import torch + return torch.random.get_rng_state() + elif device.startswith('cuda'): + import torch.cuda + return torch.cuda.get_rng_state(device=int(device.split(':')[1])) + elif device.startswith('mps'): + import torch.mps + return torch.mps.get_rng_state() + else: + raise ValueError(f"Unsupported device: {device}") + +def restore_rng_state(rng_state, device='cpu'): + if device == 'cpu': + import torch + torch.random.set_rng_state(rng_state) + elif device.startswith('cuda'): + import torch.cuda + torch.cuda.set_rng_state(rng_state, device=int(device.split(':')[1])) + elif device.startswith('mps'): + import torch.mps + torch.mps.set_rng_state(rng_state) + else: + raise ValueError(f"Unsupported device: {device}") + +def greedy_gen(model, tokenizer, device, prompt, max_new_tokens=50): + tokens = torch.tensor(tokenizer.encode(prompt, True, False)).view(1, -1).to(device) + model.eval() + for _ in range(max_new_tokens): + logits = model(tokens) + logits = logits[:, -1, :] + _, next_token = torch.topk(logits, k=1, dim=-1) + logging.info(f'next token: {next_token} {tokenizer.decode(next_token.tolist())}') + tokens = torch.cat((tokens, next_token), dim=1) + + for i, output in enumerate(tokens): + logging.info(f'{i} - {tokenizer.decode(output.tolist())}') + +def greedy_gen2(model, tokenizer, device, prompt, max_new_tokens=50): + tokens = torch.tensor(tokenizer.encode(prompt, True, False)).view(1, -1).to(device) + model.eval() + for _ in range(max_new_tokens): + logits = model(tokens) + logits = logits[:, -1, :] + _, next_token = torch.topk(logits, k=1, dim=-1) + logging.info(f'next token: {next_token} {tokenizer.decode(next_token.tolist())}') + yield tokenizer.decode(next_token.tolist())[0] + tokens = torch.cat((tokens, next_token), dim=1) + +def cleanup_cache(device='cpu'): + if device.startswith('mps'): + import torch.mps + torch.mps.empty_cache() + + +class Tokenizer: + def __init__(self, path): + self.model = sentencepiece.SentencePieceProcessor(path) + + def encode(self, text, bos=False, eos=False): + b = [self.model.bos_id()] if bos else [] + e = [self.model.eos_id()] if eos else [] + return b + self.model.encode(text) + e + + def decode(self, tokens): + return self.model.decode(tokens) From 864179fb5f69253a9dec8062160b106cc4396d68 Mon Sep 17 00:00:00 2001 From: jazelly Date: Sun, 12 May 2024 18:45:39 +0930 Subject: [PATCH 20/96] wip: client --- .gitignore | 1 + README.md | 3 +- client/package-lock.json | 6968 ++++++++++++++++++++++++++++++++++++++ client/package.json | 66 + client/src/App.tsx | 161 + 5 files changed, 7198 insertions(+), 1 deletion(-) create mode 100644 client/package-lock.json create mode 100644 client/package.json create mode 100644 client/src/App.tsx diff --git a/.gitignore b/.gitignore index 23f3a17..0060036 100644 --- a/.gitignore +++ b/.gitignore @@ -163,3 +163,4 @@ cython_debug/ checkpoint_dir/ results/ llama-2-7b*/ +node_modules/ \ No newline at end of file diff --git a/README.md b/README.md index 3db13c5..c1364e2 100644 --- a/README.md +++ b/README.md @@ -14,7 +14,6 @@ There are still a lot to implement, so stay tuned. | llama 2 | ✅ | ❌ | ❌ | ❌ | ❌ | | llama 3 | ✅ | ❌ | ✅ | ❌ | ❌ | | llama-gguf | ✅ | ❌ | ❌ | ❌ | ❌ | -| llama-ggml | ❌ | ❌ | ❌ | ❌ | ❌ | | phi-3 | ✅ | ❌ | ❌ | ❌ | ❌ | | Mistral | ✅ | ✅ | ❌ | ❌ | ❌ | @@ -61,6 +60,8 @@ Please note, there might be other dependencies for different model training tech - [x] Support training at GGUF level - [x] Explore `ollama` and `llama.cpp` +- [ ] Expose scripts as API and GUI +- [ ] Containerize backend and frontend - [ ] Explore `mlx-examples` - [ ] Support other models than LLAMA - [ ] Explore `pykan` diff --git a/client/package-lock.json b/client/package-lock.json new file mode 100644 index 0000000..3185954 --- /dev/null +++ b/client/package-lock.json @@ -0,0 +1,6968 @@ +{ + "name": "finetune_llms_frontend", + "lockfileVersion": 3, + "requires": true, + "packages": { + "": { + "name": "finetune_llms_frontend", + "license": "MIT", + "dependencies": { + "@metamask/jazzicon": "^2.0.0", + "@microsoft/fetch-event-source": "^2.0.1", + "@phosphor-icons/react": "^2.0.13", + "@tremor/react": "^3.15.1", + "dompurify": "^3.0.8", + "file-saver": "^2.0.5", + "he": "^1.2.0", + "highlight.js": "^11.9.0", + "lodash.debounce": "^4.0.8", + "markdown-it": "^13.0.1", + "pluralize": "^8.0.0", + "react": "^18.2.0", + "react-device-detect": "^2.2.2", + "react-dom": "^18.2.0", + "react-dropzone": "^14.2.3", + "react-loading-skeleton": "^3.1.0", + "react-router-dom": "^6.3.0", + 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build", + "lint": "yarn prettier --write ./src", + "preview": "vite preview" + }, + "dependencies": { + "@metamask/jazzicon": "^2.0.0", + "@microsoft/fetch-event-source": "^2.0.1", + "@phosphor-icons/react": "^2.0.13", + "@tremor/react": "^3.15.1", + "dompurify": "^3.0.8", + "file-saver": "^2.0.5", + "he": "^1.2.0", + "highlight.js": "^11.9.0", + "lodash.debounce": "^4.0.8", + "markdown-it": "^13.0.1", + "pluralize": "^8.0.0", + "react": "^18.2.0", + "react-device-detect": "^2.2.2", + "react-dom": "^18.2.0", + "react-dropzone": "^14.2.3", + "react-loading-skeleton": "^3.1.0", + "react-router-dom": "^6.3.0", + "react-tag-input-component": "^2.0.2", + "react-toastify": "^9.1.3", + "react-tooltip": "^5.25.2", + "recharts": "^2.12.5", + "recharts-to-png": "^2.3.1", + "text-case": "^1.0.9", + "truncate": "^3.0.0", + "uuid": "^9.0.0" + }, + "devDependencies": { + "@esbuild-plugins/node-globals-polyfill": "^0.1.1", + "@types/react": "^18.2.23", + "@types/react-dom": "^18.2.8", + "@types/react-router-dom": "^5.3.3", + "@vitejs/plugin-react": "^4.0.0-beta.0", + "autoprefixer": "^10.4.14", + "buffer": "^6.0.3", + "eslint": "^8.50.0", + "eslint-config-prettier": "^9.0.0", + "eslint-plugin-ft-flow": "^3.0.0", + "eslint-plugin-prettier": "^5.0.0", + "eslint-plugin-react": "^7.33.2", + "eslint-plugin-react-hooks": "^4.6.0", + "eslint-plugin-react-refresh": "^0.4.3", + "flow-bin": "^0.217.0", + "flow-remove-types": "^2.217.1", + "globals": "^13.21.0", + "hermes-eslint": "^0.15.0", + "postcss": "^8.4.23", + "prettier": "^3.0.3", + "rollup-plugin-visualizer": "^5.9.0", + "tailwindcss": "^3.3.1", + "typescript": "^5.4.5", + "vite": "^4.3.0" + } +} diff --git a/client/src/App.tsx b/client/src/App.tsx new file mode 100644 index 0000000..0a5ed65 --- /dev/null +++ b/client/src/App.tsx @@ -0,0 +1,161 @@ +import React, { lazy, Suspense } from "react"; +import { Routes, Route } from "react-router-dom"; +import { ContextWrapper } from "@/AuthContext"; +import PrivateRoute, { + AdminRoute, + ManagerRoute, +} from "@/components/PrivateRoute"; +import { ToastContainer } from "react-toastify"; +import "react-toastify/dist/ReactToastify.css"; +import Login from "@/pages/Login"; +import OnboardingFlow from "@/pages/OnboardingFlow"; + +import { PfpProvider } from "./PfpContext"; +import { LogoProvider } from "./LogoContext"; + +const Main = lazy(() => import("@/pages/Main")); +const InvitePage = lazy(() => import("@/pages/Invite")); +const WorkspaceChat = lazy(() => import("@/pages/WorkspaceChat")); +const AdminUsers = lazy(() => import("@/pages/Admin/Users")); +const AdminInvites = lazy(() => import("@/pages/Admin/Invitations")); +const AdminWorkspaces = lazy(() => import("@/pages/Admin/Workspaces")); +const AdminSystem = lazy(() => import("@/pages/Admin/System")); +const AdminLogs = lazy(() => import("@/pages/Admin/Logging")); +const GeneralChats = lazy(() => import("@/pages/GeneralSettings/Chats")); +const GeneralAppearance = lazy( + () => import("@/pages/GeneralSettings/Appearance") +); +const GeneralApiKeys = lazy(() => import("@/pages/GeneralSettings/ApiKeys")); +const GeneralLLMPreference = lazy( + () => import("@/pages/GeneralSettings/LLMPreference") +); +const GeneralTranscriptionPreference = lazy( + () => import("@/pages/GeneralSettings/TranscriptionPreference") +); +const GeneralEmbeddingPreference = lazy( + () => import("@/pages/GeneralSettings/EmbeddingPreference") +); +const EmbeddingTextSplitterPreference = lazy( + () => import("@/pages/GeneralSettings/EmbeddingTextSplitterPreference") +); +const GeneralVectorDatabase = lazy( + () => import("@/pages/GeneralSettings/VectorDatabase") +); +const GeneralSecurity = lazy(() => import("@/pages/GeneralSettings/Security")); +const WorkspaceSettings = lazy(() => import("@/pages/WorkspaceSettings")); +const EmbedConfigSetup = lazy( + () => import("@/pages/GeneralSettings/EmbedConfigs") +); +const EmbedChats = lazy(() => import("@/pages/GeneralSettings/EmbedChats")); +const PrivacyAndData = lazy( + () => import("@/pages/GeneralSettings/PrivacyAndData") +); + +export default function App() { + return ( + }> + + + + + } /> + } /> + } + /> + } + /> + } + /> + } /> + + {/* Admin */} + } + /> + + } + /> + } + /> + + } + /> + } + /> + } + /> + } + /> + } + /> + {/* Manager */} + } + /> + } + /> + } + /> + } + /> + } + /> + } + /> + } + /> + } + /> + } + /> + {/* Onboarding Flow */} + } /> + } /> + + + + + + + ); +} From 61efbe697c037ddecde4ac68339355045d4f1b8d Mon Sep 17 00:00:00 2001 From: jazelly Date: Fri, 24 May 2024 22:05:26 +0930 Subject: [PATCH 21/96] feat: expose as ui and server --- .gitignore | 3 +- README.md | 5 + client/package-lock.json | 6968 ----------------- frontend/.env.example | 3 + frontend/.gitignore | 29 + frontend/.nvmrc | 1 + frontend/index.html | 38 + frontend/jsconfig.json | 12 + {client => frontend}/package.json | 3 +- frontend/postcss.config.js | 7 + frontend/public/anything-llm-dark.png | Bin 0 -> 8413 bytes 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trainer/trainer_api/scheduler/worker.py create mode 100644 trainer/trainer_api/tests.py create mode 100644 trainer/trainer_api/urls.py create mode 100644 trainer/trainer_api/views.py create mode 100644 trainer/trainer_router/__init__.py create mode 100644 trainer/trainer_router/asgi.py create mode 100644 trainer/trainer_router/settings.py create mode 100644 trainer/trainer_router/urls.py create mode 100644 trainer/trainer_router/wsgi.py diff --git a/.gitignore b/.gitignore index 0060036..41b12b5 100644 --- a/.gitignore +++ b/.gitignore @@ -163,4 +163,5 @@ cython_debug/ checkpoint_dir/ results/ llama-2-7b*/ -node_modules/ \ No newline at end of file +node_modules/ +logs/** */ \ No newline at end of file diff --git a/README.md b/README.md index c1364e2..5950d87 100644 --- a/README.md +++ b/README.md @@ -20,6 +20,11 @@ There are still a lot to implement, so stay tuned. ## General Setup +- Pull submodules + ``` + git submodule update --init + ``` + - Install pytorch The easist way to do this is via conda. If you don't have conda, please go to [the installation guide](https://conda.io/projects/conda/en/latest/user-guide/install/index.html) diff --git a/client/package-lock.json b/client/package-lock.json deleted file mode 100644 index 3185954..0000000 --- a/client/package-lock.json +++ /dev/null @@ -1,6968 +0,0 @@ -{ - "name": "finetune_llms_frontend", - "lockfileVersion": 3, - "requires": true, - "packages": { - "": { - "name": "finetune_llms_frontend", - "license": "MIT", - "dependencies": { - "@metamask/jazzicon": "^2.0.0", - "@microsoft/fetch-event-source": "^2.0.1", - "@phosphor-icons/react": "^2.0.13", - "@tremor/react": "^3.15.1", - "dompurify": "^3.0.8", - "file-saver": "^2.0.5", - "he": "^1.2.0", - "highlight.js": "^11.9.0", - "lodash.debounce": "^4.0.8", - "markdown-it": "^13.0.1", - "pluralize": "^8.0.0", - "react": "^18.2.0", - "react-device-detect": "^2.2.2", - "react-dom": "^18.2.0", - "react-dropzone": "^14.2.3", - "react-loading-skeleton": "^3.1.0", - "react-router-dom": "^6.3.0", - 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+ + + + \ No newline at end of file diff --git a/frontend/jsconfig.json b/frontend/jsconfig.json new file mode 100644 index 0000000..c8cc81f --- /dev/null +++ b/frontend/jsconfig.json @@ -0,0 +1,12 @@ +{ + "compilerOptions": { + "module": "commonjs", + "target": "esnext", + "jsx": "react", + "paths": { + "@/*": [ + "./src/*" + ], + } + } +} \ No newline at end of file diff --git a/client/package.json b/frontend/package.json similarity index 96% rename from client/package.json rename to frontend/package.json index 3106dd2..1c988eb 100644 --- a/client/package.json +++ b/frontend/package.json @@ -1,5 +1,5 @@ { - "name": "finetune_llms_frontend", + "name": "anything-llm-frontend", "private": false, "license": "MIT", "type": "module", @@ -28,6 +28,7 @@ "react-dropzone": "^14.2.3", "react-loading-skeleton": "^3.1.0", "react-router-dom": "^6.3.0", + "react-speech-recognition": "^3.10.0", "react-tag-input-component": "^2.0.2", "react-toastify": "^9.1.3", "react-tooltip": "^5.25.2", diff --git 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between:"≬",bfr:"𝔟",Bfr:"𝔅",bigcap:"⋂",bigcirc:"◯",bigcup:"⋃",bigodot:"⨀",bigoplus:"⨁",bigotimes:"⨂",bigsqcup:"⨆",bigstar:"★",bigtriangledown:"▽",bigtriangleup:"△",biguplus:"⨄",bigvee:"⋁",bigwedge:"⋀",bkarow:"⤍",blacklozenge:"⧫",blacksquare:"▪",blacktriangle:"▴",blacktriangledown:"▾",blacktriangleleft:"◂",blacktriangleright:"▸",blank:"␣",blk12:"▒",blk14:"░",blk34:"▓",block:"█",bne:"=⃥",bnequiv:"≡⃥",bnot:"⌐",bNot:"⫭",bopf:"𝕓",Bopf:"𝔹",bot:"⊥",bottom:"⊥",bowtie:"⋈",boxbox:"⧉",boxdl:"┐",boxdL:"╕",boxDl:"╖",boxDL:"╗",boxdr:"┌",boxdR:"╒",boxDr:"╓",boxDR:"╔",boxh:"─",boxH:"═",boxhd:"┬",boxhD:"╥",boxHd:"╤",boxHD:"╦",boxhu:"┴",boxhU:"╨",boxHu:"╧",boxHU:"╩",boxminus:"⊟",boxplus:"⊞",boxtimes:"⊠",boxul:"┘",boxuL:"╛",boxUl:"╜",boxUL:"╝",boxur:"└",boxuR:"╘",boxUr:"╙",boxUR:"╚",boxv:"│",boxV:"║",boxvh:"┼",boxvH:"╪",boxVh:"╫",boxVH:"╬",boxvl:"┤",boxvL:"╡",boxVl:"╢",boxVL:"╣",boxvr:"├",boxvR:"╞",boxVr:"╟",boxVR:"╠",bprime:"‵",breve:"˘",Breve:"˘",brvbar:"¦",bscr:"𝒷",Bscr:"ℬ",bsemi:"⁏",bsim:"∽",bsime:"⋍",bsol:"\\",bsolb:"⧅",bsolhsub:"⟈",bull:"•",bullet:"•",bump:"≎",bumpe:"≏",bumpE:"⪮",bumpeq:"≏",Bumpeq:"≎",cacute:"ć",Cacute:"Ć",cap:"∩",Cap:"⋒",capand:"⩄",capbrcup:"⩉",capcap:"⩋",capcup:"⩇",capdot:"⩀",CapitalDifferentialD:"ⅅ",caps:"∩︀",caret:"⁁",caron:"ˇ",Cayleys:"ℭ",ccaps:"⩍",ccaron:"č",Ccaron:"Č",ccedil:"ç",Ccedil:"Ç",ccirc:"ĉ",Ccirc:"Ĉ",Cconint:"∰",ccups:"⩌",ccupssm:"⩐",cdot:"ċ",Cdot:"Ċ",cedil:"¸",Cedilla:"¸",cemptyv:"⦲",cent:"¢",centerdot:"·",CenterDot:"·",cfr:"𝔠",Cfr:"ℭ",chcy:"ч",CHcy:"Ч",check:"✓",checkmark:"✓",chi:"χ",Chi:"Χ",cir:"○",circ:"ˆ",circeq:"≗",circlearrowleft:"↺",circlearrowright:"↻",circledast:"⊛",circledcirc:"⊚",circleddash:"⊝",CircleDot:"⊙",circledR:"®",circledS:"Ⓢ",CircleMinus:"⊖",CirclePlus:"⊕",CircleTimes:"⊗",cire:"≗",cirE:"⧃",cirfnint:"⨐",cirmid:"⫯",cirscir:"⧂",ClockwiseContourIntegral:"∲",CloseCurlyDoubleQuote:"”",CloseCurlyQuote:"’",clubs:"♣",clubsuit:"♣",colon:":",Colon:"∷",colone:"≔",Colone:"⩴",coloneq:"≔",comma:",",commat:"@",comp:"∁",compfn:"∘",complement:"∁",complexes:"ℂ",cong:"≅",congdot:"⩭",Congruent:"≡",conint:"∮",Conint:"∯",ContourIntegral:"∮",copf:"𝕔",Copf:"ℂ",coprod:"∐",Coproduct:"∐",copy:"©",COPY:"©",copysr:"℗",CounterClockwiseContourIntegral:"∳",crarr:"↵",cross:"✗",Cross:"⨯",cscr:"𝒸",Cscr:"𝒞",csub:"⫏",csube:"⫑",csup:"⫐",csupe:"⫒",ctdot:"⋯",cudarrl:"⤸",cudarrr:"⤵",cuepr:"⋞",cuesc:"⋟",cularr:"↶",cularrp:"⤽",cup:"∪",Cup:"⋓",cupbrcap:"⩈",cupcap:"⩆",CupCap:"≍",cupcup:"⩊",cupdot:"⊍",cupor:"⩅",cups:"∪︀",curarr:"↷",curarrm:"⤼",curlyeqprec:"⋞",curlyeqsucc:"⋟",curlyvee:"⋎",curlywedge:"⋏",curren:"¤",curvearrowleft:"↶",curvearrowright:"↷",cuvee:"⋎",cuwed:"⋏",cwconint:"∲",cwint:"∱",cylcty:"⌭",dagger:"†",Dagger:"‡",daleth:"ℸ",darr:"↓",dArr:"⇓",Darr:"↡",dash:"‐",dashv:"⊣",Dashv:"⫤",dbkarow:"⤏",dblac:"˝",dcaron:"ď",Dcaron:"Ď",dcy:"д",Dcy:"Д",dd:"ⅆ",DD:"ⅅ",ddagger:"‡",ddarr:"⇊",DDotrahd:"⤑",ddotseq:"⩷",deg:"°",Del:"∇",delta:"δ",Delta:"Δ",demptyv:"⦱",dfisht:"⥿",dfr:"𝔡",Dfr:"𝔇",dHar:"⥥",dharl:"⇃",dharr:"⇂",DiacriticalAcute:"´",DiacriticalDot:"˙",DiacriticalDoubleAcute:"˝",DiacriticalGrave:"`",DiacriticalTilde:"˜",diam:"⋄",diamond:"⋄",Diamond:"⋄",diamondsuit:"♦",diams:"♦",die:"¨",DifferentialD:"ⅆ",digamma:"ϝ",disin:"⋲",div:"÷",divide:"÷",divideontimes:"⋇",divonx:"⋇",djcy:"ђ",DJcy:"Ђ",dlcorn:"⌞",dlcrop:"⌍",dollar:"$",dopf:"𝕕",Dopf:"𝔻",dot:"˙",Dot:"¨",DotDot:"⃜",doteq:"≐",doteqdot:"≑",DotEqual:"≐",dotminus:"∸",dotplus:"∔",dotsquare:"⊡",doublebarwedge:"⌆",DoubleContourIntegral:"∯",DoubleDot:"¨",DoubleDownArrow:"⇓",DoubleLeftArrow:"⇐",DoubleLeftRightArrow:"⇔",DoubleLeftTee:"⫤",DoubleLongLeftArrow:"⟸",DoubleLongLeftRightArrow:"⟺",DoubleLongRightArrow:"⟹",DoubleRightArrow:"⇒",DoubleRightTee:"⊨",DoubleUpArrow:"⇑",DoubleUpDownArrow:"⇕",DoubleVerticalBar:"∥",downarrow:"↓",Downarrow:"⇓",DownArrow:"↓",DownArrowBar:"⤓",DownArrowUpArrow:"⇵",DownBreve:"̑",downdownarrows:"⇊",downharpoonleft:"⇃",downharpoonright:"⇂",DownLeftRightVector:"⥐",DownLeftTeeVector:"⥞",DownLeftVector:"↽",DownLeftVectorBar:"⥖",DownRightTeeVector:"⥟",DownRightVector:"⇁",DownRightVectorBar:"⥗",DownTee:"⊤",DownTeeArrow:"↧",drbkarow:"⤐",drcorn:"⌟",drcrop:"⌌",dscr:"𝒹",Dscr:"𝒟",dscy:"ѕ",DScy:"Ѕ",dsol:"⧶",dstrok:"đ",Dstrok:"Đ",dtdot:"⋱",dtri:"▿",dtrif:"▾",duarr:"⇵",duhar:"⥯",dwangle:"⦦",dzcy:"џ",DZcy:"Џ",dzigrarr:"⟿",eacute:"é",Eacute:"É",easter:"⩮",ecaron:"ě",Ecaron:"Ě",ecir:"≖",ecirc:"ê",Ecirc:"Ê",ecolon:"≕",ecy:"э",Ecy:"Э",eDDot:"⩷",edot:"ė",eDot:"≑",Edot:"Ė",ee:"ⅇ",efDot:"≒",efr:"𝔢",Efr:"𝔈",eg:"⪚",egrave:"è",Egrave:"È",egs:"⪖",egsdot:"⪘",el:"⪙",Element:"∈",elinters:"⏧",ell:"ℓ",els:"⪕",elsdot:"⪗",emacr:"ē",Emacr:"Ē",empty:"∅",emptyset:"∅",EmptySmallSquare:"◻",emptyv:"∅",EmptyVerySmallSquare:"▫",emsp:" ",emsp13:" ",emsp14:" ",eng:"ŋ",ENG:"Ŋ",ensp:" ",eogon:"ę",Eogon:"Ę",eopf:"𝕖",Eopf:"𝔼",epar:"⋕",eparsl:"⧣",eplus:"⩱",epsi:"ε",epsilon:"ε",Epsilon:"Ε",epsiv:"ϵ",eqcirc:"≖",eqcolon:"≕",eqsim:"≂",eqslantgtr:"⪖",eqslantless:"⪕",Equal:"⩵",equals:"=",EqualTilde:"≂",equest:"≟",Equilibrium:"⇌",equiv:"≡",equivDD:"⩸",eqvparsl:"⧥",erarr:"⥱",erDot:"≓",escr:"ℯ",Escr:"ℰ",esdot:"≐",esim:"≂",Esim:"⩳",eta:"η",Eta:"Η",eth:"ð",ETH:"Ð",euml:"ë",Euml:"Ë",euro:"€",excl:"!",exist:"∃",Exists:"∃",expectation:"ℰ",exponentiale:"ⅇ",ExponentialE:"ⅇ",fallingdotseq:"≒",fcy:"ф",Fcy:"Ф",female:"♀",ffilig:"ffi",fflig:"ff",ffllig:"ffl",ffr:"𝔣",Ffr:"𝔉",filig:"fi",FilledSmallSquare:"◼",FilledVerySmallSquare:"▪",fjlig:"fj",flat:"♭",fllig:"fl",fltns:"▱",fnof:"ƒ",fopf:"𝕗",Fopf:"𝔽",forall:"∀",ForAll:"∀",fork:"⋔",forkv:"⫙",Fouriertrf:"ℱ",fpartint:"⨍",frac12:"½",frac13:"⅓",frac14:"¼",frac15:"⅕",frac16:"⅙",frac18:"⅛",frac23:"⅔",frac25:"⅖",frac34:"¾",frac35:"⅗",frac38:"⅜",frac45:"⅘",frac56:"⅚",frac58:"⅝",frac78:"⅞",frasl:"⁄",frown:"⌢",fscr:"𝒻",Fscr:"ℱ",gacute:"ǵ",gamma:"γ",Gamma:"Γ",gammad:"ϝ",Gammad:"Ϝ",gap:"⪆",gbreve:"ğ",Gbreve:"Ğ",Gcedil:"Ģ",gcirc:"ĝ",Gcirc:"Ĝ",gcy:"г",Gcy:"Г",gdot:"ġ",Gdot:"Ġ",ge:"≥",gE:"≧",gel:"⋛",gEl:"⪌",geq:"≥",geqq:"≧",geqslant:"⩾",ges:"⩾",gescc:"⪩",gesdot:"⪀",gesdoto:"⪂",gesdotol:"⪄",gesl:"⋛︀",gesles:"⪔",gfr:"𝔤",Gfr:"𝔊",gg:"≫",Gg:"⋙",ggg:"⋙",gimel:"ℷ",gjcy:"ѓ",GJcy:"Ѓ",gl:"≷",gla:"⪥",glE:"⪒",glj:"⪤",gnap:"⪊",gnapprox:"⪊",gne:"⪈",gnE:"≩",gneq:"⪈",gneqq:"≩",gnsim:"⋧",gopf:"𝕘",Gopf:"𝔾",grave:"`",GreaterEqual:"≥",GreaterEqualLess:"⋛",GreaterFullEqual:"≧",GreaterGreater:"⪢",GreaterLess:"≷",GreaterSlantEqual:"⩾",GreaterTilde:"≳",gscr:"ℊ",Gscr:"𝒢",gsim:"≳",gsime:"⪎",gsiml:"⪐",gt:">",Gt:"≫",GT:">",gtcc:"⪧",gtcir:"⩺",gtdot:"⋗",gtlPar:"⦕",gtquest:"⩼",gtrapprox:"⪆",gtrarr:"⥸",gtrdot:"⋗",gtreqless:"⋛",gtreqqless:"⪌",gtrless:"≷",gtrsim:"≳",gvertneqq:"≩︀",gvnE:"≩︀",Hacek:"ˇ",hairsp:" ",half:"½",hamilt:"ℋ",hardcy:"ъ",HARDcy:"Ъ",harr:"↔",hArr:"⇔",harrcir:"⥈",harrw:"↭",Hat:"^",hbar:"ℏ",hcirc:"ĥ",Hcirc:"Ĥ",hearts:"♥",heartsuit:"♥",hellip:"…",hercon:"⊹",hfr:"𝔥",Hfr:"ℌ",HilbertSpace:"ℋ",hksearow:"⤥",hkswarow:"⤦",hoarr:"⇿",homtht:"∻",hookleftarrow:"↩",hookrightarrow:"↪",hopf:"𝕙",Hopf:"ℍ",horbar:"―",HorizontalLine:"─",hscr:"𝒽",Hscr:"ℋ",hslash:"ℏ",hstrok:"ħ",Hstrok:"Ħ",HumpDownHump:"≎",HumpEqual:"≏",hybull:"⁃",hyphen:"‐",iacute:"í",Iacute:"Í",ic:"⁣",icirc:"î",Icirc:"Î",icy:"и",Icy:"И",Idot:"İ",iecy:"е",IEcy:"Е",iexcl:"¡",iff:"⇔",ifr:"𝔦",Ifr:"ℑ",igrave:"ì",Igrave:"Ì",ii:"ⅈ",iiiint:"⨌",iiint:"∭",iinfin:"⧜",iiota:"℩",ijlig:"ij",IJlig:"IJ",Im:"ℑ",imacr:"ī",Imacr:"Ī",image:"ℑ",ImaginaryI:"ⅈ",imagline:"ℐ",imagpart:"ℑ",imath:"ı",imof:"⊷",imped:"Ƶ",Implies:"⇒",in:"∈",incare:"℅",infin:"∞",infintie:"⧝",inodot:"ı",int:"∫",Int:"∬",intcal:"⊺",integers:"ℤ",Integral:"∫",intercal:"⊺",Intersection:"⋂",intlarhk:"⨗",intprod:"⨼",InvisibleComma:"⁣",InvisibleTimes:"⁢",iocy:"ё",IOcy:"Ё",iogon:"į",Iogon:"Į",iopf:"𝕚",Iopf:"𝕀",iota:"ι",Iota:"Ι",iprod:"⨼",iquest:"¿",iscr:"𝒾",Iscr:"ℐ",isin:"∈",isindot:"⋵",isinE:"⋹",isins:"⋴",isinsv:"⋳",isinv:"∈",it:"⁢",itilde:"ĩ",Itilde:"Ĩ",iukcy:"і",Iukcy:"І",iuml:"ï",Iuml:"Ï",jcirc:"ĵ",Jcirc:"Ĵ",jcy:"й",Jcy:"Й",jfr:"𝔧",Jfr:"𝔍",jmath:"ȷ",jopf:"𝕛",Jopf:"𝕁",jscr:"𝒿",Jscr:"𝒥",jsercy:"ј",Jsercy:"Ј",jukcy:"є",Jukcy:"Є",kappa:"κ",Kappa:"Κ",kappav:"ϰ",kcedil:"ķ",Kcedil:"Ķ",kcy:"к",Kcy:"К",kfr:"𝔨",Kfr:"𝔎",kgreen:"ĸ",khcy:"х",KHcy:"Х",kjcy:"ќ",KJcy:"Ќ",kopf:"𝕜",Kopf:"𝕂",kscr:"𝓀",Kscr:"𝒦",lAarr:"⇚",lacute:"ĺ",Lacute:"Ĺ",laemptyv:"⦴",lagran:"ℒ",lambda:"λ",Lambda:"Λ",lang:"⟨",Lang:"⟪",langd:"⦑",langle:"⟨",lap:"⪅",Laplacetrf:"ℒ",laquo:"«",larr:"←",lArr:"⇐",Larr:"↞",larrb:"⇤",larrbfs:"⤟",larrfs:"⤝",larrhk:"↩",larrlp:"↫",larrpl:"⤹",larrsim:"⥳",larrtl:"↢",lat:"⪫",latail:"⤙",lAtail:"⤛",late:"⪭",lates:"⪭︀",lbarr:"⤌",lBarr:"⤎",lbbrk:"❲",lbrace:"{",lbrack:"[",lbrke:"⦋",lbrksld:"⦏",lbrkslu:"⦍",lcaron:"ľ",Lcaron:"Ľ",lcedil:"ļ",Lcedil:"Ļ",lceil:"⌈",lcub:"{",lcy:"л",Lcy:"Л",ldca:"⤶",ldquo:"“",ldquor:"„",ldrdhar:"⥧",ldrushar:"⥋",ldsh:"↲",le:"≤",lE:"≦",LeftAngleBracket:"⟨",leftarrow:"←",Leftarrow:"⇐",LeftArrow:"←",LeftArrowBar:"⇤",LeftArrowRightArrow:"⇆",leftarrowtail:"↢",LeftCeiling:"⌈",LeftDoubleBracket:"⟦",LeftDownTeeVector:"⥡",LeftDownVector:"⇃",LeftDownVectorBar:"⥙",LeftFloor:"⌊",leftharpoondown:"↽",leftharpoonup:"↼",leftleftarrows:"⇇",leftrightarrow:"↔",Leftrightarrow:"⇔",LeftRightArrow:"↔",leftrightarrows:"⇆",leftrightharpoons:"⇋",leftrightsquigarrow:"↭",LeftRightVector:"⥎",LeftTee:"⊣",LeftTeeArrow:"↤",LeftTeeVector:"⥚",leftthreetimes:"⋋",LeftTriangle:"⊲",LeftTriangleBar:"⧏",LeftTriangleEqual:"⊴",LeftUpDownVector:"⥑",LeftUpTeeVector:"⥠",LeftUpVector:"↿",LeftUpVectorBar:"⥘",LeftVector:"↼",LeftVectorBar:"⥒",leg:"⋚",lEg:"⪋",leq:"≤",leqq:"≦",leqslant:"⩽",les:"⩽",lescc:"⪨",lesdot:"⩿",lesdoto:"⪁",lesdotor:"⪃",lesg:"⋚︀",lesges:"⪓",lessapprox:"⪅",lessdot:"⋖",lesseqgtr:"⋚",lesseqqgtr:"⪋",LessEqualGreater:"⋚",LessFullEqual:"≦",LessGreater:"≶",lessgtr:"≶",LessLess:"⪡",lesssim:"≲",LessSlantEqual:"⩽",LessTilde:"≲",lfisht:"⥼",lfloor:"⌊",lfr:"𝔩",Lfr:"𝔏",lg:"≶",lgE:"⪑",lHar:"⥢",lhard:"↽",lharu:"↼",lharul:"⥪",lhblk:"▄",ljcy:"љ",LJcy:"Љ",ll:"≪",Ll:"⋘",llarr:"⇇",llcorner:"⌞",Lleftarrow:"⇚",llhard:"⥫",lltri:"◺",lmidot:"ŀ",Lmidot:"Ŀ",lmoust:"⎰",lmoustache:"⎰",lnap:"⪉",lnapprox:"⪉",lne:"⪇",lnE:"≨",lneq:"⪇",lneqq:"≨",lnsim:"⋦",loang:"⟬",loarr:"⇽",lobrk:"⟦",longleftarrow:"⟵",Longleftarrow:"⟸",LongLeftArrow:"⟵",longleftrightarrow:"⟷",Longleftrightarrow:"⟺",LongLeftRightArrow:"⟷",longmapsto:"⟼",longrightarrow:"⟶",Longrightarrow:"⟹",LongRightArrow:"⟶",looparrowleft:"↫",looparrowright:"↬",lopar:"⦅",lopf:"𝕝",Lopf:"𝕃",loplus:"⨭",lotimes:"⨴",lowast:"∗",lowbar:"_",LowerLeftArrow:"↙",LowerRightArrow:"↘",loz:"◊",lozenge:"◊",lozf:"⧫",lpar:"(",lparlt:"⦓",lrarr:"⇆",lrcorner:"⌟",lrhar:"⇋",lrhard:"⥭",lrm:"‎",lrtri:"⊿",lsaquo:"‹",lscr:"𝓁",Lscr:"ℒ",lsh:"↰",Lsh:"↰",lsim:"≲",lsime:"⪍",lsimg:"⪏",lsqb:"[",lsquo:"‘",lsquor:"‚",lstrok:"ł",Lstrok:"Ł",lt:"<",Lt:"≪",LT:"<",ltcc:"⪦",ltcir:"⩹",ltdot:"⋖",lthree:"⋋",ltimes:"⋉",ltlarr:"⥶",ltquest:"⩻",ltri:"◃",ltrie:"⊴",ltrif:"◂",ltrPar:"⦖",lurdshar:"⥊",luruhar:"⥦",lvertneqq:"≨︀",lvnE:"≨︀",macr:"¯",male:"♂",malt:"✠",maltese:"✠",map:"↦",Map:"⤅",mapsto:"↦",mapstodown:"↧",mapstoleft:"↤",mapstoup:"↥",marker:"▮",mcomma:"⨩",mcy:"м",Mcy:"М",mdash:"—",mDDot:"∺",measuredangle:"∡",MediumSpace:" ",Mellintrf:"ℳ",mfr:"𝔪",Mfr:"𝔐",mho:"℧",micro:"µ",mid:"∣",midast:"*",midcir:"⫰",middot:"·",minus:"−",minusb:"⊟",minusd:"∸",minusdu:"⨪",MinusPlus:"∓",mlcp:"⫛",mldr:"…",mnplus:"∓",models:"⊧",mopf:"𝕞",Mopf:"𝕄",mp:"∓",mscr:"𝓂",Mscr:"ℳ",mstpos:"∾",mu:"μ",Mu:"Μ",multimap:"⊸",mumap:"⊸",nabla:"∇",nacute:"ń",Nacute:"Ń",nang:"∠⃒",nap:"≉",napE:"⩰̸",napid:"≋̸",napos:"ʼn",napprox:"≉",natur:"♮",natural:"♮",naturals:"ℕ",nbsp:" ",nbump:"≎̸",nbumpe:"≏̸",ncap:"⩃",ncaron:"ň",Ncaron:"Ň",ncedil:"ņ",Ncedil:"Ņ",ncong:"≇",ncongdot:"⩭̸",ncup:"⩂",ncy:"н",Ncy:"Н",ndash:"–",ne:"≠",nearhk:"⤤",nearr:"↗",neArr:"⇗",nearrow:"↗",nedot:"≐̸",NegativeMediumSpace:"​",NegativeThickSpace:"​",NegativeThinSpace:"​",NegativeVeryThinSpace:"​",nequiv:"≢",nesear:"⤨",nesim:"≂̸",NestedGreaterGreater:"≫",NestedLessLess:"≪",NewLine:"\n",nexist:"∄",nexists:"∄",nfr:"𝔫",Nfr:"𝔑",nge:"≱",ngE:"≧̸",ngeq:"≱",ngeqq:"≧̸",ngeqslant:"⩾̸",nges:"⩾̸",nGg:"⋙̸",ngsim:"≵",ngt:"≯",nGt:"≫⃒",ngtr:"≯",nGtv:"≫̸",nharr:"↮",nhArr:"⇎",nhpar:"⫲",ni:"∋",nis:"⋼",nisd:"⋺",niv:"∋",njcy:"њ",NJcy:"Њ",nlarr:"↚",nlArr:"⇍",nldr:"‥",nle:"≰",nlE:"≦̸",nleftarrow:"↚",nLeftarrow:"⇍",nleftrightarrow:"↮",nLeftrightarrow:"⇎",nleq:"≰",nleqq:"≦̸",nleqslant:"⩽̸",nles:"⩽̸",nless:"≮",nLl:"⋘̸",nlsim:"≴",nlt:"≮",nLt:"≪⃒",nltri:"⋪",nltrie:"⋬",nLtv:"≪̸",nmid:"∤",NoBreak:"⁠",NonBreakingSpace:" ",nopf:"𝕟",Nopf:"ℕ",not:"¬",Not:"⫬",NotCongruent:"≢",NotCupCap:"≭",NotDoubleVerticalBar:"∦",NotElement:"∉",NotEqual:"≠",NotEqualTilde:"≂̸",NotExists:"∄",NotGreater:"≯",NotGreaterEqual:"≱",NotGreaterFullEqual:"≧̸",NotGreaterGreater:"≫̸",NotGreaterLess:"≹",NotGreaterSlantEqual:"⩾̸",NotGreaterTilde:"≵",NotHumpDownHump:"≎̸",NotHumpEqual:"≏̸",notin:"∉",notindot:"⋵̸",notinE:"⋹̸",notinva:"∉",notinvb:"⋷",notinvc:"⋶",NotLeftTriangle:"⋪",NotLeftTriangleBar:"⧏̸",NotLeftTriangleEqual:"⋬",NotLess:"≮",NotLessEqual:"≰",NotLessGreater:"≸",NotLessLess:"≪̸",NotLessSlantEqual:"⩽̸",NotLessTilde:"≴",NotNestedGreaterGreater:"⪢̸",NotNestedLessLess:"⪡̸",notni:"∌",notniva:"∌",notnivb:"⋾",notnivc:"⋽",NotPrecedes:"⊀",NotPrecedesEqual:"⪯̸",NotPrecedesSlantEqual:"⋠",NotReverseElement:"∌",NotRightTriangle:"⋫",NotRightTriangleBar:"⧐̸",NotRightTriangleEqual:"⋭",NotSquareSubset:"⊏̸",NotSquareSubsetEqual:"⋢",NotSquareSuperset:"⊐̸",NotSquareSupersetEqual:"⋣",NotSubset:"⊂⃒",NotSubsetEqual:"⊈",NotSucceeds:"⊁",NotSucceedsEqual:"⪰̸",NotSucceedsSlantEqual:"⋡",NotSucceedsTilde:"≿̸",NotSuperset:"⊃⃒",NotSupersetEqual:"⊉",NotTilde:"≁",NotTildeEqual:"≄",NotTildeFullEqual:"≇",NotTildeTilde:"≉",NotVerticalBar:"∤",npar:"∦",nparallel:"∦",nparsl:"⫽⃥",npart:"∂̸",npolint:"⨔",npr:"⊀",nprcue:"⋠",npre:"⪯̸",nprec:"⊀",npreceq:"⪯̸",nrarr:"↛",nrArr:"⇏",nrarrc:"⤳̸",nrarrw:"↝̸",nrightarrow:"↛",nRightarrow:"⇏",nrtri:"⋫",nrtrie:"⋭",nsc:"⊁",nsccue:"⋡",nsce:"⪰̸",nscr:"𝓃",Nscr:"𝒩",nshortmid:"∤",nshortparallel:"∦",nsim:"≁",nsime:"≄",nsimeq:"≄",nsmid:"∤",nspar:"∦",nsqsube:"⋢",nsqsupe:"⋣",nsub:"⊄",nsube:"⊈",nsubE:"⫅̸",nsubset:"⊂⃒",nsubseteq:"⊈",nsubseteqq:"⫅̸",nsucc:"⊁",nsucceq:"⪰̸",nsup:"⊅",nsupe:"⊉",nsupE:"⫆̸",nsupset:"⊃⃒",nsupseteq:"⊉",nsupseteqq:"⫆̸",ntgl:"≹",ntilde:"ñ",Ntilde:"Ñ",ntlg:"≸",ntriangleleft:"⋪",ntrianglelefteq:"⋬",ntriangleright:"⋫",ntrianglerighteq:"⋭",nu:"ν",Nu:"Ν",num:"#",numero:"№",numsp:" ",nvap:"≍⃒",nvdash:"⊬",nvDash:"⊭",nVdash:"⊮",nVDash:"⊯",nvge:"≥⃒",nvgt:">⃒",nvHarr:"⤄",nvinfin:"⧞",nvlArr:"⤂",nvle:"≤⃒",nvlt:"<⃒",nvltrie:"⊴⃒",nvrArr:"⤃",nvrtrie:"⊵⃒",nvsim:"∼⃒",nwarhk:"⤣",nwarr:"↖",nwArr:"⇖",nwarrow:"↖",nwnear:"⤧",oacute:"ó",Oacute:"Ó",oast:"⊛",ocir:"⊚",ocirc:"ô",Ocirc:"Ô",ocy:"о",Ocy:"О",odash:"⊝",odblac:"ő",Odblac:"Ő",odiv:"⨸",odot:"⊙",odsold:"⦼",oelig:"œ",OElig:"Œ",ofcir:"⦿",ofr:"𝔬",Ofr:"𝔒",ogon:"˛",ograve:"ò",Ograve:"Ò",ogt:"⧁",ohbar:"⦵",ohm:"Ω",oint:"∮",olarr:"↺",olcir:"⦾",olcross:"⦻",oline:"‾",olt:"⧀",omacr:"ō",Omacr:"Ō",omega:"ω",Omega:"Ω",omicron:"ο",Omicron:"Ο",omid:"⦶",ominus:"⊖",oopf:"𝕠",Oopf:"𝕆",opar:"⦷",OpenCurlyDoubleQuote:"“",OpenCurlyQuote:"‘",operp:"⦹",oplus:"⊕",or:"∨",Or:"⩔",orarr:"↻",ord:"⩝",order:"ℴ",orderof:"ℴ",ordf:"ª",ordm:"º",origof:"⊶",oror:"⩖",orslope:"⩗",orv:"⩛",oS:"Ⓢ",oscr:"ℴ",Oscr:"𝒪",oslash:"ø",Oslash:"Ø",osol:"⊘",otilde:"õ",Otilde:"Õ",otimes:"⊗",Otimes:"⨷",otimesas:"⨶",ouml:"ö",Ouml:"Ö",ovbar:"⌽",OverBar:"‾",OverBrace:"⏞",OverBracket:"⎴",OverParenthesis:"⏜",par:"∥",para:"¶",parallel:"∥",parsim:"⫳",parsl:"⫽",part:"∂",PartialD:"∂",pcy:"п",Pcy:"П",percnt:"%",period:".",permil:"‰",perp:"⊥",pertenk:"‱",pfr:"𝔭",Pfr:"𝔓",phi:"φ",Phi:"Φ",phiv:"ϕ",phmmat:"ℳ",phone:"☎",pi:"π",Pi:"Π",pitchfork:"⋔",piv:"ϖ",planck:"ℏ",planckh:"ℎ",plankv:"ℏ",plus:"+",plusacir:"⨣",plusb:"⊞",pluscir:"⨢",plusdo:"∔",plusdu:"⨥",pluse:"⩲",PlusMinus:"±",plusmn:"±",plussim:"⨦",plustwo:"⨧",pm:"±",Poincareplane:"ℌ",pointint:"⨕",popf:"𝕡",Popf:"ℙ",pound:"£",pr:"≺",Pr:"⪻",prap:"⪷",prcue:"≼",pre:"⪯",prE:"⪳",prec:"≺",precapprox:"⪷",preccurlyeq:"≼",Precedes:"≺",PrecedesEqual:"⪯",PrecedesSlantEqual:"≼",PrecedesTilde:"≾",preceq:"⪯",precnapprox:"⪹",precneqq:"⪵",precnsim:"⋨",precsim:"≾",prime:"′",Prime:"″",primes:"ℙ",prnap:"⪹",prnE:"⪵",prnsim:"⋨",prod:"∏",Product:"∏",profalar:"⌮",profline:"⌒",profsurf:"⌓",prop:"∝",Proportion:"∷",Proportional:"∝",propto:"∝",prsim:"≾",prurel:"⊰",pscr:"𝓅",Pscr:"𝒫",psi:"ψ",Psi:"Ψ",puncsp:" ",qfr:"𝔮",Qfr:"𝔔",qint:"⨌",qopf:"𝕢",Qopf:"ℚ",qprime:"⁗",qscr:"𝓆",Qscr:"𝒬",quaternions:"ℍ",quatint:"⨖",quest:"?",questeq:"≟",quot:'"',QUOT:'"',rAarr:"⇛",race:"∽̱",racute:"ŕ",Racute:"Ŕ",radic:"√",raemptyv:"⦳",rang:"⟩",Rang:"⟫",rangd:"⦒",range:"⦥",rangle:"⟩",raquo:"»",rarr:"→",rArr:"⇒",Rarr:"↠",rarrap:"⥵",rarrb:"⇥",rarrbfs:"⤠",rarrc:"⤳",rarrfs:"⤞",rarrhk:"↪",rarrlp:"↬",rarrpl:"⥅",rarrsim:"⥴",rarrtl:"↣",Rarrtl:"⤖",rarrw:"↝",ratail:"⤚",rAtail:"⤜",ratio:"∶",rationals:"ℚ",rbarr:"⤍",rBarr:"⤏",RBarr:"⤐",rbbrk:"❳",rbrace:"}",rbrack:"]",rbrke:"⦌",rbrksld:"⦎",rbrkslu:"⦐",rcaron:"ř",Rcaron:"Ř",rcedil:"ŗ",Rcedil:"Ŗ",rceil:"⌉",rcub:"}",rcy:"р",Rcy:"Р",rdca:"⤷",rdldhar:"⥩",rdquo:"”",rdquor:"”",rdsh:"↳",Re:"ℜ",real:"ℜ",realine:"ℛ",realpart:"ℜ",reals:"ℝ",rect:"▭",reg:"®",REG:"®",ReverseElement:"∋",ReverseEquilibrium:"⇋",ReverseUpEquilibrium:"⥯",rfisht:"⥽",rfloor:"⌋",rfr:"𝔯",Rfr:"ℜ",rHar:"⥤",rhard:"⇁",rharu:"⇀",rharul:"⥬",rho:"ρ",Rho:"Ρ",rhov:"ϱ",RightAngleBracket:"⟩",rightarrow:"→",Rightarrow:"⇒",RightArrow:"→",RightArrowBar:"⇥",RightArrowLeftArrow:"⇄",rightarrowtail:"↣",RightCeiling:"⌉",RightDoubleBracket:"⟧",RightDownTeeVector:"⥝",RightDownVector:"⇂",RightDownVectorBar:"⥕",RightFloor:"⌋",rightharpoondown:"⇁",rightharpoonup:"⇀",rightleftarrows:"⇄",rightleftharpoons:"⇌",rightrightarrows:"⇉",rightsquigarrow:"↝",RightTee:"⊢",RightTeeArrow:"↦",RightTeeVector:"⥛",rightthreetimes:"⋌",RightTriangle:"⊳",RightTriangleBar:"⧐",RightTriangleEqual:"⊵",RightUpDownVector:"⥏",RightUpTeeVector:"⥜",RightUpVector:"↾",RightUpVectorBar:"⥔",RightVector:"⇀",RightVectorBar:"⥓",ring:"˚",risingdotseq:"≓",rlarr:"⇄",rlhar:"⇌",rlm:"‏",rmoust:"⎱",rmoustache:"⎱",rnmid:"⫮",roang:"⟭",roarr:"⇾",robrk:"⟧",ropar:"⦆",ropf:"𝕣",Ropf:"ℝ",roplus:"⨮",rotimes:"⨵",RoundImplies:"⥰",rpar:")",rpargt:"⦔",rppolint:"⨒",rrarr:"⇉",Rrightarrow:"⇛",rsaquo:"›",rscr:"𝓇",Rscr:"ℛ",rsh:"↱",Rsh:"↱",rsqb:"]",rsquo:"’",rsquor:"’",rthree:"⋌",rtimes:"⋊",rtri:"▹",rtrie:"⊵",rtrif:"▸",rtriltri:"⧎",RuleDelayed:"⧴",ruluhar:"⥨",rx:"℞",sacute:"ś",Sacute:"Ś",sbquo:"‚",sc:"≻",Sc:"⪼",scap:"⪸",scaron:"š",Scaron:"Š",sccue:"≽",sce:"⪰",scE:"⪴",scedil:"ş",Scedil:"Ş",scirc:"ŝ",Scirc:"Ŝ",scnap:"⪺",scnE:"⪶",scnsim:"⋩",scpolint:"⨓",scsim:"≿",scy:"с",Scy:"С",sdot:"⋅",sdotb:"⊡",sdote:"⩦",searhk:"⤥",searr:"↘",seArr:"⇘",searrow:"↘",sect:"§",semi:";",seswar:"⤩",setminus:"∖",setmn:"∖",sext:"✶",sfr:"𝔰",Sfr:"𝔖",sfrown:"⌢",sharp:"♯",shchcy:"щ",SHCHcy:"Щ",shcy:"ш",SHcy:"Ш",ShortDownArrow:"↓",ShortLeftArrow:"←",shortmid:"∣",shortparallel:"∥",ShortRightArrow:"→",ShortUpArrow:"↑",shy:"­",sigma:"σ",Sigma:"Σ",sigmaf:"ς",sigmav:"ς",sim:"∼",simdot:"⩪",sime:"≃",simeq:"≃",simg:"⪞",simgE:"⪠",siml:"⪝",simlE:"⪟",simne:"≆",simplus:"⨤",simrarr:"⥲",slarr:"←",SmallCircle:"∘",smallsetminus:"∖",smashp:"⨳",smeparsl:"⧤",smid:"∣",smile:"⌣",smt:"⪪",smte:"⪬",smtes:"⪬︀",softcy:"ь",SOFTcy:"Ь",sol:"/",solb:"⧄",solbar:"⌿",sopf:"𝕤",Sopf:"𝕊",spades:"♠",spadesuit:"♠",spar:"∥",sqcap:"⊓",sqcaps:"⊓︀",sqcup:"⊔",sqcups:"⊔︀",Sqrt:"√",sqsub:"⊏",sqsube:"⊑",sqsubset:"⊏",sqsubseteq:"⊑",sqsup:"⊐",sqsupe:"⊒",sqsupset:"⊐",sqsupseteq:"⊒",squ:"□",square:"□",Square:"□",SquareIntersection:"⊓",SquareSubset:"⊏",SquareSubsetEqual:"⊑",SquareSuperset:"⊐",SquareSupersetEqual:"⊒",SquareUnion:"⊔",squarf:"▪",squf:"▪",srarr:"→",sscr:"𝓈",Sscr:"𝒮",ssetmn:"∖",ssmile:"⌣",sstarf:"⋆",star:"☆",Star:"⋆",starf:"★",straightepsilon:"ϵ",straightphi:"ϕ",strns:"¯",sub:"⊂",Sub:"⋐",subdot:"⪽",sube:"⊆",subE:"⫅",subedot:"⫃",submult:"⫁",subne:"⊊",subnE:"⫋",subplus:"⪿",subrarr:"⥹",subset:"⊂",Subset:"⋐",subseteq:"⊆",subseteqq:"⫅",SubsetEqual:"⊆",subsetneq:"⊊",subsetneqq:"⫋",subsim:"⫇",subsub:"⫕",subsup:"⫓",succ:"≻",succapprox:"⪸",succcurlyeq:"≽",Succeeds:"≻",SucceedsEqual:"⪰",SucceedsSlantEqual:"≽",SucceedsTilde:"≿",succeq:"⪰",succnapprox:"⪺",succneqq:"⪶",succnsim:"⋩",succsim:"≿",SuchThat:"∋",sum:"∑",Sum:"∑",sung:"♪",sup:"⊃",Sup:"⋑",sup1:"¹",sup2:"²",sup3:"³",supdot:"⪾",supdsub:"⫘",supe:"⊇",supE:"⫆",supedot:"⫄",Superset:"⊃",SupersetEqual:"⊇",suphsol:"⟉",suphsub:"⫗",suplarr:"⥻",supmult:"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db=ps.exports,ae={},Tp={Aacute:"Á",aacute:"á",Abreve:"Ă",abreve:"ă",ac:"∾",acd:"∿",acE:"∾̳",Acirc:"Â",acirc:"â",acute:"´",Acy:"А",acy:"а",AElig:"Æ",aelig:"æ",af:"⁡",Afr:"𝔄",afr:"𝔞",Agrave:"À",agrave:"à",alefsym:"ℵ",aleph:"ℵ",Alpha:"Α",alpha:"α",Amacr:"Ā",amacr:"ā",amalg:"⨿",amp:"&",AMP:"&",andand:"⩕",And:"⩓",and:"∧",andd:"⩜",andslope:"⩘",andv:"⩚",ang:"∠",ange:"⦤",angle:"∠",angmsdaa:"⦨",angmsdab:"⦩",angmsdac:"⦪",angmsdad:"⦫",angmsdae:"⦬",angmsdaf:"⦭",angmsdag:"⦮",angmsdah:"⦯",angmsd:"∡",angrt:"∟",angrtvb:"⊾",angrtvbd:"⦝",angsph:"∢",angst:"Å",angzarr:"⍼",Aogon:"Ą",aogon:"ą",Aopf:"𝔸",aopf:"𝕒",apacir:"⩯",ap:"≈",apE:"⩰",ape:"≊",apid:"≋",apos:"'",ApplyFunction:"⁡",approx:"≈",approxeq:"≊",Aring:"Å",aring:"å",Ascr:"𝒜",ascr:"𝒶",Assign:"≔",ast:"*",asymp:"≈",asympeq:"≍",Atilde:"Ã",atilde:"ã",Auml:"Ä",auml:"ä",awconint:"∳",awint:"⨑",backcong:"≌",backepsilon:"϶",backprime:"‵",backsim:"∽",backsimeq:"⋍",Backslash:"∖",Barv:"⫧",barvee:"⊽",barwed:"⌅",Barwed:"⌆",barwedge:"⌅",bbrk:"⎵",bbrktbrk:"⎶",bcong:"≌",Bcy:"Б",bcy:"б",bdquo:"„",becaus:"∵",because:"∵",Because:"∵",bemptyv:"⦰",bepsi:"϶",bernou:"ℬ",Bernoullis:"ℬ",Beta:"Β",beta:"β",beth:"ℶ",between:"≬",Bfr:"𝔅",bfr:"𝔟",bigcap:"⋂",bigcirc:"◯",bigcup:"⋃",bigodot:"⨀",bigoplus:"⨁",bigotimes:"⨂",bigsqcup:"⨆",bigstar:"★",bigtriangledown:"▽",bigtriangleup:"△",biguplus:"⨄",bigvee:"⋁",bigwedge:"⋀",bkarow:"⤍",blacklozenge:"⧫",blacksquare:"▪",blacktriangle:"▴",blacktriangledown:"▾",blacktriangleleft:"◂",blacktriangleright:"▸",blank:"␣",blk12:"▒",blk14:"░",blk34:"▓",block:"█",bne:"=⃥",bnequiv:"≡⃥",bNot:"⫭",bnot:"⌐",Bopf:"𝔹",bopf:"𝕓",bot:"⊥",bottom:"⊥",bowtie:"⋈",boxbox:"⧉",boxdl:"┐",boxdL:"╕",boxDl:"╖",boxDL:"╗",boxdr:"┌",boxdR:"╒",boxDr:"╓",boxDR:"╔",boxh:"─",boxH:"═",boxhd:"┬",boxHd:"╤",boxhD:"╥",boxHD:"╦",boxhu:"┴",boxHu:"╧",boxhU:"╨",boxHU:"╩",boxminus:"⊟",boxplus:"⊞",boxtimes:"⊠",boxul:"┘",boxuL:"╛",boxUl:"╜",boxUL:"╝",boxur:"└",boxuR:"╘",boxUr:"╙",boxUR:"╚",boxv:"│",boxV:"║",boxvh:"┼",boxvH:"╪",boxVh:"╫",boxVH:"╬",boxvl:"┤",boxvL:"╡",boxVl:"╢",boxVL:"╣",boxvr:"├",boxvR:"╞",boxVr:"╟",boxVR:"╠",bprime:"‵",breve:"˘",Breve:"˘",brvbar:"¦",bscr:"𝒷",Bscr:"ℬ",bsemi:"⁏",bsim:"∽",bsime:"⋍",bsolb:"⧅",bsol:"\\",bsolhsub:"⟈",bull:"•",bullet:"•",bump:"≎",bumpE:"⪮",bumpe:"≏",Bumpeq:"≎",bumpeq:"≏",Cacute:"Ć",cacute:"ć",capand:"⩄",capbrcup:"⩉",capcap:"⩋",cap:"∩",Cap:"⋒",capcup:"⩇",capdot:"⩀",CapitalDifferentialD:"ⅅ",caps:"∩︀",caret:"⁁",caron:"ˇ",Cayleys:"ℭ",ccaps:"⩍",Ccaron:"Č",ccaron:"č",Ccedil:"Ç",ccedil:"ç",Ccirc:"Ĉ",ccirc:"ĉ",Cconint:"∰",ccups:"⩌",ccupssm:"⩐",Cdot:"Ċ",cdot:"ċ",cedil:"¸",Cedilla:"¸",cemptyv:"⦲",cent:"¢",centerdot:"·",CenterDot:"·",cfr:"𝔠",Cfr:"ℭ",CHcy:"Ч",chcy:"ч",check:"✓",checkmark:"✓",Chi:"Χ",chi:"χ",circ:"ˆ",circeq:"≗",circlearrowleft:"↺",circlearrowright:"↻",circledast:"⊛",circledcirc:"⊚",circleddash:"⊝",CircleDot:"⊙",circledR:"®",circledS:"Ⓢ",CircleMinus:"⊖",CirclePlus:"⊕",CircleTimes:"⊗",cir:"○",cirE:"⧃",cire:"≗",cirfnint:"⨐",cirmid:"⫯",cirscir:"⧂",ClockwiseContourIntegral:"∲",CloseCurlyDoubleQuote:"”",CloseCurlyQuote:"’",clubs:"♣",clubsuit:"♣",colon:":",Colon:"∷",Colone:"⩴",colone:"≔",coloneq:"≔",comma:",",commat:"@",comp:"∁",compfn:"∘",complement:"∁",complexes:"ℂ",cong:"≅",congdot:"⩭",Congruent:"≡",conint:"∮",Conint:"∯",ContourIntegral:"∮",copf:"𝕔",Copf:"ℂ",coprod:"∐",Coproduct:"∐",copy:"©",COPY:"©",copysr:"℗",CounterClockwiseContourIntegral:"∳",crarr:"↵",cross:"✗",Cross:"⨯",Cscr:"𝒞",cscr:"𝒸",csub:"⫏",csube:"⫑",csup:"⫐",csupe:"⫒",ctdot:"⋯",cudarrl:"⤸",cudarrr:"⤵",cuepr:"⋞",cuesc:"⋟",cularr:"↶",cularrp:"⤽",cupbrcap:"⩈",cupcap:"⩆",CupCap:"≍",cup:"∪",Cup:"⋓",cupcup:"⩊",cupdot:"⊍",cupor:"⩅",cups:"∪︀",curarr:"↷",curarrm:"⤼",curlyeqprec:"⋞",curlyeqsucc:"⋟",curlyvee:"⋎",curlywedge:"⋏",curren:"¤",curvearrowleft:"↶",curvearrowright:"↷",cuvee:"⋎",cuwed:"⋏",cwconint:"∲",cwint:"∱",cylcty:"⌭",dagger:"†",Dagger:"‡",daleth:"ℸ",darr:"↓",Darr:"↡",dArr:"⇓",dash:"‐",Dashv:"⫤",dashv:"⊣",dbkarow:"⤏",dblac:"˝",Dcaron:"Ď",dcaron:"ď",Dcy:"Д",dcy:"д",ddagger:"‡",ddarr:"⇊",DD:"ⅅ",dd:"ⅆ",DDotrahd:"⤑",ddotseq:"⩷",deg:"°",Del:"∇",Delta:"Δ",delta:"δ",demptyv:"⦱",dfisht:"⥿",Dfr:"𝔇",dfr:"𝔡",dHar:"⥥",dharl:"⇃",dharr:"⇂",DiacriticalAcute:"´",DiacriticalDot:"˙",DiacriticalDoubleAcute:"˝",DiacriticalGrave:"`",DiacriticalTilde:"˜",diam:"⋄",diamond:"⋄",Diamond:"⋄",diamondsuit:"♦",diams:"♦",die:"¨",DifferentialD:"ⅆ",digamma:"ϝ",disin:"⋲",div:"÷",divide:"÷",divideontimes:"⋇",divonx:"⋇",DJcy:"Ђ",djcy:"ђ",dlcorn:"⌞",dlcrop:"⌍",dollar:"$",Dopf:"𝔻",dopf:"𝕕",Dot:"¨",dot:"˙",DotDot:"⃜",doteq:"≐",doteqdot:"≑",DotEqual:"≐",dotminus:"∸",dotplus:"∔",dotsquare:"⊡",doublebarwedge:"⌆",DoubleContourIntegral:"∯",DoubleDot:"¨",DoubleDownArrow:"⇓",DoubleLeftArrow:"⇐",DoubleLeftRightArrow:"⇔",DoubleLeftTee:"⫤",DoubleLongLeftArrow:"⟸",DoubleLongLeftRightArrow:"⟺",DoubleLongRightArrow:"⟹",DoubleRightArrow:"⇒",DoubleRightTee:"⊨",DoubleUpArrow:"⇑",DoubleUpDownArrow:"⇕",DoubleVerticalBar:"∥",DownArrowBar:"⤓",downarrow:"↓",DownArrow:"↓",Downarrow:"⇓",DownArrowUpArrow:"⇵",DownBreve:"̑",downdownarrows:"⇊",downharpoonleft:"⇃",downharpoonright:"⇂",DownLeftRightVector:"⥐",DownLeftTeeVector:"⥞",DownLeftVectorBar:"⥖",DownLeftVector:"↽",DownRightTeeVector:"⥟",DownRightVectorBar:"⥗",DownRightVector:"⇁",DownTeeArrow:"↧",DownTee:"⊤",drbkarow:"⤐",drcorn:"⌟",drcrop:"⌌",Dscr:"𝒟",dscr:"𝒹",DScy:"Ѕ",dscy:"ѕ",dsol:"⧶",Dstrok:"Đ",dstrok:"đ",dtdot:"⋱",dtri:"▿",dtrif:"▾",duarr:"⇵",duhar:"⥯",dwangle:"⦦",DZcy:"Џ",dzcy:"џ",dzigrarr:"⟿",Eacute:"É",eacute:"é",easter:"⩮",Ecaron:"Ě",ecaron:"ě",Ecirc:"Ê",ecirc:"ê",ecir:"≖",ecolon:"≕",Ecy:"Э",ecy:"э",eDDot:"⩷",Edot:"Ė",edot:"ė",eDot:"≑",ee:"ⅇ",efDot:"≒",Efr:"𝔈",efr:"𝔢",eg:"⪚",Egrave:"È",egrave:"è",egs:"⪖",egsdot:"⪘",el:"⪙",Element:"∈",elinters:"⏧",ell:"ℓ",els:"⪕",elsdot:"⪗",Emacr:"Ē",emacr:"ē",empty:"∅",emptyset:"∅",EmptySmallSquare:"◻",emptyv:"∅",EmptyVerySmallSquare:"▫",emsp13:" ",emsp14:" ",emsp:" ",ENG:"Ŋ",eng:"ŋ",ensp:" ",Eogon:"Ę",eogon:"ę",Eopf:"𝔼",eopf:"𝕖",epar:"⋕",eparsl:"⧣",eplus:"⩱",epsi:"ε",Epsilon:"Ε",epsilon:"ε",epsiv:"ϵ",eqcirc:"≖",eqcolon:"≕",eqsim:"≂",eqslantgtr:"⪖",eqslantless:"⪕",Equal:"⩵",equals:"=",EqualTilde:"≂",equest:"≟",Equilibrium:"⇌",equiv:"≡",equivDD:"⩸",eqvparsl:"⧥",erarr:"⥱",erDot:"≓",escr:"ℯ",Escr:"ℰ",esdot:"≐",Esim:"⩳",esim:"≂",Eta:"Η",eta:"η",ETH:"Ð",eth:"ð",Euml:"Ë",euml:"ë",euro:"€",excl:"!",exist:"∃",Exists:"∃",expectation:"ℰ",exponentiale:"ⅇ",ExponentialE:"ⅇ",fallingdotseq:"≒",Fcy:"Ф",fcy:"ф",female:"♀",ffilig:"ffi",fflig:"ff",ffllig:"ffl",Ffr:"𝔉",ffr:"𝔣",filig:"fi",FilledSmallSquare:"◼",FilledVerySmallSquare:"▪",fjlig:"fj",flat:"♭",fllig:"fl",fltns:"▱",fnof:"ƒ",Fopf:"𝔽",fopf:"𝕗",forall:"∀",ForAll:"∀",fork:"⋔",forkv:"⫙",Fouriertrf:"ℱ",fpartint:"⨍",frac12:"½",frac13:"⅓",frac14:"¼",frac15:"⅕",frac16:"⅙",frac18:"⅛",frac23:"⅔",frac25:"⅖",frac34:"¾",frac35:"⅗",frac38:"⅜",frac45:"⅘",frac56:"⅚",frac58:"⅝",frac78:"⅞",frasl:"⁄",frown:"⌢",fscr:"𝒻",Fscr:"ℱ",gacute:"ǵ",Gamma:"Γ",gamma:"γ",Gammad:"Ϝ",gammad:"ϝ",gap:"⪆",Gbreve:"Ğ",gbreve:"ğ",Gcedil:"Ģ",Gcirc:"Ĝ",gcirc:"ĝ",Gcy:"Г",gcy:"г",Gdot:"Ġ",gdot:"ġ",ge:"≥",gE:"≧",gEl:"⪌",gel:"⋛",geq:"≥",geqq:"≧",geqslant:"⩾",gescc:"⪩",ges:"⩾",gesdot:"⪀",gesdoto:"⪂",gesdotol:"⪄",gesl:"⋛︀",gesles:"⪔",Gfr:"𝔊",gfr:"𝔤",gg:"≫",Gg:"⋙",ggg:"⋙",gimel:"ℷ",GJcy:"Ѓ",gjcy:"ѓ",gla:"⪥",gl:"≷",glE:"⪒",glj:"⪤",gnap:"⪊",gnapprox:"⪊",gne:"⪈",gnE:"≩",gneq:"⪈",gneqq:"≩",gnsim:"⋧",Gopf:"𝔾",gopf:"𝕘",grave:"`",GreaterEqual:"≥",GreaterEqualLess:"⋛",GreaterFullEqual:"≧",GreaterGreater:"⪢",GreaterLess:"≷",GreaterSlantEqual:"⩾",GreaterTilde:"≳",Gscr:"𝒢",gscr:"ℊ",gsim:"≳",gsime:"⪎",gsiml:"⪐",gtcc:"⪧",gtcir:"⩺",gt:">",GT:">",Gt:"≫",gtdot:"⋗",gtlPar:"⦕",gtquest:"⩼",gtrapprox:"⪆",gtrarr:"⥸",gtrdot:"⋗",gtreqless:"⋛",gtreqqless:"⪌",gtrless:"≷",gtrsim:"≳",gvertneqq:"≩︀",gvnE:"≩︀",Hacek:"ˇ",hairsp:" ",half:"½",hamilt:"ℋ",HARDcy:"Ъ",hardcy:"ъ",harrcir:"⥈",harr:"↔",hArr:"⇔",harrw:"↭",Hat:"^",hbar:"ℏ",Hcirc:"Ĥ",hcirc:"ĥ",hearts:"♥",heartsuit:"♥",hellip:"…",hercon:"⊹",hfr:"𝔥",Hfr:"ℌ",HilbertSpace:"ℋ",hksearow:"⤥",hkswarow:"⤦",hoarr:"⇿",homtht:"∻",hookleftarrow:"↩",hookrightarrow:"↪",hopf:"𝕙",Hopf:"ℍ",horbar:"―",HorizontalLine:"─",hscr:"𝒽",Hscr:"ℋ",hslash:"ℏ",Hstrok:"Ħ",hstrok:"ħ",HumpDownHump:"≎",HumpEqual:"≏",hybull:"⁃",hyphen:"‐",Iacute:"Í",iacute:"í",ic:"⁣",Icirc:"Î",icirc:"î",Icy:"И",icy:"и",Idot:"İ",IEcy:"Е",iecy:"е",iexcl:"¡",iff:"⇔",ifr:"𝔦",Ifr:"ℑ",Igrave:"Ì",igrave:"ì",ii:"ⅈ",iiiint:"⨌",iiint:"∭",iinfin:"⧜",iiota:"℩",IJlig:"IJ",ijlig:"ij",Imacr:"Ī",imacr:"ī",image:"ℑ",ImaginaryI:"ⅈ",imagline:"ℐ",imagpart:"ℑ",imath:"ı",Im:"ℑ",imof:"⊷",imped:"Ƶ",Implies:"⇒",incare:"℅",in:"∈",infin:"∞",infintie:"⧝",inodot:"ı",intcal:"⊺",int:"∫",Int:"∬",integers:"ℤ",Integral:"∫",intercal:"⊺",Intersection:"⋂",intlarhk:"⨗",intprod:"⨼",InvisibleComma:"⁣",InvisibleTimes:"⁢",IOcy:"Ё",iocy:"ё",Iogon:"Į",iogon:"į",Iopf:"𝕀",iopf:"𝕚",Iota:"Ι",iota:"ι",iprod:"⨼",iquest:"¿",iscr:"𝒾",Iscr:"ℐ",isin:"∈",isindot:"⋵",isinE:"⋹",isins:"⋴",isinsv:"⋳",isinv:"∈",it:"⁢",Itilde:"Ĩ",itilde:"ĩ",Iukcy:"І",iukcy:"і",Iuml:"Ï",iuml:"ï",Jcirc:"Ĵ",jcirc:"ĵ",Jcy:"Й",jcy:"й",Jfr:"𝔍",jfr:"𝔧",jmath:"ȷ",Jopf:"𝕁",jopf:"𝕛",Jscr:"𝒥",jscr:"𝒿",Jsercy:"Ј",jsercy:"ј",Jukcy:"Є",jukcy:"є",Kappa:"Κ",kappa:"κ",kappav:"ϰ",Kcedil:"Ķ",kcedil:"ķ",Kcy:"К",kcy:"к",Kfr:"𝔎",kfr:"𝔨",kgreen:"ĸ",KHcy:"Х",khcy:"х",KJcy:"Ќ",kjcy:"ќ",Kopf:"𝕂",kopf:"𝕜",Kscr:"𝒦",kscr:"𝓀",lAarr:"⇚",Lacute:"Ĺ",lacute:"ĺ",laemptyv:"⦴",lagran:"ℒ",Lambda:"Λ",lambda:"λ",lang:"⟨",Lang:"⟪",langd:"⦑",langle:"⟨",lap:"⪅",Laplacetrf:"ℒ",laquo:"«",larrb:"⇤",larrbfs:"⤟",larr:"←",Larr:"↞",lArr:"⇐",larrfs:"⤝",larrhk:"↩",larrlp:"↫",larrpl:"⤹",larrsim:"⥳",larrtl:"↢",latail:"⤙",lAtail:"⤛",lat:"⪫",late:"⪭",lates:"⪭︀",lbarr:"⤌",lBarr:"⤎",lbbrk:"❲",lbrace:"{",lbrack:"[",lbrke:"⦋",lbrksld:"⦏",lbrkslu:"⦍",Lcaron:"Ľ",lcaron:"ľ",Lcedil:"Ļ",lcedil:"ļ",lceil:"⌈",lcub:"{",Lcy:"Л",lcy:"л",ldca:"⤶",ldquo:"“",ldquor:"„",ldrdhar:"⥧",ldrushar:"⥋",ldsh:"↲",le:"≤",lE:"≦",LeftAngleBracket:"⟨",LeftArrowBar:"⇤",leftarrow:"←",LeftArrow:"←",Leftarrow:"⇐",LeftArrowRightArrow:"⇆",leftarrowtail:"↢",LeftCeiling:"⌈",LeftDoubleBracket:"⟦",LeftDownTeeVector:"⥡",LeftDownVectorBar:"⥙",LeftDownVector:"⇃",LeftFloor:"⌊",leftharpoondown:"↽",leftharpoonup:"↼",leftleftarrows:"⇇",leftrightarrow:"↔",LeftRightArrow:"↔",Leftrightarrow:"⇔",leftrightarrows:"⇆",leftrightharpoons:"⇋",leftrightsquigarrow:"↭",LeftRightVector:"⥎",LeftTeeArrow:"↤",LeftTee:"⊣",LeftTeeVector:"⥚",leftthreetimes:"⋋",LeftTriangleBar:"⧏",LeftTriangle:"⊲",LeftTriangleEqual:"⊴",LeftUpDownVector:"⥑",LeftUpTeeVector:"⥠",LeftUpVectorBar:"⥘",LeftUpVector:"↿",LeftVectorBar:"⥒",LeftVector:"↼",lEg:"⪋",leg:"⋚",leq:"≤",leqq:"≦",leqslant:"⩽",lescc:"⪨",les:"⩽",lesdot:"⩿",lesdoto:"⪁",lesdotor:"⪃",lesg:"⋚︀",lesges:"⪓",lessapprox:"⪅",lessdot:"⋖",lesseqgtr:"⋚",lesseqqgtr:"⪋",LessEqualGreater:"⋚",LessFullEqual:"≦",LessGreater:"≶",lessgtr:"≶",LessLess:"⪡",lesssim:"≲",LessSlantEqual:"⩽",LessTilde:"≲",lfisht:"⥼",lfloor:"⌊",Lfr:"𝔏",lfr:"𝔩",lg:"≶",lgE:"⪑",lHar:"⥢",lhard:"↽",lharu:"↼",lharul:"⥪",lhblk:"▄",LJcy:"Љ",ljcy:"љ",llarr:"⇇",ll:"≪",Ll:"⋘",llcorner:"⌞",Lleftarrow:"⇚",llhard:"⥫",lltri:"◺",Lmidot:"Ŀ",lmidot:"ŀ",lmoustache:"⎰",lmoust:"⎰",lnap:"⪉",lnapprox:"⪉",lne:"⪇",lnE:"≨",lneq:"⪇",lneqq:"≨",lnsim:"⋦",loang:"⟬",loarr:"⇽",lobrk:"⟦",longleftarrow:"⟵",LongLeftArrow:"⟵",Longleftarrow:"⟸",longleftrightarrow:"⟷",LongLeftRightArrow:"⟷",Longleftrightarrow:"⟺",longmapsto:"⟼",longrightarrow:"⟶",LongRightArrow:"⟶",Longrightarrow:"⟹",looparrowleft:"↫",looparrowright:"↬",lopar:"⦅",Lopf:"𝕃",lopf:"𝕝",loplus:"⨭",lotimes:"⨴",lowast:"∗",lowbar:"_",LowerLeftArrow:"↙",LowerRightArrow:"↘",loz:"◊",lozenge:"◊",lozf:"⧫",lpar:"(",lparlt:"⦓",lrarr:"⇆",lrcorner:"⌟",lrhar:"⇋",lrhard:"⥭",lrm:"‎",lrtri:"⊿",lsaquo:"‹",lscr:"𝓁",Lscr:"ℒ",lsh:"↰",Lsh:"↰",lsim:"≲",lsime:"⪍",lsimg:"⪏",lsqb:"[",lsquo:"‘",lsquor:"‚",Lstrok:"Ł",lstrok:"ł",ltcc:"⪦",ltcir:"⩹",lt:"<",LT:"<",Lt:"≪",ltdot:"⋖",lthree:"⋋",ltimes:"⋉",ltlarr:"⥶",ltquest:"⩻",ltri:"◃",ltrie:"⊴",ltrif:"◂",ltrPar:"⦖",lurdshar:"⥊",luruhar:"⥦",lvertneqq:"≨︀",lvnE:"≨︀",macr:"¯",male:"♂",malt:"✠",maltese:"✠",Map:"⤅",map:"↦",mapsto:"↦",mapstodown:"↧",mapstoleft:"↤",mapstoup:"↥",marker:"▮",mcomma:"⨩",Mcy:"М",mcy:"м",mdash:"—",mDDot:"∺",measuredangle:"∡",MediumSpace:" ",Mellintrf:"ℳ",Mfr:"𝔐",mfr:"𝔪",mho:"℧",micro:"µ",midast:"*",midcir:"⫰",mid:"∣",middot:"·",minusb:"⊟",minus:"−",minusd:"∸",minusdu:"⨪",MinusPlus:"∓",mlcp:"⫛",mldr:"…",mnplus:"∓",models:"⊧",Mopf:"𝕄",mopf:"𝕞",mp:"∓",mscr:"𝓂",Mscr:"ℳ",mstpos:"∾",Mu:"Μ",mu:"μ",multimap:"⊸",mumap:"⊸",nabla:"∇",Nacute:"Ń",nacute:"ń",nang:"∠⃒",nap:"≉",napE:"⩰̸",napid:"≋̸",napos:"ʼn",napprox:"≉",natural:"♮",naturals:"ℕ",natur:"♮",nbsp:" ",nbump:"≎̸",nbumpe:"≏̸",ncap:"⩃",Ncaron:"Ň",ncaron:"ň",Ncedil:"Ņ",ncedil:"ņ",ncong:"≇",ncongdot:"⩭̸",ncup:"⩂",Ncy:"Н",ncy:"н",ndash:"–",nearhk:"⤤",nearr:"↗",neArr:"⇗",nearrow:"↗",ne:"≠",nedot:"≐̸",NegativeMediumSpace:"​",NegativeThickSpace:"​",NegativeThinSpace:"​",NegativeVeryThinSpace:"​",nequiv:"≢",nesear:"⤨",nesim:"≂̸",NestedGreaterGreater:"≫",NestedLessLess:"≪",NewLine:"\n",nexist:"∄",nexists:"∄",Nfr:"𝔑",nfr:"𝔫",ngE:"≧̸",nge:"≱",ngeq:"≱",ngeqq:"≧̸",ngeqslant:"⩾̸",nges:"⩾̸",nGg:"⋙̸",ngsim:"≵",nGt:"≫⃒",ngt:"≯",ngtr:"≯",nGtv:"≫̸",nharr:"↮",nhArr:"⇎",nhpar:"⫲",ni:"∋",nis:"⋼",nisd:"⋺",niv:"∋",NJcy:"Њ",njcy:"њ",nlarr:"↚",nlArr:"⇍",nldr:"‥",nlE:"≦̸",nle:"≰",nleftarrow:"↚",nLeftarrow:"⇍",nleftrightarrow:"↮",nLeftrightarrow:"⇎",nleq:"≰",nleqq:"≦̸",nleqslant:"⩽̸",nles:"⩽̸",nless:"≮",nLl:"⋘̸",nlsim:"≴",nLt:"≪⃒",nlt:"≮",nltri:"⋪",nltrie:"⋬",nLtv:"≪̸",nmid:"∤",NoBreak:"⁠",NonBreakingSpace:" ",nopf:"𝕟",Nopf:"ℕ",Not:"⫬",not:"¬",NotCongruent:"≢",NotCupCap:"≭",NotDoubleVerticalBar:"∦",NotElement:"∉",NotEqual:"≠",NotEqualTilde:"≂̸",NotExists:"∄",NotGreater:"≯",NotGreaterEqual:"≱",NotGreaterFullEqual:"≧̸",NotGreaterGreater:"≫̸",NotGreaterLess:"≹",NotGreaterSlantEqual:"⩾̸",NotGreaterTilde:"≵",NotHumpDownHump:"≎̸",NotHumpEqual:"≏̸",notin:"∉",notindot:"⋵̸",notinE:"⋹̸",notinva:"∉",notinvb:"⋷",notinvc:"⋶",NotLeftTriangleBar:"⧏̸",NotLeftTriangle:"⋪",NotLeftTriangleEqual:"⋬",NotLess:"≮",NotLessEqual:"≰",NotLessGreater:"≸",NotLessLess:"≪̸",NotLessSlantEqual:"⩽̸",NotLessTilde:"≴",NotNestedGreaterGreater:"⪢̸",NotNestedLessLess:"⪡̸",notni:"∌",notniva:"∌",notnivb:"⋾",notnivc:"⋽",NotPrecedes:"⊀",NotPrecedesEqual:"⪯̸",NotPrecedesSlantEqual:"⋠",NotReverseElement:"∌",NotRightTriangleBar:"⧐̸",NotRightTriangle:"⋫",NotRightTriangleEqual:"⋭",NotSquareSubset:"⊏̸",NotSquareSubsetEqual:"⋢",NotSquareSuperset:"⊐̸",NotSquareSupersetEqual:"⋣",NotSubset:"⊂⃒",NotSubsetEqual:"⊈",NotSucceeds:"⊁",NotSucceedsEqual:"⪰̸",NotSucceedsSlantEqual:"⋡",NotSucceedsTilde:"≿̸",NotSuperset:"⊃⃒",NotSupersetEqual:"⊉",NotTilde:"≁",NotTildeEqual:"≄",NotTildeFullEqual:"≇",NotTildeTilde:"≉",NotVerticalBar:"∤",nparallel:"∦",npar:"∦",nparsl:"⫽⃥",npart:"∂̸",npolint:"⨔",npr:"⊀",nprcue:"⋠",nprec:"⊀",npreceq:"⪯̸",npre:"⪯̸",nrarrc:"⤳̸",nrarr:"↛",nrArr:"⇏",nrarrw:"↝̸",nrightarrow:"↛",nRightarrow:"⇏",nrtri:"⋫",nrtrie:"⋭",nsc:"⊁",nsccue:"⋡",nsce:"⪰̸",Nscr:"𝒩",nscr:"𝓃",nshortmid:"∤",nshortparallel:"∦",nsim:"≁",nsime:"≄",nsimeq:"≄",nsmid:"∤",nspar:"∦",nsqsube:"⋢",nsqsupe:"⋣",nsub:"⊄",nsubE:"⫅̸",nsube:"⊈",nsubset:"⊂⃒",nsubseteq:"⊈",nsubseteqq:"⫅̸",nsucc:"⊁",nsucceq:"⪰̸",nsup:"⊅",nsupE:"⫆̸",nsupe:"⊉",nsupset:"⊃⃒",nsupseteq:"⊉",nsupseteqq:"⫆̸",ntgl:"≹",Ntilde:"Ñ",ntilde:"ñ",ntlg:"≸",ntriangleleft:"⋪",ntrianglelefteq:"⋬",ntriangleright:"⋫",ntrianglerighteq:"⋭",Nu:"Ν",nu:"ν",num:"#",numero:"№",numsp:" ",nvap:"≍⃒",nvdash:"⊬",nvDash:"⊭",nVdash:"⊮",nVDash:"⊯",nvge:"≥⃒",nvgt:">⃒",nvHarr:"⤄",nvinfin:"⧞",nvlArr:"⤂",nvle:"≤⃒",nvlt:"<⃒",nvltrie:"⊴⃒",nvrArr:"⤃",nvrtrie:"⊵⃒",nvsim:"∼⃒",nwarhk:"⤣",nwarr:"↖",nwArr:"⇖",nwarrow:"↖",nwnear:"⤧",Oacute:"Ó",oacute:"ó",oast:"⊛",Ocirc:"Ô",ocirc:"ô",ocir:"⊚",Ocy:"О",ocy:"о",odash:"⊝",Odblac:"Ő",odblac:"ő",odiv:"⨸",odot:"⊙",odsold:"⦼",OElig:"Œ",oelig:"œ",ofcir:"⦿",Ofr:"𝔒",ofr:"𝔬",ogon:"˛",Ograve:"Ò",ograve:"ò",ogt:"⧁",ohbar:"⦵",ohm:"Ω",oint:"∮",olarr:"↺",olcir:"⦾",olcross:"⦻",oline:"‾",olt:"⧀",Omacr:"Ō",omacr:"ō",Omega:"Ω",omega:"ω",Omicron:"Ο",omicron:"ο",omid:"⦶",ominus:"⊖",Oopf:"𝕆",oopf:"𝕠",opar:"⦷",OpenCurlyDoubleQuote:"“",OpenCurlyQuote:"‘",operp:"⦹",oplus:"⊕",orarr:"↻",Or:"⩔",or:"∨",ord:"⩝",order:"ℴ",orderof:"ℴ",ordf:"ª",ordm:"º",origof:"⊶",oror:"⩖",orslope:"⩗",orv:"⩛",oS:"Ⓢ",Oscr:"𝒪",oscr:"ℴ",Oslash:"Ø",oslash:"ø",osol:"⊘",Otilde:"Õ",otilde:"õ",otimesas:"⨶",Otimes:"⨷",otimes:"⊗",Ouml:"Ö",ouml:"ö",ovbar:"⌽",OverBar:"‾",OverBrace:"⏞",OverBracket:"⎴",OverParenthesis:"⏜",para:"¶",parallel:"∥",par:"∥",parsim:"⫳",parsl:"⫽",part:"∂",PartialD:"∂",Pcy:"П",pcy:"п",percnt:"%",period:".",permil:"‰",perp:"⊥",pertenk:"‱",Pfr:"𝔓",pfr:"𝔭",Phi:"Φ",phi:"φ",phiv:"ϕ",phmmat:"ℳ",phone:"☎",Pi:"Π",pi:"π",pitchfork:"⋔",piv:"ϖ",planck:"ℏ",planckh:"ℎ",plankv:"ℏ",plusacir:"⨣",plusb:"⊞",pluscir:"⨢",plus:"+",plusdo:"∔",plusdu:"⨥",pluse:"⩲",PlusMinus:"±",plusmn:"±",plussim:"⨦",plustwo:"⨧",pm:"±",Poincareplane:"ℌ",pointint:"⨕",popf:"𝕡",Popf:"ℙ",pound:"£",prap:"⪷",Pr:"⪻",pr:"≺",prcue:"≼",precapprox:"⪷",prec:"≺",preccurlyeq:"≼",Precedes:"≺",PrecedesEqual:"⪯",PrecedesSlantEqual:"≼",PrecedesTilde:"≾",preceq:"⪯",precnapprox:"⪹",precneqq:"⪵",precnsim:"⋨",pre:"⪯",prE:"⪳",precsim:"≾",prime:"′",Prime:"″",primes:"ℙ",prnap:"⪹",prnE:"⪵",prnsim:"⋨",prod:"∏",Product:"∏",profalar:"⌮",profline:"⌒",profsurf:"⌓",prop:"∝",Proportional:"∝",Proportion:"∷",propto:"∝",prsim:"≾",prurel:"⊰",Pscr:"𝒫",pscr:"𝓅",Psi:"Ψ",psi:"ψ",puncsp:" ",Qfr:"𝔔",qfr:"𝔮",qint:"⨌",qopf:"𝕢",Qopf:"ℚ",qprime:"⁗",Qscr:"𝒬",qscr:"𝓆",quaternions:"ℍ",quatint:"⨖",quest:"?",questeq:"≟",quot:'"',QUOT:'"',rAarr:"⇛",race:"∽̱",Racute:"Ŕ",racute:"ŕ",radic:"√",raemptyv:"⦳",rang:"⟩",Rang:"⟫",rangd:"⦒",range:"⦥",rangle:"⟩",raquo:"»",rarrap:"⥵",rarrb:"⇥",rarrbfs:"⤠",rarrc:"⤳",rarr:"→",Rarr:"↠",rArr:"⇒",rarrfs:"⤞",rarrhk:"↪",rarrlp:"↬",rarrpl:"⥅",rarrsim:"⥴",Rarrtl:"⤖",rarrtl:"↣",rarrw:"↝",ratail:"⤚",rAtail:"⤜",ratio:"∶",rationals:"ℚ",rbarr:"⤍",rBarr:"⤏",RBarr:"⤐",rbbrk:"❳",rbrace:"}",rbrack:"]",rbrke:"⦌",rbrksld:"⦎",rbrkslu:"⦐",Rcaron:"Ř",rcaron:"ř",Rcedil:"Ŗ",rcedil:"ŗ",rceil:"⌉",rcub:"}",Rcy:"Р",rcy:"р",rdca:"⤷",rdldhar:"⥩",rdquo:"”",rdquor:"”",rdsh:"↳",real:"ℜ",realine:"ℛ",realpart:"ℜ",reals:"ℝ",Re:"ℜ",rect:"▭",reg:"®",REG:"®",ReverseElement:"∋",ReverseEquilibrium:"⇋",ReverseUpEquilibrium:"⥯",rfisht:"⥽",rfloor:"⌋",rfr:"𝔯",Rfr:"ℜ",rHar:"⥤",rhard:"⇁",rharu:"⇀",rharul:"⥬",Rho:"Ρ",rho:"ρ",rhov:"ϱ",RightAngleBracket:"⟩",RightArrowBar:"⇥",rightarrow:"→",RightArrow:"→",Rightarrow:"⇒",RightArrowLeftArrow:"⇄",rightarrowtail:"↣",RightCeiling:"⌉",RightDoubleBracket:"⟧",RightDownTeeVector:"⥝",RightDownVectorBar:"⥕",RightDownVector:"⇂",RightFloor:"⌋",rightharpoondown:"⇁",rightharpoonup:"⇀",rightleftarrows:"⇄",rightleftharpoons:"⇌",rightrightarrows:"⇉",rightsquigarrow:"↝",RightTeeArrow:"↦",RightTee:"⊢",RightTeeVector:"⥛",rightthreetimes:"⋌",RightTriangleBar:"⧐",RightTriangle:"⊳",RightTriangleEqual:"⊵",RightUpDownVector:"⥏",RightUpTeeVector:"⥜",RightUpVectorBar:"⥔",RightUpVector:"↾",RightVectorBar:"⥓",RightVector:"⇀",ring:"˚",risingdotseq:"≓",rlarr:"⇄",rlhar:"⇌",rlm:"‏",rmoustache:"⎱",rmoust:"⎱",rnmid:"⫮",roang:"⟭",roarr:"⇾",robrk:"⟧",ropar:"⦆",ropf:"𝕣",Ropf:"ℝ",roplus:"⨮",rotimes:"⨵",RoundImplies:"⥰",rpar:")",rpargt:"⦔",rppolint:"⨒",rrarr:"⇉",Rrightarrow:"⇛",rsaquo:"›",rscr:"𝓇",Rscr:"ℛ",rsh:"↱",Rsh:"↱",rsqb:"]",rsquo:"’",rsquor:"’",rthree:"⋌",rtimes:"⋊",rtri:"▹",rtrie:"⊵",rtrif:"▸",rtriltri:"⧎",RuleDelayed:"⧴",ruluhar:"⥨",rx:"℞",Sacute:"Ś",sacute:"ś",sbquo:"‚",scap:"⪸",Scaron:"Š",scaron:"š",Sc:"⪼",sc:"≻",sccue:"≽",sce:"⪰",scE:"⪴",Scedil:"Ş",scedil:"ş",Scirc:"Ŝ",scirc:"ŝ",scnap:"⪺",scnE:"⪶",scnsim:"⋩",scpolint:"⨓",scsim:"≿",Scy:"С",scy:"с",sdotb:"⊡",sdot:"⋅",sdote:"⩦",searhk:"⤥",searr:"↘",seArr:"⇘",searrow:"↘",sect:"§",semi:";",seswar:"⤩",setminus:"∖",setmn:"∖",sext:"✶",Sfr:"𝔖",sfr:"𝔰",sfrown:"⌢",sharp:"♯",SHCHcy:"Щ",shchcy:"щ",SHcy:"Ш",shcy:"ш",ShortDownArrow:"↓",ShortLeftArrow:"←",shortmid:"∣",shortparallel:"∥",ShortRightArrow:"→",ShortUpArrow:"↑",shy:"­",Sigma:"Σ",sigma:"σ",sigmaf:"ς",sigmav:"ς",sim:"∼",simdot:"⩪",sime:"≃",simeq:"≃",simg:"⪞",simgE:"⪠",siml:"⪝",simlE:"⪟",simne:"≆",simplus:"⨤",simrarr:"⥲",slarr:"←",SmallCircle:"∘",smallsetminus:"∖",smashp:"⨳",smeparsl:"⧤",smid:"∣",smile:"⌣",smt:"⪪",smte:"⪬",smtes:"⪬︀",SOFTcy:"Ь",softcy:"ь",solbar:"⌿",solb:"⧄",sol:"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a,s,i,l,u,c,p,d=!1,m=t.bMarks[n]+t.tShift[n],A=t.eMarks[n];if(t.sCount[n]-t.blkIndent>=4||m+3>A||126!==(a=t.src.charCodeAt(m))&&96!==a||(u=m,(s=(m=t.skipChars(m,a))-u)<3)||(p=t.src.slice(u,m),i=t.src.slice(m,A),96===a&&i.indexOf(String.fromCharCode(a))>=0))return!1;if(o)return!0;for(l=n;!(++l>=r||(m=u=t.bMarks[l]+t.tShift[l],A=t.eMarks[l],m=4||(m=t.skipChars(m,a),m-u=4||62!==t.src.charCodeAt(I))return!1;if(o)return!0;for(A=[],b=[],g=[],E=[],_=t.md.block.ruler.getRules("blockquote"),h=t.parentType,t.parentType="blockquote",d=n;d=(Q=t.eMarks[d])));d++)if(62!==t.src.charCodeAt(I++)||R){if(c)break;for(N=!1,i=0,u=_.length;i=Q,b.push(t.bsCount[d]),t.bsCount[d]=t.sCount[d]+1+(v?1:0),g.push(t.sCount[d]),t.sCount[d]=m-l,E.push(t.tShift[d]),t.tShift[d]=I-t.bMarks[d]}for(C=t.blkIndent,t.blkIndent=0,(S=t.push("blockquote_open","blockquote",1)).markup=">",S.map=p=[n,0],t.md.block.tokenize(t,n,d),(S=t.push("blockquote_close","blockquote",-1)).markup=">",t.lineMax=q,t.parentType=h,p[1]=t.line,i=0;i=4||42!==(a=t.src.charCodeAt(u++))&&45!==a&&95!==a)return!1;for(s=1;u=4||t.listIndent>=0&&t.sCount[P]-t.listIndent>=4&&t.sCount[P]=t.blkIndent&&(x=!0),(I=Xp(t,P))>=0){if(p=!0,ie=t.bMarks[P]+t.tShift[P],h=Number(t.src.slice(ie,I-1)),x&&1!==h)return!1}else{if(!((I=Kp(t,P))>=0))return!1;p=!1}if(x&&t.skipSpaces(I)>=t.eMarks[P])return!1;if(o)return!0;for(C=t.src.charCodeAt(I-1),b=t.tokens.length,p?(G=t.push("ordered_list_open","ol",1),1!==h&&(G.attrs=[["start",h]])):G=t.push("bullet_list_open","ul",1),G.map=A=[P,0],G.markup=String.fromCharCode(C),Q=!1,O=t.md.block.ruler.getRules("list"),N=t.parentType,t.parentType="list";P=g?1:E-c)>4&&(u=1),l=c+u,(G=t.push("list_item_open","li",1)).markup=String.fromCharCode(C),G.map=d=[P,0],p&&(G.info=t.src.slice(ie,I-1)),R=t.tight,S=t.tShift[P],_=t.sCount[P],v=t.listIndent,t.listIndent=t.blkIndent,t.blkIndent=l,t.tight=!0,t.tShift[P]=s-t.bMarks[P],t.sCount[P]=E,s>=g&&t.isEmpty(P+1)?t.line=Math.min(t.line+2,r):t.md.block.tokenize(t,P,r,!0),(!t.tight||Q)&&(T=!1),Q=t.line-P>1&&t.isEmpty(t.line-1),t.blkIndent=t.listIndent,t.listIndent=v,t.tShift[P]=S,t.sCount[P]=_,t.tight=R,(G=t.push("list_item_close","li",-1)).markup=String.fromCharCode(C),P=t.line,d[1]=P,P>=r||t.sCount[P]=4)break;for(Y=!1,i=0,m=O.length;i=4||91!==t.src.charCodeAt(_))return!1;for(;++_3||t.sCount[R]<0)){for(g=!1,c=0,p=E.length;c"u"&&(t.env.references={}),typeof t.env.references[d]>"u"&&(t.env.references[d]={title:v,href:u}),t.parentType=A,t.line=n+N+1),!0)}],["html_block",function(t,n,r,o){var a,s,i,l,u=t.bMarks[n]+t.tShift[n],c=t.eMarks[n];if(t.sCount[n]-t.blkIndent>=4||!t.md.options.html||60!==t.src.charCodeAt(u))return!1;for(l=t.src.slice(u,c),a=0;a=4||(35!==(a=t.src.charCodeAt(u))||u>=c))return!1;for(s=1,a=t.src.charCodeAt(++u);35===a&&u6||uu&&ef(t.src.charCodeAt(i-1))&&(c=i),t.line=n+1,(l=t.push("heading_open","h"+String(s),1)).markup="########".slice(0,s),l.map=[n,t.line],(l=t.push("inline","",0)).content=t.src.slice(u,c).trim(),l.map=[n,t.line],l.children=[],(l=t.push("heading_close","h"+String(s),-1)).markup="########".slice(0,s)),!0)},["paragraph","reference","blockquote"]],["lheading",function(t,n,r){var o,a,s,i,l,u,c,p,d,A,m=n+1,b=t.md.block.ruler.getRules("paragraph");if(t.sCount[n]-t.blkIndent>=4)return!1;for(A=t.parentType,t.parentType="paragraph";m3)){if(t.sCount[m]>=t.blkIndent&&((u=t.bMarks[m]+t.tShift[m])<(c=t.eMarks[m])&&((45===(d=t.src.charCodeAt(u))||61===d)&&(u=t.skipChars(u,d),(u=t.skipSpaces(u))>=c)))){p=61===d?1:2;break}if(!(t.sCount[m]<0)){for(a=!1,s=0,i=b.length;s3||t.sCount[c]<0)){for(a=!1,s=0,i=p.length;s=n||e.sCount[l]=c){e.line=n;break}for(a=e.line,o=0;o=e.line)throw new Error("block rule didn't increment state.line");break}if(!r)throw new Error("none of the block rules matched");e.tight=!u,e.isEmpty(e.line-1)&&(u=!0),(l=e.line)?@[]^_`{|}~-".split("").forEach((function(e){Eu[e.charCodeAt(0)]=1}));var ys={};function rf(e,t){var n,r,o,a,s,i=[],l=t.length;for(n=0;n=0;n--)(95===(r=t[n]).marker||42===r.marker)&&-1!==r.end&&(o=t[r.end],i=n>0&&t[n-1].end===r.end+1&&t[n-1].marker===r.marker&&t[n-1].token===r.token-1&&t[r.end+1].token===o.token+1,s=String.fromCharCode(r.marker),(a=e.tokens[r.token]).type=i?"strong_open":"em_open",a.tag=i?"strong":"em",a.nesting=1,a.markup=i?s+s:s,a.content="",(a=e.tokens[o.token]).type=i?"strong_close":"em_close",a.tag=i?"strong":"em",a.nesting=-1,a.markup=i?s+s:s,a.content="",i&&(e.tokens[t[n-1].token].content="",e.tokens[t[r.end+1].token].content="",n--))}Ts.tokenize=function(t,n){var r,o,s=t.pos,i=t.src.charCodeAt(s);if(n||95!==i&&42!==i)return!1;for(o=t.scanDelims(t.pos,42===i),r=0;r\x00-\x20]*)$/,tv=bs.HTML_TAG_RE;var af=Tp,sv=ae.has,iv=ae.isValidEntityCode,sf=ae.fromCodePoint,lv=/^&#((?:x[a-f0-9]{1,6}|[0-9]{1,7}));/i,uv=/^&([a-z][a-z0-9]{1,31});/i;function lf(e){var t,n,r,o,a,s,i,l,u={},c=e.length;if(c){var p=0,d=-2,m=[];for(t=0;ta;n-=m[n]+1)if((o=e[n]).marker===r.marker&&o.open&&o.end<0&&(i=!1,(o.close||r.open)&&(o.length+r.length)%3==0&&(o.length%3!=0||r.length%3!=0)&&(i=!0),!i)){l=n>0&&!e[n-1].open?m[n-1]+1:0,m[t]=t-n+l,m[n]=l,r.open=!1,o.end=t,o.close=!1,s=-1,d=-2;break}-1!==s&&(u[r.marker][(r.open?3:0)+(r.length||0)%3]=s)}}}var _u=pu,uf=ae.isWhiteSpace,cf=ae.isPunctChar,df=ae.isMdAsciiPunct;function Io(e,t,n,r){this.src=e,this.env=n,this.md=t,this.tokens=r,this.tokens_meta=Array(r.length),this.pos=0,this.posMax=this.src.length,this.level=0,this.pending="",this.pendingLevel=0,this.cache={},this.delimiters=[],this._prev_delimiters=[],this.backticks={},this.backticksScanned=!1,this.linkLevel=0}Io.prototype.pushPending=function(){var e=new _u("text","",0);return e.content=this.pending,e.level=this.pendingLevel,this.tokens.push(e),this.pending="",e},Io.prototype.push=function(e,t,n){this.pending&&this.pushPending();var r=new _u(e,t,n),o=null;return n<0&&(this.level--,this.delimiters=this._prev_delimiters.pop()),r.level=this.level,n>0&&(this.level++,this._prev_delimiters.push(this.delimiters),this.delimiters=[],o={delimiters:this.delimiters}),this.pendingLevel=this.level,this.tokens.push(r),this.tokens_meta.push(o),r},Io.prototype.scanDelims=function(e,t){var r,o,a,s,i,l,u,c,p,n=e,d=!0,m=!0,A=this.posMax,b=this.src.charCodeAt(e);for(r=e>0?this.src.charCodeAt(e-1):32;n0||(r=t.pos,o=t.posMax,r+3>o)||58!==t.src.charCodeAt(r)||47!==t.src.charCodeAt(r+1)||47!==t.src.charCodeAt(r+2)||(a=t.pending.match(H_),!a)||(s=a[1],i=t.md.linkify.matchAtStart(t.src.slice(r-s.length)),!i)||(l=i.url,l.length<=s.length)||(l=l.replace(/\*+$/,""),u=t.md.normalizeLink(l),!t.md.validateLink(u))||(n||(t.pending=t.pending.slice(0,-s.length),(c=t.push("link_open","a",1)).attrs=[["href",u]],c.markup="linkify",c.info="auto",(c=t.push("text","",0)).content=t.md.normalizeLinkText(l),(c=t.push("link_close","a",-1)).markup="linkify",c.info="auto"),t.pos+=l.length-s.length,0))}],["newline",function(t,n){var r,o,a,s=t.pos;if(10!==t.src.charCodeAt(s))return!1;if(r=t.pending.length-1,o=t.posMax,!n)if(r>=0&&32===t.pending.charCodeAt(r))if(r>=1&&32===t.pending.charCodeAt(r-1)){for(a=r-1;a>=1&&32===t.pending.charCodeAt(a-1);)a--;t.pending=t.pending.slice(0,a),t.push("hardbreak","br",0)}else t.pending=t.pending.slice(0,-1),t.push("softbreak","br",0);else t.push("softbreak","br",0);for(s++;s=u)return!1;if(10===(r=t.src.charCodeAt(l))){for(n||t.push("hardbreak","br",0),l++;l=55296&&r<=56319&&l+1=56320&&o<=57343&&(s+=t.src[l+1],l++)),a="\\"+s,n||(i=t.push("text_special","",0),r<256&&0!==Eu[r]?i.content=s:i.content=a,i.markup=a,i.info="escape"),t.pos=l+1,!0}],["backticks",function(t,n){var r,o,a,s,i,l,u,c,p=t.pos;if(96!==t.src.charCodeAt(p))return!1;for(r=p,p++,o=t.posMax;p=b)return!1;if(C=l,(u=t.md.helpers.parseLinkDestination(t.src,l,t.posMax)).ok){for(d=t.md.normalizeLink(u.str),t.md.validateLink(d)?l=u.pos:d="",C=l;l=b||41!==t.src.charCodeAt(l))&&(h=!0),l++}if(h){if(typeof t.env.references>"u")return!1;if(l=0?a=t.src.slice(C,l++):l=s+1):l=s+1,a||(a=t.src.slice(i,s)),!(c=t.env.references[W_(a)]))return t.pos=A,!1;d=c.href,m=c.title}return n||(t.pos=i,t.posMax=s,t.push("link_open","a",1).attrs=r=[["href",d]],m&&r.push(["title",m]),t.linkLevel++,t.md.inline.tokenize(t),t.linkLevel--,t.push("link_close","a",-1)),t.pos=l,t.posMax=b,!0}],["image",function(t,n){var r,o,a,s,i,l,u,c,p,d,m,A,b,C="",h=t.pos,g=t.posMax;if(33!==t.src.charCodeAt(t.pos)||91!==t.src.charCodeAt(t.pos+1)||(l=t.pos+2,(i=t.md.helpers.parseLinkLabel(t,t.pos+1,!1))<0))return!1;if((u=i+1)=g)return!1;for(b=u,(p=t.md.helpers.parseLinkDestination(t.src,u,t.posMax)).ok&&(C=t.md.normalizeLink(p.str),t.md.validateLink(C)?u=p.pos:C=""),b=u;u=g||41!==t.src.charCodeAt(u))return t.pos=h,!1;u++}else{if(typeof t.env.references>"u")return!1;if(u=0?s=t.src.slice(b,u++):u=i+1):u=i+1,s||(s=t.src.slice(l,i)),!(c=t.env.references[K_(s)]))return t.pos=h,!1;C=c.href,d=c.title}return n||(a=t.src.slice(l,i),t.md.inline.parse(a,t.md,t.env,A=[]),(m=t.push("image","img",0)).attrs=r=[["src",C],["alt",""]],m.children=A,m.content=a,d&&r.push(["title",d])),t.pos=u,t.posMax=g,!0}],["autolink",function(t,n){var r,o,a,s,i,l,u=t.pos;if(60!==t.src.charCodeAt(u))return!1;for(i=t.pos,l=t.posMax;;){if(++u>=l||60===(s=t.src.charCodeAt(u)))return!1;if(62===s)break}return r=t.src.slice(i+1,u),J_.test(r)?(o=t.md.normalizeLink(r),!!t.md.validateLink(o)&&(n||((a=t.push("link_open","a",1)).attrs=[["href",o]],a.markup="autolink",a.info="auto",(a=t.push("text","",0)).content=t.md.normalizeLinkText(r),(a=t.push("link_close","a",-1)).markup="autolink",a.info="auto"),t.pos+=r.length+2,!0)):!!Q_.test(r)&&(o=t.md.normalizeLink("mailto:"+r),!!t.md.validateLink(o)&&(n||((a=t.push("link_open","a",1)).attrs=[["href",o]],a.markup="autolink",a.info="auto",(a=t.push("text","",0)).content=t.md.normalizeLinkText(r),(a=t.push("link_close","a",-1)).markup="autolink",a.info="auto"),t.pos+=r.length+2,!0))}],["html_inline",function(t,n){var r,o,a,s,i=t.pos;return!(!t.md.options.html||(a=t.posMax,60!==t.src.charCodeAt(i)||i+2>=a)||(r=t.src.charCodeAt(i+1),33!==r&&63!==r&&47!==r&&!function(e){var t=32|e;return t>=97&&t<=122}(r))||(o=t.src.slice(i).match(tv),!o))&&(n||((s=t.push("html_inline","",0)).content=o[0],function(e){return/^\s]/i.test(e)}(s.content)&&t.linkLevel++,function(e){return/^<\/a\s*>/i.test(e)}(s.content)&&t.linkLevel--),t.pos+=o[0].length,!0)}],["entity",function(t,n){var o,a,s,i=t.pos,l=t.posMax;if(38!==t.src.charCodeAt(i)||i+1>=l)return!1;if(35===t.src.charCodeAt(i+1)){if(a=t.src.slice(i).match(lv))return n||(o="x"===a[1][0].toLowerCase()?parseInt(a[1].slice(1),16):parseInt(a[1],10),(s=t.push("text_special","",0)).content=iv(o)?sf(o):sf(65533),s.markup=a[0],s.info="entity"),t.pos+=a[0].length,!0}else if((a=t.src.slice(i).match(uv))&&sv(af,a[1]))return n||((s=t.push("text_special","",0)).content=af[a[1]],s.markup=a[0],s.info="entity"),t.pos+=a[0].length,!0;return!1}]],Du=[["balance_pairs",function(t){var n,r=t.tokens_meta,o=t.tokens_meta.length;for(lf(t.delimiters),n=0;n0&&o++,"text"===a[n].type&&n+1=e.pos)throw new Error("inline rule didn't increment 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e.walkDecls((f=>{if(this.disabledDecl(f,t))return;let w,d=f.parent,p=f.prop,m=f.value;if("grid-row-span"!==p)if("grid-column-span"!==p)if("display"!==p||"box"!==m){if("text-emphasis-position"===p)("under"===m||"over"===m)&&t.warn("You should use 2 values for text-emphasis-position For example, `under left` instead of just `under`.",{node:f});else if(/^(align|justify|place)-(items|content)$/.test(p)&&function(f){return f.parent.some((d=>"display"===d.prop&&/(inline-)?flex/.test(d.value)))}(f))("start"===m||"end"===m)&&t.warn(`${m} value has mixed support, consider using flex-${m} instead`,{node:f});else if("text-decoration-skip"===p&&"ink"===m)t.warn("Replace text-decoration-skip: ink to text-decoration-skip-ink: auto, because spec had been changed",{node:f});else{if(c&&this.gridStatus(f,t))if("subgrid"===f.value&&t.warn("IE does not support subgrid",{node:f}),/^(align|justify|place)-items$/.test(p)&&o(f)){let x=p.replace("-items","-self");t.warn(`IE does not support ${p} on grid 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JSON.parse(localUser) : null, + authToken: localAuthToken ? localAuthToken : null, + }); + + const [actions] = useState({ + updateUser: (user, authToken = "") => { + localStorage.setItem(AUTH_USER, JSON.stringify(user)); + localStorage.setItem(AUTH_TOKEN, authToken); + setStore({ user, authToken }); + }, + unsetUser: () => { + localStorage.removeItem(AUTH_USER); + localStorage.removeItem(AUTH_TOKEN); + localStorage.removeItem(AUTH_TIMESTAMP); + setStore({ user: null, authToken: null }); + }, + }); + + return ( + + {props.children} + + ); +} diff --git a/frontend/src/LogoContext.jsx b/frontend/src/LogoContext.jsx new file mode 100644 index 0000000..6818967 --- /dev/null +++ b/frontend/src/LogoContext.jsx @@ -0,0 +1,28 @@ +import { createContext, useEffect, useState } from "react"; +import AnythingLLM from "./media/logo/anything-llm.png"; +import System from "./models/system"; + +export const LogoContext = createContext(); + +export function LogoProvider({ children }) { + const [logo, setLogo] = useState(""); + + useEffect(() => { + async function fetchInstanceLogo() { + try { + const logoURL = await System.fetchLogo(); + logoURL ? setLogo(logoURL) : setLogo(AnythingLLM); + } catch (err) { + setLogo(AnythingLLM); + console.error("Failed to fetch logo:", err); + } + } + fetchInstanceLogo(); + }, []); + + return ( + + {children} + + ); +} diff --git a/frontend/src/PfpContext.jsx b/frontend/src/PfpContext.jsx new file mode 100644 index 0000000..3d60d55 --- /dev/null +++ b/frontend/src/PfpContext.jsx @@ -0,0 +1,30 @@ +import React, { createContext, useState, useEffect } from "react"; +import useUser from "./hooks/useUser"; +import System from "./models/system"; + +export const PfpContext = createContext(); + +export function PfpProvider({ children }) { + const [pfp, setPfp] = useState(null); + const { user } = useUser(); + + useEffect(() => { + async function fetchPfp() { + if (!user?.id) return; + try { + const pfpUrl = await System.fetchPfp(user.id); + setPfp(pfpUrl); + } catch (err) { + setPfp(null); + console.error("Failed to fetch pfp:", err); + } + } + fetchPfp(); + }, [user?.id]); + + return ( + + {children} + + ); +} diff --git a/frontend/src/components/ChangeWarning/index.jsx b/frontend/src/components/ChangeWarning/index.jsx new file mode 100644 index 0000000..42b211b --- /dev/null +++ b/frontend/src/components/ChangeWarning/index.jsx @@ -0,0 +1,47 @@ +import { Warning } from "@phosphor-icons/react"; + +export default function ChangeWarningModal({ + warningText = "", + onClose, + onConfirm, +}) { + return ( +

+
+
+
+ +

Warning

+
+
+
+

+ {warningText} +
+
+ Are you sure you want to proceed? +

+
+ +
+ + +
+
+
+ ); +} diff --git a/frontend/src/components/ChatBubble/index.jsx b/frontend/src/components/ChatBubble/index.jsx new file mode 100644 index 0000000..72002ab --- /dev/null +++ b/frontend/src/components/ChatBubble/index.jsx @@ -0,0 +1,31 @@ +import React from "react"; +import Jazzicon from "../UserIcon"; +import { userFromStorage } from "@/utils/request"; +import { AI_BACKGROUND_COLOR, USER_BACKGROUND_COLOR } from "@/utils/constants"; + +export default function ChatBubble({ message, type, popMsg }) { + const isUser = type === "user"; + const backgroundColor = isUser ? USER_BACKGROUND_COLOR : AI_BACKGROUND_COLOR; + + return ( +
+
+
+ + + + {message} + +
+
+
+ ); +} diff --git a/frontend/src/components/DataConnectorOption/index.jsx b/frontend/src/components/DataConnectorOption/index.jsx new file mode 100644 index 0000000..038624a --- /dev/null +++ b/frontend/src/components/DataConnectorOption/index.jsx @@ -0,0 +1,25 @@ +export default function DataConnectorOption({ slug }) { + if (!DATA_CONNECTORS.hasOwnProperty(slug)) return null; + const { path, image, name, description, link } = DATA_CONNECTORS[slug]; + + return ( + + + {link} + + + + ); +} diff --git a/frontend/src/components/DataConnectorOption/media/confluence.jpeg b/frontend/src/components/DataConnectorOption/media/confluence.jpeg new file mode 100644 index 0000000000000000000000000000000000000000..7559663a68ac1dfdc3f5a64f4de891d3d449272c GIT binary patch literal 5659 zcmc&&cT`i^w+LL6^<1^BKveb{mA+}qOXVG9axPyj#eI_^cQ%woJQ6_ zU7g#9)$8y4gC|5Tc^CzWxu{0l&HDnA_A&|k6V-2}_%&VETk z4#$>1PJha_NuCZ55nNK}v2(kyianRz^F0~;dQ-XgQ;meqqFdgA@0Dqmxby#@%VUS4 zX6f}6-n(BfX>L`5$Z}RSHGXIi9ewp`+44??+`>|pOw-bi{Y|OC-jj^G4F3)SQ9mqM z57-qKk~rHL0@Lc1fJrpgW)!4%$jhOhq0-&5a^oIN$Sk#VzDxx%TNiti#p4qKOK)1) z(Fa?MhS{ii`?*lftpJx)v*0)RQKI*ib);q{m*Sj> z1vXS&X;%w7n4*37*E+AJdx(s$Y;hJmZ^|%ZQWuj~Ta*pc#8>kr%+d9j-Oc$Hh-A}U z`4vpg2d%Jg_0M5OO8OtrL1VPB~bu9hnY9WF|MCSW3;9k5$YlEZgdrip_#2``e?F%`HM1kp>G> z8^Z$R)AdKuNo}>WYokY?z}8EVQ_! zboJXgZ?8W9Mz}}j>f#P~S+aEtflOL$@LV5k)`W=Ot$K`O;tJmy`wf=G*7%~z=-Xk} zzv@FCH7l9GlMRtH8g^(i6*S|O+3XR>*eKC_`fWFF?RXpogGw4ecbBFxv;j#K1DaESr;)6o*$=FBaLJgL5Yyf?u@d zQTU`aDPhuy-v(2-sJ8~6XA;CnqI>RQJAwK*6=9r_bOxIJIVw)*@v9Bz-q|&q%6>RU4CxlA zRyVS=xHR6FFJt6NO9(!{Z2h2_U;mPVL)7YhdxkNxh3)48uN?}*IP#hjULm^VE#IhA zN6S&uJKbtf6=&0Z{?^nK{v7A62oi7BGq0y9x>j3WX`4Ef-s&73*(KfO^b(4_+)yZA zl=A>oew3X*6IRva9H(8JXK(@ILZ7b)tttLu*73fQ_nctmofo{nJvhhvg17soL7{JR zK#aY-6V0qE?9sJbwdD@Ueu*y9)BT+lZHPR1-2$WEHC^pqw0&=#If03^<^FQ{83zr| zjadQnk{a#0`*(N^g>ddVV)7Yb~Nsne!LuVq4jR`*OF8wNm4peH==t<0PEp5sjY5WGC^Jd+ZkKt4sOMWFI#yss?| zb;QmnZ^ORr7&)FjU+9vN7e0c(CB-4mW%!vdBU$>oX=xoNDnvx^HCJNIen)bd9l3P$ zB1apOL{1bxGkGS>d5}N{;%>3qONA~+d`_a923A;|GeOY9PJ8$GYJ>u(gs9IU&c^NScKQTWnc9&kZU|4poV@w@sY_hTu& zUwtYb*Z71{^wdWxOh3|!+Q}88?In$C?|POTx5Fy^A|c^*i_>nN>}FA9l*V4mlJ$2| zeML$9&5oEBp~p>Dg#Tvd4tD8u1${W5-XU6Lr_})i+u{?fl`h&|$-QypqU|AD9!@-O zj|WF6S!oqt>aY%V(WQ*nRGb>Fgcqi|OdSumfklKOaZ{D+2(TiC44q*i@1&k;tdD6s(e`V=^UneM!&)>Y~L)c&8oM;-$LJRasFL{m+weT zsjK+r`sD0DI@sniKfi@qZ$qhkbtv}wPRxVxurwUBbt9CNeKb>Bp-RF=VC!z${~`IoAWY&%0Lazzm zXq%ZP?Yc!JA*$Z$#PS;dZ!{%s=D6JOn5<-Q4hz?FD{N#t@ zK9DXeWUeb+3*N~;)RV9ixHnA)c@>XALAR{jp^>;r_mLdcg2Yl^MLhCH$=e6%wB*c0vhfVLWg z0;91g*R1~Nw{nCiaOhsZEz-@Qg@W6}xSoL8ZNG%k1nYx?Q@p+o^%jIY;-QAA-F8H# z-`5Sr$D8Ay!L51vy_VY=h7{SRKlb7ey<_!_8DOoJSPrAjZuR{ozLT9)|KoxEwi>&m z>-_)ZQ@<2F$ba{VZ*2rPneoVVr?1_ADDn1fGLX=URry#GmLEnuy$^7Uj-B5I$7&Is z+1nn21u?Pj-Roa&xR;#)=Rjc%9aD?AQ<+8<5ldsnb)q^UI)NL7t>Mutkx!&70n%!+ zca>$=8z;|qp@|OR+4}$!+l0R1HZ-u46O(7Lp3GP#k)(G^!;(@d?QL+rMECJtez7rK zH0Y(XE9SZrxj0L6{&Z3^HRuMtu#`+$0(;_-eMhQ@igku#4-g7t_`c7jIcM|sS{wYG zp4!Lg200CV7$Tb!3b&h+Jx=t2f6dDttf#6)(v};mq^+;venkvfa+AHc z;>%fj{7L#~ls2E~kjm-&+$RZ)87d;6h|-V6vcnY049-qT4$oa}7+XA9jd~!8bW2)j zo3qCy;;-k6RcUoYL!d$DedOd7gWkVy2`(4@m!H5}0|~2myBAw|>-&Itvg^Hfoezl$eZJVeg|IgS zs3Wrjjk?O}e-;S30{}4Y9+Oo*9B}CR;Q-lVhdm&N(W}^Pkq79ezFZ>2*e=W&b;!x#VXwXG&=LWlOu`A0Tp^Wti`P zn(Y1j*T27(eTLUQP<`MvzWM;i3NKDYw#e`Uu|`N+%#hV`%n7$okwpIalS^Pn8DsiF z3adXbEHCt?(SdF>4*z# zLv2Xf=QIEM8}l)xO3O`KiljdO#!UL@@;&`jjLcygDVr1?xU#gmwG3O7zAC3z zfyf%^n5!KOF|}e; 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+import YouTube from "./youtube.svg"; +import Link from "./link.svg"; +import Confluence from "./confluence.jpeg"; + +const ConnectorImages = { + github: Github, + youtube: YouTube, + websiteDepth: Link, + confluence: Confluence, +}; + +export default ConnectorImages; diff --git a/frontend/src/components/DataConnectorOption/media/link.svg b/frontend/src/components/DataConnectorOption/media/link.svg new file mode 100644 index 0000000..c957e54 --- /dev/null +++ b/frontend/src/components/DataConnectorOption/media/link.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/frontend/src/components/DataConnectorOption/media/youtube.svg b/frontend/src/components/DataConnectorOption/media/youtube.svg new file mode 100644 index 0000000..5fd9776 --- /dev/null +++ b/frontend/src/components/DataConnectorOption/media/youtube.svg @@ -0,0 +1,10 @@ + + + + + + + + + + diff --git a/frontend/src/components/DefaultChat/index.jsx b/frontend/src/components/DefaultChat/index.jsx new file mode 100644 index 0000000..a20e323 --- /dev/null +++ b/frontend/src/components/DefaultChat/index.jsx @@ -0,0 +1,363 @@ +import React, { useEffect, useState } from "react"; +import { + GithubLogo, + GitMerge, + EnvelopeSimple, + Plus, +} from "@phosphor-icons/react"; +import NewWorkspaceModal, { + useNewWorkspaceModal, +} from "../Modals/NewWorkspace"; +import paths from "@/utils/paths"; +import { isMobile } from "react-device-detect"; +import { SidebarMobileHeader } from "../Sidebar"; +import ChatBubble from "../ChatBubble"; +import System from "@/models/system"; +import Jazzicon from "../UserIcon"; +import { userFromStorage } from "@/utils/request"; +import { AI_BACKGROUND_COLOR, USER_BACKGROUND_COLOR } from "@/utils/constants"; +import useUser from "@/hooks/useUser"; + +export default function DefaultChatContainer() { + const [mockMsgs, setMockMessages] = useState([]); + const { user } = useUser(); + const [fetchedMessages, setFetchedMessages] = useState([]); + const { + showing: showingNewWsModal, + showModal: showNewWsModal, + hideModal: hideNewWsModal, + } = useNewWorkspaceModal(); + const popMsg = !window.localStorage.getItem("anythingllm_intro"); + + useEffect(() => { + const fetchData = async () => { + const fetchedMessages = await System.getWelcomeMessages(); + setFetchedMessages(fetchedMessages); + }; + fetchData(); + }, []); + + const MESSAGES = [ + +
+
+
+ + + + Welcome to AnythingLLM, AnythingLLM is an open-source AI tool by + Mintplex Labs that turns anything into a trained chatbot you can + query and chat with. AnythingLLM is a BYOK (bring-your-own-keys) + software so there is no subscription, fee, or charges for this + software outside of the services you want to use with it. + +
+
+
+ , + + +
+
+
+ + + + AnythingLLM is the easiest way to put powerful AI products like + OpenAi, GPT-4, LangChain, PineconeDB, ChromaDB, and other services + together in a neat package with no fuss to increase your + productivity by 100x. + +
+
+
+ , + + +
+
+
+ +
+ + AnythingLLM can run totally locally on your machine with little + overhead you wont even notice it's there! No GPU needed. Cloud + and on-premises installation is available as well. +
+ The AI tooling ecosystem gets more powerful everyday. + AnythingLLM makes it easy to use. + + + +

Create an issue on Github

+ +
+
+
+
+ , + + +
+
+
+ + + + How do I get started?! + +
+
+
+ , + + +
+
+
+ +
+ + It's simple. All collections are organized into buckets we call{" "} + "Workspaces". Workspaces are buckets of files, documents, + images, PDFs, and other files which will be transformed into + something LLM's can understand and use in conversation. +
+
+ You can add and remove files at anytime. + + + {(!user || user?.role !== "default") && ( + + )} +
+
+
+
+ , + + +
+
+
+ + + + Is this like an AI dropbox or something? What about chatting? It + is a chatbot isn't it? + +
+
+
+ , + + +
+
+
+ + + + AnythingLLM is more than a smarter Dropbox. +
+
+ AnythingLLM offers two ways of talking with your data: +
+
+ Query: Your chats will return data or inferences found with + the documents in your workspace it has access to. Adding more + documents to the Workspace make it smarter! +
+
+ Conversational: Your documents + your on-going chat history + both contribute to the LLM knowledge at the same time. Great for + appending real-time text-based info or corrections and + misunderstandings the LLM might have. +
+
+ You can toggle between either mode{" "} + in the middle of chatting! + +
+
+
+ , + + +
+
+
+ + + + Wow, this sounds amazing, let me try it out already! + +
+
+
+ , + + +
+
+ +
+
+ , + ]; + + useEffect(() => { + function processMsgs() { + if (!!window.localStorage.getItem("anythingllm_intro")) { + setMockMessages([...MESSAGES]); + return false; + } else { + setMockMessages([MESSAGES[0]]); + } + + var timer = 500; + var messages = []; + + MESSAGES.map((child) => { + setTimeout(() => { + setMockMessages([...messages, child]); + messages.push(child); + }, timer); + timer += 2_500; + }); + window.localStorage.setItem("anythingllm_intro", 1); + } + + processMsgs(); + }, []); + + return ( +
+ {isMobile && } + {fetchedMessages.length === 0 + ? mockMsgs.map((content, i) => { + return {content}; + }) + : fetchedMessages.map((fetchedMessage, i) => { + return ( + + + + ); + })} + {showingNewWsModal && } +
+ ); +} diff --git a/frontend/src/components/EditingChatBubble/index.jsx b/frontend/src/components/EditingChatBubble/index.jsx new file mode 100644 index 0000000..0aa2a07 --- /dev/null +++ b/frontend/src/components/EditingChatBubble/index.jsx @@ -0,0 +1,65 @@ +import React, { useState } from "react"; +import { X } from "@phosphor-icons/react"; + +export default function EditingChatBubble({ + message, + index, + type, + handleMessageChange, + removeMessage, +}) { + const [isEditing, setIsEditing] = useState(false); + const [tempMessage, setTempMessage] = useState(message[type]); + const isUser = type === "user"; + + return ( +
+

+ {isUser ? "User" : "AnythingLLM Chat Assistant"} +

+
+ +
setIsEditing(true)} + > + {isEditing ? ( + setTempMessage(e.target.value)} + onBlur={() => { + handleMessageChange(index, type, tempMessage); + setIsEditing(false); + }} + autoFocus + className={`w-full ${ + isUser ? "bg-[#41444C] text-white" : "bg-[#2E3036] text-white" + }`} + /> + ) : ( + tempMessage && ( +

+ {tempMessage} +

+ ) + )} +
+
+
+ ); +} diff --git a/frontend/src/components/EmbeddingSelection/AzureAiOptions/index.jsx b/frontend/src/components/EmbeddingSelection/AzureAiOptions/index.jsx new file mode 100644 index 0000000..209c0aa --- /dev/null +++ b/frontend/src/components/EmbeddingSelection/AzureAiOptions/index.jsx @@ -0,0 +1,55 @@ +export default function AzureAiOptions({ settings }) { + return ( +
+
+
+ + +
+ +
+ + +
+ +
+ + +
+
+
+ ); +} diff --git a/frontend/src/components/EmbeddingSelection/CohereOptions/index.jsx b/frontend/src/components/EmbeddingSelection/CohereOptions/index.jsx new file mode 100644 index 0000000..7cb0923 --- /dev/null +++ b/frontend/src/components/EmbeddingSelection/CohereOptions/index.jsx @@ -0,0 +1,55 @@ +export default function CohereEmbeddingOptions({ settings }) { + return ( +
+
+
+ + +
+
+ + +
+
+
+ ); +} diff --git a/frontend/src/components/EmbeddingSelection/EmbedderItem/index.jsx b/frontend/src/components/EmbeddingSelection/EmbedderItem/index.jsx new file mode 100644 index 0000000..72b3d73 --- /dev/null +++ b/frontend/src/components/EmbeddingSelection/EmbedderItem/index.jsx @@ -0,0 +1,37 @@ +export default function EmbedderItem({ + name, + value, + image, + description, + checked, + onClick, +}) { + return ( +
onClick(value)} + className={`w-full p-2 rounded-md hover:cursor-pointer hover:bg-white/10 ${ + checked ? "bg-white/10" : "" + }`} + > + +
+ {`${name} +
+
{name}
+
{description}
+
+
+
+ ); +} diff --git a/frontend/src/components/EmbeddingSelection/LMStudioOptions/index.jsx b/frontend/src/components/EmbeddingSelection/LMStudioOptions/index.jsx new file mode 100644 index 0000000..1192ce6 --- /dev/null +++ b/frontend/src/components/EmbeddingSelection/LMStudioOptions/index.jsx @@ -0,0 +1,120 @@ +import React, { useEffect, useState } from "react"; +import System from "@/models/system"; + +export default function LMStudioEmbeddingOptions({ settings }) { + const [basePathValue, setBasePathValue] = useState( + settings?.EmbeddingBasePath + ); + const [basePath, setBasePath] = useState(settings?.EmbeddingBasePath); + + return ( +
+
+
+ + setBasePathValue(e.target.value)} + onBlur={() => setBasePath(basePathValue)} + required={true} + autoComplete="off" + spellCheck={false} + /> +
+ +
+ + e.target.blur()} + defaultValue={settings?.EmbeddingModelMaxChunkLength} + required={false} + autoComplete="off" + /> +
+
+
+ ); +} + +function LMStudioModelSelection({ settings, basePath = null }) { + const [customModels, setCustomModels] = useState([]); + const [loading, setLoading] = useState(true); + + useEffect(() => { + async function findCustomModels() { + if (!basePath || !basePath.includes("/v1")) { + setCustomModels([]); + setLoading(false); + return; + } + setLoading(true); + const { models } = await System.customModels("lmstudio", null, basePath); + setCustomModels(models || []); + setLoading(false); + } + findCustomModels(); + }, [basePath]); + + if (loading || customModels.length == 0) { + return ( +
+ + +
+ ); + } + + return ( +
+ + +
+ ); +} diff --git a/frontend/src/components/EmbeddingSelection/LocalAiOptions/index.jsx b/frontend/src/components/EmbeddingSelection/LocalAiOptions/index.jsx new file mode 100644 index 0000000..8c611cd --- /dev/null +++ b/frontend/src/components/EmbeddingSelection/LocalAiOptions/index.jsx @@ -0,0 +1,151 @@ +import React, { useEffect, useState } from "react"; +import System from "@/models/system"; + +export default function LocalAiOptions({ settings }) { + const [basePathValue, setBasePathValue] = useState( + settings?.EmbeddingBasePath + ); + const [basePath, setBasePath] = useState(settings?.EmbeddingBasePath); + const [apiKeyValue, setApiKeyValue] = useState(settings?.LocalAiApiKey); + const [apiKey, setApiKey] = useState(settings?.LocalAiApiKey); + + return ( +
+
+
+ + setBasePathValue(e.target.value)} + onBlur={() => setBasePath(basePathValue)} + required={true} + autoComplete="off" + spellCheck={false} + /> +
+ +
+ + e.target.blur()} + defaultValue={settings?.EmbeddingModelMaxChunkLength} + required={false} + autoComplete="off" + /> +
+
+
+
+
+ +
+ setApiKeyValue(e.target.value)} + onBlur={() => setApiKey(apiKeyValue)} + /> +
+
+
+ ); +} + +function LocalAIModelSelection({ settings, apiKey = null, basePath = null }) { + const [customModels, setCustomModels] = useState([]); + const [loading, setLoading] = useState(true); + + useEffect(() => { + async function findCustomModels() { + if (!basePath || !basePath.includes("/v1")) { + setCustomModels([]); + setLoading(false); + return; + } + setLoading(true); + const { models } = await System.customModels( + "localai", + typeof apiKey === "boolean" ? null : apiKey, + basePath + ); + setCustomModels(models || []); + setLoading(false); + } + findCustomModels(); + }, [basePath, apiKey]); + + if (loading || customModels.length == 0) { + return ( +
+ + +
+ ); + } + + return ( +
+ + +
+ ); +} diff --git a/frontend/src/components/EmbeddingSelection/NativeEmbeddingOptions/index.jsx b/frontend/src/components/EmbeddingSelection/NativeEmbeddingOptions/index.jsx new file mode 100644 index 0000000..1cbfc68 --- /dev/null +++ b/frontend/src/components/EmbeddingSelection/NativeEmbeddingOptions/index.jsx @@ -0,0 +1,10 @@ +export default function NativeEmbeddingOptions() { + return ( +
+

+ There is no set up required when using AnythingLLM's native embedding + engine. +

+
+ ); +} diff --git a/frontend/src/components/EmbeddingSelection/OllamaOptions/index.jsx b/frontend/src/components/EmbeddingSelection/OllamaOptions/index.jsx new file mode 100644 index 0000000..3213f5d --- /dev/null +++ b/frontend/src/components/EmbeddingSelection/OllamaOptions/index.jsx @@ -0,0 +1,120 @@ +import React, { useEffect, useState } from "react"; +import System from "@/models/system"; + +export default function OllamaEmbeddingOptions({ settings }) { + const [basePathValue, setBasePathValue] = useState( + settings?.EmbeddingBasePath + ); + const [basePath, setBasePath] = useState(settings?.EmbeddingBasePath); + + return ( +
+
+
+ + setBasePathValue(e.target.value)} + onBlur={() => setBasePath(basePathValue)} + required={true} + autoComplete="off" + spellCheck={false} + /> +
+ +
+ + e.target.blur()} + defaultValue={settings?.EmbeddingModelMaxChunkLength} + required={false} + autoComplete="off" + /> +
+
+
+ ); +} + +function OllamaLLMModelSelection({ settings, basePath = null }) { + const [customModels, setCustomModels] = useState([]); + const [loading, setLoading] = useState(true); + + useEffect(() => { + async function findCustomModels() { + if (!basePath) { + setCustomModels([]); + setLoading(false); + return; + } + setLoading(true); + const { models } = await System.customModels("ollama", null, basePath); + setCustomModels(models || []); + setLoading(false); + } + findCustomModels(); + }, [basePath]); + + if (loading || customModels.length == 0) { + return ( +
+ + +
+ ); + } + + return ( +
+ + +
+ ); +} diff --git a/frontend/src/components/EmbeddingSelection/OpenAiOptions/index.jsx b/frontend/src/components/EmbeddingSelection/OpenAiOptions/index.jsx new file mode 100644 index 0000000..af266d5 --- /dev/null +++ b/frontend/src/components/EmbeddingSelection/OpenAiOptions/index.jsx @@ -0,0 +1,51 @@ +export default function OpenAiOptions({ settings }) { + return ( +
+
+
+ + +
+
+ + +
+
+
+ ); +} diff --git a/frontend/src/components/Footer/index.jsx b/frontend/src/components/Footer/index.jsx new file mode 100644 index 0000000..10cd80c --- /dev/null +++ b/frontend/src/components/Footer/index.jsx @@ -0,0 +1,107 @@ +import System from "@/models/system"; +import paths from "@/utils/paths"; +import { + BookOpen, + DiscordLogo, + GithubLogo, + Briefcase, + Envelope, + Globe, + HouseLine, + Info, + LinkSimple, +} from "@phosphor-icons/react"; +import React, { useEffect, useState } from "react"; +import SettingsButton from "../SettingsButton"; +import { isMobile } from "react-device-detect"; + +export const MAX_ICONS = 3; +export const ICON_COMPONENTS = { + BookOpen: BookOpen, + DiscordLogo: DiscordLogo, + GithubLogo: GithubLogo, + Envelope: Envelope, + LinkSimple: LinkSimple, + HouseLine: HouseLine, + Globe: Globe, + Briefcase: Briefcase, + Info: Info, +}; + +export default function Footer() { + const [footerData, setFooterData] = useState(false); + + useEffect(() => { + async function fetchFooterData() { + const { footerData } = await System.fetchCustomFooterIcons(); + setFooterData(footerData); + } + fetchFooterData(); + }, []); + + // wait for some kind of non-false response from footer data first + // to prevent pop-in. + if (footerData === false) return null; + + if (!Array.isArray(footerData) || footerData.length === 0) { + return ( +
+
+ + + + + + + + + + {!isMobile && } +
+
+ ); + } + + return ( + + ); +} diff --git a/frontend/src/components/LLMSelection/AnthropicAiOptions/index.jsx b/frontend/src/components/LLMSelection/AnthropicAiOptions/index.jsx new file mode 100644 index 0000000..9fe283f --- /dev/null +++ b/frontend/src/components/LLMSelection/AnthropicAiOptions/index.jsx @@ -0,0 +1,52 @@ +export default function AnthropicAiOptions({ settings }) { + return ( +
+
+
+ + +
+ + {!settings?.credentialsOnly && ( +
+ + +
+ )} +
+
+ ); +} diff --git a/frontend/src/components/LLMSelection/AzureAiOptions/index.jsx b/frontend/src/components/LLMSelection/AzureAiOptions/index.jsx new file mode 100644 index 0000000..224582e --- /dev/null +++ b/frontend/src/components/LLMSelection/AzureAiOptions/index.jsx @@ -0,0 +1,92 @@ +export default function AzureAiOptions({ settings }) { + return ( +
+
+
+ + +
+ +
+ + +
+ +
+ + +
+
+ +
+
+ + +
+ +
+ + +
+
+
+
+ ); +} diff --git a/frontend/src/components/LLMSelection/CohereAiOptions/index.jsx b/frontend/src/components/LLMSelection/CohereAiOptions/index.jsx new file mode 100644 index 0000000..a20c8b8 --- /dev/null +++ b/frontend/src/components/LLMSelection/CohereAiOptions/index.jsx @@ -0,0 +1,49 @@ +export default function CohereAiOptions({ settings }) { + return ( +
+
+
+ + +
+
+ + +
+
+
+ ); +} diff --git a/frontend/src/components/LLMSelection/GeminiLLMOptions/index.jsx b/frontend/src/components/LLMSelection/GeminiLLMOptions/index.jsx new file mode 100644 index 0000000..8cb513f --- /dev/null +++ b/frontend/src/components/LLMSelection/GeminiLLMOptions/index.jsx @@ -0,0 +1,45 @@ +export default function GeminiLLMOptions({ settings }) { + return ( +
+
+
+ + +
+ + {!settings?.credentialsOnly && ( +
+ + +
+ )} +
+
+ ); +} diff --git a/frontend/src/components/LLMSelection/GenericOpenAiOptions/index.jsx b/frontend/src/components/LLMSelection/GenericOpenAiOptions/index.jsx new file mode 100644 index 0000000..ac143e9 --- /dev/null +++ b/frontend/src/components/LLMSelection/GenericOpenAiOptions/index.jsx @@ -0,0 +1,81 @@ +export default function GenericOpenAiOptions({ settings }) { + return ( +
+
+ + +
+
+ + +
+
+ + +
+
+ + e.target.blur()} + defaultValue={settings?.GenericOpenAiTokenLimit} + required={true} + autoComplete="off" + /> +
+
+ + +
+
+ ); +} diff --git a/frontend/src/components/LLMSelection/GroqAiOptions/index.jsx b/frontend/src/components/LLMSelection/GroqAiOptions/index.jsx new file mode 100644 index 0000000..2b02e14 --- /dev/null +++ b/frontend/src/components/LLMSelection/GroqAiOptions/index.jsx @@ -0,0 +1,48 @@ +export default function GroqAiOptions({ settings }) { + return ( +
+
+ + +
+ + {!settings?.credentialsOnly && ( +
+ + +
+ )} +
+ ); +} diff --git a/frontend/src/components/LLMSelection/HuggingFaceOptions/index.jsx b/frontend/src/components/LLMSelection/HuggingFaceOptions/index.jsx new file mode 100644 index 0000000..c93a945 --- /dev/null +++ b/frontend/src/components/LLMSelection/HuggingFaceOptions/index.jsx @@ -0,0 +1,56 @@ +export default function HuggingFaceOptions({ settings }) { + return ( +
+
+
+ + +
+
+ + +
+
+ + e.target.blur()} + defaultValue={settings?.HuggingFaceLLMTokenLimit} + required={true} + autoComplete="off" + /> +
+
+
+ ); +} diff --git a/frontend/src/components/LLMSelection/KoboldCPPOptions/index.jsx b/frontend/src/components/LLMSelection/KoboldCPPOptions/index.jsx new file mode 100644 index 0000000..7e5e20a --- /dev/null +++ b/frontend/src/components/LLMSelection/KoboldCPPOptions/index.jsx @@ -0,0 +1,112 @@ +import { useState, useEffect } from "react"; +import System from "@/models/system"; + +export default function KoboldCPPOptions({ settings }) { + const [basePathValue, setBasePathValue] = useState( + settings?.KoboldCPPBasePath + ); + const [basePath, setBasePath] = useState(settings?.KoboldCPPBasePath); + + return ( +
+
+ + setBasePathValue(e.target.value)} + onBlur={() => setBasePath(basePathValue)} + /> +
+ +
+ + e.target.blur()} + defaultValue={settings?.KoboldCPPTokenLimit} + required={true} + autoComplete="off" + /> +
+
+ ); +} + +function KoboldCPPModelSelection({ settings, basePath = null }) { + const [customModels, setCustomModels] = useState([]); + const [loading, setLoading] = useState(true); + + useEffect(() => { + async function findCustomModels() { + if (!basePath || !basePath.includes("/v1")) { + setCustomModels([]); + setLoading(false); + return; + } + setLoading(true); + const { models } = await System.customModels("koboldcpp", null, basePath); + setCustomModels(models || []); + setLoading(false); + } + findCustomModels(); + }, [basePath]); + + if (loading || customModels.length === 0) { + return ( +
+ + +
+ ); + } + + return ( +
+ + +
+ ); +} diff --git a/frontend/src/components/LLMSelection/LLMItem/index.jsx b/frontend/src/components/LLMSelection/LLMItem/index.jsx new file mode 100644 index 0000000..e6b643a --- /dev/null +++ b/frontend/src/components/LLMSelection/LLMItem/index.jsx @@ -0,0 +1,37 @@ +export default function LLMItem({ + name, + value, + image, + description, + checked, + onClick, +}) { + return ( +
onClick(value)} + className={`w-full p-2 rounded-md hover:cursor-pointer hover:bg-white/10 ${ + checked ? "bg-white/10" : "" + }`} + > + +
+ {`${name} +
+
{name}
+
{description}
+
+
+
+ ); +} diff --git a/frontend/src/components/LLMSelection/LLMProviderOption/index.jsx b/frontend/src/components/LLMSelection/LLMProviderOption/index.jsx new file mode 100644 index 0000000..3c3ed44 --- /dev/null +++ b/frontend/src/components/LLMSelection/LLMProviderOption/index.jsx @@ -0,0 +1,37 @@ +export default function LLMProviderOption({ + name, + link, + description, + value, + image, + checked = false, + onClick, +}) { + return ( +
onClick(value)}> + + +
+ ); +} diff --git a/frontend/src/components/LLMSelection/LMStudioOptions/index.jsx b/frontend/src/components/LLMSelection/LMStudioOptions/index.jsx new file mode 100644 index 0000000..9a1c59b --- /dev/null +++ b/frontend/src/components/LLMSelection/LMStudioOptions/index.jsx @@ -0,0 +1,143 @@ +import { useEffect, useState } from "react"; +import { Info } from "@phosphor-icons/react"; +import paths from "@/utils/paths"; +import System from "@/models/system"; + +export default function LMStudioOptions({ settings, showAlert = false }) { + const [basePathValue, setBasePathValue] = useState( + settings?.LMStudioBasePath + ); + const [basePath, setBasePath] = useState(settings?.LMStudioBasePath); + + return ( +
+ {showAlert && ( +
+
+ +

+ LMStudio as your LLM requires you to set an embedding service to + use. +

+
+ + Manage embedding → + +
+ )} +
+
+ + setBasePathValue(e.target.value)} + onBlur={() => setBasePath(basePathValue)} + /> +
+ {!settings?.credentialsOnly && ( + <> + +
+ + e.target.blur()} + defaultValue={settings?.LMStudioTokenLimit} + required={true} + autoComplete="off" + /> +
+ + )} +
+
+ ); +} + +function LMStudioModelSelection({ settings, basePath = null }) { + const [customModels, setCustomModels] = useState([]); + const [loading, setLoading] = useState(true); + + useEffect(() => { + async function findCustomModels() { + if (!basePath || !basePath.includes("/v1")) { + setCustomModels([]); + setLoading(false); + return; + } + setLoading(true); + const { models } = await System.customModels("lmstudio", null, basePath); + setCustomModels(models || []); + setLoading(false); + } + findCustomModels(); + }, [basePath]); + + if (loading || customModels.length == 0) { + return ( +
+ + +
+ ); + } + + return ( +
+ + +
+ ); +} diff --git a/frontend/src/components/LLMSelection/LocalAiOptions/index.jsx b/frontend/src/components/LLMSelection/LocalAiOptions/index.jsx new file mode 100644 index 0000000..1304c9e --- /dev/null +++ b/frontend/src/components/LLMSelection/LocalAiOptions/index.jsx @@ -0,0 +1,173 @@ +import { useEffect, useState } from "react"; +import { Info } from "@phosphor-icons/react"; +import paths from "@/utils/paths"; +import System from "@/models/system"; + +export default function LocalAiOptions({ settings, showAlert = false }) { + const [basePathValue, setBasePathValue] = useState(settings?.LocalAiBasePath); + const [basePath, setBasePath] = useState(settings?.LocalAiBasePath); + const [apiKeyValue, setApiKeyValue] = useState(settings?.LocalAiApiKey); + const [apiKey, setApiKey] = useState(settings?.LocalAiApiKey); + + return ( +
+ {showAlert && ( +
+
+ +

+ LocalAI as your LLM requires you to set an embedding service to + use. +

+
+ + Manage embedding → + +
+ )} +
+
+ + setBasePathValue(e.target.value)} + onBlur={() => setBasePath(basePathValue)} + /> +
+ {!settings?.credentialsOnly && ( + <> + +
+ + e.target.blur()} + defaultValue={settings?.LocalAiTokenLimit} + required={true} + autoComplete="off" + /> +
+ + )} +
+
+
+
+ +
+ + setApiKeyValue(e.target.value)} + onBlur={() => setApiKey(apiKeyValue)} + /> +
+
+
+ ); +} + +function LocalAIModelSelection({ settings, basePath = null, apiKey = null }) { + const [customModels, setCustomModels] = useState([]); + const [loading, setLoading] = useState(true); + + useEffect(() => { + async function findCustomModels() { + if (!basePath || !basePath.includes("/v1")) { + setCustomModels([]); + setLoading(false); + return; + } + setLoading(true); + const { models } = await System.customModels( + "localai", + typeof apiKey === "boolean" ? null : apiKey, + basePath + ); + setCustomModels(models || []); + setLoading(false); + } + findCustomModels(); + }, [basePath, apiKey]); + + if (loading || customModels.length == 0) { + return ( +
+ + +
+ ); + } + + return ( +
+ + +
+ ); +} diff --git a/frontend/src/components/LLMSelection/MistralOptions/index.jsx b/frontend/src/components/LLMSelection/MistralOptions/index.jsx new file mode 100644 index 0000000..4daadcf --- /dev/null +++ b/frontend/src/components/LLMSelection/MistralOptions/index.jsx @@ -0,0 +1,105 @@ +import { useState, useEffect } from "react"; +import System from "@/models/system"; + +export default function MistralOptions({ settings }) { + const [inputValue, setInputValue] = useState(settings?.MistralApiKey); + const [mistralKey, setMistralKey] = useState(settings?.MistralApiKey); + + return ( +
+
+ + setInputValue(e.target.value)} + onBlur={() => setMistralKey(inputValue)} + /> +
+ {!settings?.credentialsOnly && ( + + )} +
+ ); +} + +function MistralModelSelection({ apiKey, settings }) { + const [customModels, setCustomModels] = useState([]); + const [loading, setLoading] = useState(true); + + useEffect(() => { + async function findCustomModels() { + if (!apiKey) { + setCustomModels([]); + setLoading(false); + return; + } + setLoading(true); + const { models } = await System.customModels( + "mistral", + typeof apiKey === "boolean" ? null : apiKey + ); + setCustomModels(models || []); + setLoading(false); + } + findCustomModels(); + }, [apiKey]); + + if (loading || customModels.length == 0) { + return ( +
+ + +
+ ); + } + + return ( +
+ + +
+ ); +} diff --git a/frontend/src/components/LLMSelection/NativeLLMOptions/index.jsx b/frontend/src/components/LLMSelection/NativeLLMOptions/index.jsx new file mode 100644 index 0000000..bb46c9c --- /dev/null +++ b/frontend/src/components/LLMSelection/NativeLLMOptions/index.jsx @@ -0,0 +1,102 @@ +import { useEffect, useState } from "react"; +import { Flask } from "@phosphor-icons/react"; +import System from "@/models/system"; + +export default function NativeLLMOptions({ settings }) { + return ( +
+
+
+ +

+ Using a locally hosted LLM is experimental. Use with caution. +

+
+
+
+ +
+
+ ); +} + +function NativeModelSelection({ settings }) { + const [customModels, setCustomModels] = useState([]); + const [loading, setLoading] = useState(true); + + useEffect(() => { + async function findCustomModels() { + setLoading(true); + const { models } = await System.customModels("native-llm", null, null); + setCustomModels(models || []); + setLoading(false); + } + findCustomModels(); + }, []); + + if (loading || customModels.length == 0) { + return ( +
+ + +
+ ); + } + + return ( + <> +
+ + +
+
+ + e.target.blur()} + defaultValue={settings?.NativeLLMTokenLimit} + required={true} + autoComplete="off" + /> +
+ + ); +} diff --git a/frontend/src/components/LLMSelection/OllamaLLMOptions/index.jsx b/frontend/src/components/LLMSelection/OllamaLLMOptions/index.jsx new file mode 100644 index 0000000..b08f294 --- /dev/null +++ b/frontend/src/components/LLMSelection/OllamaLLMOptions/index.jsx @@ -0,0 +1,124 @@ +import { useEffect, useState } from "react"; +import System from "@/models/system"; + +export default function OllamaLLMOptions({ settings }) { + const [basePathValue, setBasePathValue] = useState( + settings?.OllamaLLMBasePath + ); + const [basePath, setBasePath] = useState(settings?.OllamaLLMBasePath); + + return ( +
+
+
+ + setBasePathValue(e.target.value)} + onBlur={() => setBasePath(basePathValue)} + /> +
+ {!settings?.credentialsOnly && ( + <> + +
+ + e.target.blur()} + defaultValue={settings?.OllamaLLMTokenLimit} + required={true} + autoComplete="off" + /> +
+ + )} +
+
+ ); +} + +function OllamaLLMModelSelection({ settings, basePath = null }) { + const [customModels, setCustomModels] = useState([]); + const [loading, setLoading] = useState(true); + + useEffect(() => { + async function findCustomModels() { + if (!basePath) { + setCustomModels([]); + setLoading(false); + return; + } + setLoading(true); + const { models } = await System.customModels("ollama", null, basePath); + setCustomModels(models || []); + setLoading(false); + } + findCustomModels(); + }, [basePath]); + + if (loading || customModels.length == 0) { + return ( +
+ + +
+ ); + } + + return ( +
+ + +
+ ); +} diff --git a/frontend/src/components/LLMSelection/OpenAiOptions/index.jsx b/frontend/src/components/LLMSelection/OpenAiOptions/index.jsx new file mode 100644 index 0000000..67f7d29 --- /dev/null +++ b/frontend/src/components/LLMSelection/OpenAiOptions/index.jsx @@ -0,0 +1,107 @@ +import { useState, useEffect } from "react"; +import System from "@/models/system"; + +export default function OpenAiOptions({ settings }) { + const [inputValue, setInputValue] = useState(settings?.OpenAiKey); + const [openAIKey, setOpenAIKey] = useState(settings?.OpenAiKey); + + return ( +
+
+ + setInputValue(e.target.value)} + onBlur={() => setOpenAIKey(inputValue)} + /> +
+ {!settings?.credentialsOnly && ( + + )} +
+ ); +} + +function OpenAIModelSelection({ apiKey, settings }) { + const [groupedModels, setGroupedModels] = useState({}); + const [loading, setLoading] = useState(true); + + useEffect(() => { + async function findCustomModels() { + setLoading(true); + const { models } = await System.customModels( + "openai", + typeof apiKey === "boolean" ? null : apiKey + ); + + if (models?.length > 0) { + const modelsByOrganization = models.reduce((acc, model) => { + acc[model.organization] = acc[model.organization] || []; + acc[model.organization].push(model); + return acc; + }, {}); + setGroupedModels(modelsByOrganization); + } + + setLoading(false); + } + findCustomModels(); + }, [apiKey]); + + if (loading) { + return ( +
+ + +
+ ); + } + + return ( +
+ + +
+ ); +} diff --git a/frontend/src/components/LLMSelection/OpenRouterOptions/index.jsx b/frontend/src/components/LLMSelection/OpenRouterOptions/index.jsx new file mode 100644 index 0000000..94ae320 --- /dev/null +++ b/frontend/src/components/LLMSelection/OpenRouterOptions/index.jsx @@ -0,0 +1,99 @@ +import System from "@/models/system"; +import { useState, useEffect } from "react"; + +export default function OpenRouterOptions({ settings }) { + return ( +
+
+ + +
+ {!settings?.credentialsOnly && ( + + )} +
+ ); +} + +function OpenRouterModelSelection({ settings }) { + const [groupedModels, setGroupedModels] = useState({}); + const [loading, setLoading] = useState(true); + + useEffect(() => { + async function findCustomModels() { + setLoading(true); + const { models } = await System.customModels("openrouter"); + if (models?.length > 0) { + const modelsByOrganization = models.reduce((acc, model) => { + acc[model.organization] = acc[model.organization] || []; + acc[model.organization].push(model); + return acc; + }, {}); + + setGroupedModels(modelsByOrganization); + } + + setLoading(false); + } + findCustomModels(); + }, []); + + if (loading || Object.keys(groupedModels).length === 0) { + return ( +
+ + +
+ ); + } + + return ( +
+ + +
+ ); +} diff --git a/frontend/src/components/LLMSelection/PerplexityOptions/index.jsx b/frontend/src/components/LLMSelection/PerplexityOptions/index.jsx new file mode 100644 index 0000000..9b53cd1 --- /dev/null +++ b/frontend/src/components/LLMSelection/PerplexityOptions/index.jsx @@ -0,0 +1,90 @@ +import System from "@/models/system"; +import { useState, useEffect } from "react"; + +export default function PerplexityOptions({ settings }) { + return ( +
+
+ + +
+ {!settings?.credentialsOnly && ( + + )} +
+ ); +} + +function PerplexityModelSelection({ settings }) { + const [customModels, setCustomModels] = useState([]); + const [loading, setLoading] = useState(true); + + useEffect(() => { + async function findCustomModels() { + setLoading(true); + const { models } = await System.customModels("perplexity"); + setCustomModels(models || []); + setLoading(false); + } + findCustomModels(); + }, []); + + if (loading || customModels.length == 0) { + return ( +
+ + +
+ ); + } + + return ( +
+ + +
+ ); +} diff --git a/frontend/src/components/LLMSelection/TextGenWebUIOptions/index.jsx b/frontend/src/components/LLMSelection/TextGenWebUIOptions/index.jsx new file mode 100644 index 0000000..50bb841 --- /dev/null +++ b/frontend/src/components/LLMSelection/TextGenWebUIOptions/index.jsx @@ -0,0 +1,51 @@ +export default function TextGenWebUIOptions({ settings }) { + return ( +
+
+ + +
+
+ + e.target.blur()} + defaultValue={settings?.TextGenWebUITokenLimit} + required={true} + autoComplete="off" + /> +
+
+ + +
+
+ ); +} diff --git a/frontend/src/components/LLMSelection/TogetherAiOptions/index.jsx b/frontend/src/components/LLMSelection/TogetherAiOptions/index.jsx new file mode 100644 index 0000000..a5947a3 --- /dev/null +++ b/frontend/src/components/LLMSelection/TogetherAiOptions/index.jsx @@ -0,0 +1,99 @@ +import System from "@/models/system"; +import { useState, useEffect } from "react"; + +export default function TogetherAiOptions({ settings }) { + return ( +
+
+ + +
+ {!settings?.credentialsOnly && ( + + )} +
+ ); +} +function TogetherAiModelSelection({ settings }) { + const [groupedModels, setGroupedModels] = useState({}); + const [loading, setLoading] = useState(true); + + useEffect(() => { + async function findCustomModels() { + setLoading(true); + const { models } = await System.customModels("togetherai"); + + if (models?.length > 0) { + const modelsByOrganization = models.reduce((acc, model) => { + acc[model.organization] = acc[model.organization] || []; + acc[model.organization].push(model); + return acc; + }, {}); + + setGroupedModels(modelsByOrganization); + } + + setLoading(false); + } + findCustomModels(); + }, []); + + if (loading || Object.keys(groupedModels).length === 0) { + return ( +
+ + +
+ ); + } + + return ( +
+ + +
+ ); +} diff --git a/frontend/src/components/ModalWrapper/index.jsx b/frontend/src/components/ModalWrapper/index.jsx new file mode 100644 index 0000000..37041f6 --- /dev/null +++ b/frontend/src/components/ModalWrapper/index.jsx @@ -0,0 +1,9 @@ +export default function ModalWrapper({ children, isOpen }) { + if (!isOpen) return null; + + return ( +
+ {children} +
+ ); +} diff --git a/frontend/src/components/Modals/DisplayRecoveryCodeModal/index.jsx b/frontend/src/components/Modals/DisplayRecoveryCodeModal/index.jsx new file mode 100644 index 0000000..a75a353 --- /dev/null +++ b/frontend/src/components/Modals/DisplayRecoveryCodeModal/index.jsx @@ -0,0 +1,86 @@ +import showToast from "@/utils/toast"; +import { DownloadSimple, Key } from "@phosphor-icons/react"; +import { saveAs } from "file-saver"; +import { useState } from "react"; + +export default function RecoveryCodeModal({ + recoveryCodes, + onDownloadComplete, + onClose, +}) { + const [downloadClicked, setDownloadClicked] = useState(false); + + const downloadRecoveryCodes = () => { + const blob = new Blob([recoveryCodes.join("\n")], { type: "text/plain" }); + saveAs(blob, "recovery_codes.txt"); + setDownloadClicked(true); + }; + + const handleClose = () => { + if (downloadClicked) { + onDownloadComplete(); + onClose(); + } + }; + + const handleCopyToClipboard = () => { + navigator.clipboard.writeText(recoveryCodes.join(",\n")).then(() => { + showToast("Recovery codes copied to clipboard", "success", { + clear: true, + }); + }); + }; + + return ( +
+
+
+ + +
+
+

+ In order to reset your password in the future, you will need these + recovery codes. Download or copy your recovery codes to save them.{" "} +
+ These recovery codes are only shown once! +

+
+
    + {recoveryCodes.map((code, index) => ( +
  • + {code} +
    • + ))} +
+
+
+
+
+ +
+
+ ); +} diff --git a/frontend/src/components/Modals/MangeWorkspace/DataConnectors/ConnectorOption/index.jsx b/frontend/src/components/Modals/MangeWorkspace/DataConnectors/ConnectorOption/index.jsx new file mode 100644 index 0000000..e0b10e0 --- /dev/null +++ b/frontend/src/components/Modals/MangeWorkspace/DataConnectors/ConnectorOption/index.jsx @@ -0,0 +1,25 @@ +export default function ConnectorOption({ + slug, + selectedConnector, + setSelectedConnector, + image, + name, + description, +}) { + return ( + + ); +} diff --git a/frontend/src/components/Modals/MangeWorkspace/DataConnectors/Connectors/Confluence/index.jsx b/frontend/src/components/Modals/MangeWorkspace/DataConnectors/Connectors/Confluence/index.jsx new file mode 100644 index 0000000..52ca7e6 --- /dev/null +++ b/frontend/src/components/Modals/MangeWorkspace/DataConnectors/Connectors/Confluence/index.jsx @@ -0,0 +1,164 @@ +import { useState } from "react"; +import System from "@/models/system"; +import showToast from "@/utils/toast"; +import { Warning } from "@phosphor-icons/react"; +import { Tooltip } from "react-tooltip"; + +export default function ConfluenceOptions() { + const [loading, setLoading] = useState(false); + + const handleSubmit = async (e) => { + e.preventDefault(); + const form = new FormData(e.target); + + try { + setLoading(true); + showToast( + "Fetching all pages for Confluence space - this may take a while.", + "info", + { + clear: true, + autoClose: false, + } + ); + const { data, error } = await System.dataConnectors.confluence.collect({ + pageUrl: form.get("pageUrl"), + username: form.get("username"), + accessToken: form.get("accessToken"), + }); + + if (!!error) { + showToast(error, "error", { clear: true }); + setLoading(false); + return; + } + + showToast( + `Pages collected from Confluence space ${data.spaceKey}. Output folder is ${data.destination}.`, + "success", + { clear: true } + ); + e.target.reset(); + setLoading(false); + } catch (e) { + console.error(e); + showToast(e.message, "error", { clear: true }); + setLoading(false); + } + }; + + return ( +
+
+
+
+
+
+
+ +

+ URL of a page in the Confluence space. +

+
+ +
+
+
+ +

+ Your Confluence username. +

+
+ +
+
+
+ +

+ Access token for authentication. +

+
+ +
+
+
+ +
+ + {loading && ( +

+ Once complete, all pages will be available for embedding into + workspaces. +

+ )} +
+
+
+
+ ); +} diff --git a/frontend/src/components/Modals/MangeWorkspace/DataConnectors/Connectors/Github/index.jsx b/frontend/src/components/Modals/MangeWorkspace/DataConnectors/Connectors/Github/index.jsx new file mode 100644 index 0000000..de6ed77 --- /dev/null +++ b/frontend/src/components/Modals/MangeWorkspace/DataConnectors/Connectors/Github/index.jsx @@ -0,0 +1,271 @@ +import React, { useEffect, useState } from "react"; +import System from "@/models/system"; +import showToast from "@/utils/toast"; +import pluralize from "pluralize"; +import { TagsInput } from "react-tag-input-component"; +import { Warning } from "@phosphor-icons/react"; +import { Tooltip } from "react-tooltip"; + +const DEFAULT_BRANCHES = ["main", "master"]; +export default function GithubOptions() { + const [loading, setLoading] = useState(false); + const [repo, setRepo] = useState(null); + const [accessToken, setAccessToken] = useState(null); + const [ignores, setIgnores] = useState([]); + + const [settings, setSettings] = useState({ + repo: null, + accessToken: null, + }); + + const handleSubmit = async (e) => { + e.preventDefault(); + const form = new FormData(e.target); + + try { + setLoading(true); + showToast( + "Fetching all files for repo - this may take a while.", + "info", + { clear: true, autoClose: false } + ); + const { data, error } = await System.dataConnectors.github.collect({ + repo: form.get("repo"), + accessToken: form.get("accessToken"), + branch: form.get("branch"), + ignorePaths: ignores, + }); + + if (!!error) { + showToast(error, "error", { clear: true }); + setLoading(false); + return; + } + + showToast( + `${data.files} ${pluralize("file", data.files)} collected from ${ + data.author + }/${data.repo}:${data.branch}. Output folder is ${data.destination}.`, + "success", + { clear: true } + ); + e.target.reset(); + setLoading(false); + return; + } catch (e) { + console.error(e); + showToast(e.message, "error", { clear: true }); + setLoading(false); + } + }; + + return ( +
+
+
+
+
+
+
+ +

+ Url of the GitHub repo you wish to collect. +

+
+ setRepo(e.target.value)} + onBlur={() => setSettings({ ...settings, repo })} + spellCheck={false} + /> +
+
+
+ +

+ Access Token to prevent rate limiting. +

+
+ setAccessToken(e.target.value)} + onBlur={() => setSettings({ ...settings, accessToken })} + /> +
+ +
+ +
+
+ +

+ List in .gitignore format to ignore specific files during + collection. Press enter after each entry you want to save. +

+
+ +
+
+ +
+ + {loading && ( +

+ Once complete, all files will be available for embedding into + workspaces in the document picker. +

+ )} +
+
+
+
+ ); +} + +function GitHubBranchSelection({ repo, accessToken }) { + const [allBranches, setAllBranches] = useState(DEFAULT_BRANCHES); + const [loading, setLoading] = useState(true); + + useEffect(() => { + async function fetchAllBranches() { + if (!repo) { + setAllBranches(DEFAULT_BRANCHES); + setLoading(false); + return; + } + + setLoading(true); + const { branches } = await System.dataConnectors.github.branches({ + repo, + accessToken, + }); + setAllBranches(branches.length > 0 ? branches : DEFAULT_BRANCHES); + setLoading(false); + } + fetchAllBranches(); + }, [repo, accessToken]); + + if (loading) { + return ( +
+
+ +

+ Branch you wish to collect files from. +

+
+ +
+ ); + } + + return ( +
+
+ +

+ Branch you wish to collect files from. +

+
+ +
+ ); +} diff --git a/frontend/src/components/Modals/MangeWorkspace/DataConnectors/Connectors/WebsiteDepth/index.jsx b/frontend/src/components/Modals/MangeWorkspace/DataConnectors/Connectors/WebsiteDepth/index.jsx new file mode 100644 index 0000000..b3fc454 --- /dev/null +++ b/frontend/src/components/Modals/MangeWorkspace/DataConnectors/Connectors/WebsiteDepth/index.jsx @@ -0,0 +1,134 @@ +import React, { useState } from "react"; +import System from "@/models/system"; +import showToast from "@/utils/toast"; +import pluralize from "pluralize"; + +export default function WebsiteDepthOptions() { + const [loading, setLoading] = useState(false); + + const handleSubmit = async (e) => { + e.preventDefault(); + const form = new FormData(e.target); + + try { + setLoading(true); + showToast("Scraping website - this may take a while.", "info", { + clear: true, + autoClose: false, + }); + + const { data, error } = await System.dataConnectors.websiteDepth.scrape({ + url: form.get("url"), + depth: parseInt(form.get("depth")), + maxLinks: parseInt(form.get("maxLinks")), + }); + + if (!!error) { + showToast(error, "error", { clear: true }); + setLoading(false); + return; + } + + showToast( + `Successfully scraped ${data.length} ${pluralize( + "page", + data.length + )}!`, + "success", + { clear: true } + ); + e.target.reset(); + setLoading(false); + } catch (e) { + console.error(e); + showToast(e.message, "error", { clear: true }); + setLoading(false); + } + }; + + return ( +
+
+
+
+
+
+
+ +

+ URL of the website you want to scrape. +

+
+ +
+
+
+ +

+ This is the number of child-links that the worker should + follow from the origin URL. +

+
+ +
+
+
+ +

+ Maximum number of links to scrape. +

+
+ +
+
+
+ +
+ + {loading && ( +

+ Once complete, all scraped pages will be available for embedding + into workspaces in the document picker. +

+ )} +
+
+
+
+ ); +} diff --git a/frontend/src/components/Modals/MangeWorkspace/DataConnectors/Connectors/Youtube/index.jsx b/frontend/src/components/Modals/MangeWorkspace/DataConnectors/Connectors/Youtube/index.jsx new file mode 100644 index 0000000..ed18dcd --- /dev/null +++ b/frontend/src/components/Modals/MangeWorkspace/DataConnectors/Connectors/Youtube/index.jsx @@ -0,0 +1,91 @@ +import React, { useState } from "react"; +import System from "@/models/system"; +import showToast from "@/utils/toast"; + +export default function YoutubeOptions() { + const [loading, setLoading] = useState(false); + + const handleSubmit = async (e) => { + e.preventDefault(); + const form = new FormData(e.target); + + try { + setLoading(true); + showToast("Fetching transcript for YouTube video.", "info", { + clear: true, + autoClose: false, + }); + + const { data, error } = await System.dataConnectors.youtube.transcribe({ + url: form.get("url"), + }); + + if (!!error) { + showToast(error, "error", { clear: true }); + setLoading(false); + return; + } + + showToast( + `${data.title} by ${data.author} transcription completed. Output folder is ${data.destination}.`, + "success", + { clear: true } + ); + e.target.reset(); + setLoading(false); + return; + } catch (e) { + console.error(e); + showToast(e.message, "error", { clear: true }); + setLoading(false); + } + }; + + return ( +
+
+
+
+
+
+
+ +

+ URL of the YouTube video you wish to transcribe. +

+
+ +
+
+
+ +
+ + {loading && ( +

+ Once complete, the transcription will be available for embedding + into workspaces in the document picker. +

+ )} +
+
+
+
+ ); +} diff --git a/frontend/src/components/Modals/MangeWorkspace/DataConnectors/index.jsx b/frontend/src/components/Modals/MangeWorkspace/DataConnectors/index.jsx new file mode 100644 index 0000000..5a03e19 --- /dev/null +++ b/frontend/src/components/Modals/MangeWorkspace/DataConnectors/index.jsx @@ -0,0 +1,91 @@ +import ConnectorImages from "@/components/DataConnectorOption/media"; +import { MagnifyingGlass } from "@phosphor-icons/react"; +import GithubOptions from "./Connectors/Github"; +import YoutubeOptions from "./Connectors/Youtube"; +import ConfluenceOptions from "./Connectors/Confluence"; +import { useState } from "react"; +import ConnectorOption from "./ConnectorOption"; +import WebsiteDepthOptions from "./Connectors/WebsiteDepth"; + +export const DATA_CONNECTORS = { + github: { + name: "GitHub Repo", + image: ConnectorImages.github, + description: + "Import an entire public or private Github repository in a single click.", + options: , + }, + "youtube-transcript": { + name: "YouTube Transcript", + image: ConnectorImages.youtube, + description: + "Import the transcription of an entire YouTube video from a link.", + options: , + }, + "website-depth": { + name: "Bulk Link Scraper", + image: ConnectorImages.websiteDepth, + description: "Scrape a website and its sub-links up to a certain depth.", + options: , + }, + confluence: { + name: "Confluence", + image: ConnectorImages.confluence, + description: "Import an entire Confluence page in a single click.", + options: , + }, +}; + +export default function DataConnectors() { + const [selectedConnector, setSelectedConnector] = useState("github"); + const [searchQuery, setSearchQuery] = useState(""); + + const filteredConnectors = Object.keys(DATA_CONNECTORS).filter((slug) => + DATA_CONNECTORS[slug].name.toLowerCase().includes(searchQuery.toLowerCase()) + ); + + return ( +
+
+
+ + setSearchQuery(e.target.value)} + /> +
+
+ {filteredConnectors.length > 0 ? ( + filteredConnectors.map((slug, index) => ( + + )) + ) : ( +
+ No data connectors found. +
+ )} +
+
+
+
+ {DATA_CONNECTORS[selectedConnector].options} +
+
+ ); +} diff --git a/frontend/src/components/Modals/MangeWorkspace/Documents/Directory/FileRow/index.jsx b/frontend/src/components/Modals/MangeWorkspace/Documents/Directory/FileRow/index.jsx new file mode 100644 index 0000000..e679896 --- /dev/null +++ b/frontend/src/components/Modals/MangeWorkspace/Documents/Directory/FileRow/index.jsx @@ -0,0 +1,74 @@ +import { useState } from "react"; +import { + formatDate, + getFileExtension, + middleTruncate, +} from "@/utils/directories"; +import { File } from "@phosphor-icons/react"; +import debounce from "lodash.debounce"; + +export default function FileRow({ item, selected, toggleSelection }) { + const [showTooltip, setShowTooltip] = useState(false); + + const handleShowTooltip = () => { + setShowTooltip(true); + }; + + const handleHideTooltip = () => { + setShowTooltip(false); + }; + + const handleMouseEnter = debounce(handleShowTooltip, 500); + const handleMouseLeave = debounce(handleHideTooltip, 500); + + return ( + toggleSelection(item)} + className={`text-white/80 text-xs grid grid-cols-12 py-2 pl-3.5 pr-8 hover:bg-sky-500/20 cursor-pointer file-row ${ + selected ? "selected" : "" + }`} + > +
+
+ {selected &&
} +
+ +
+

+ {middleTruncate(item.title, 17)} +

+ {showTooltip && ( +
+ {item.title} +
+ )} +
+
+

+ {formatDate(item?.published)} +

+

+ {getFileExtension(item.url)} +

+
+ {item?.cached && ( +
+

Cached

+
+ )} +
+ + ); +} diff --git a/frontend/src/components/Modals/MangeWorkspace/Documents/Directory/FolderRow/index.jsx b/frontend/src/components/Modals/MangeWorkspace/Documents/Directory/FolderRow/index.jsx new file mode 100644 index 0000000..46c4b7f --- /dev/null +++ b/frontend/src/components/Modals/MangeWorkspace/Documents/Directory/FolderRow/index.jsx @@ -0,0 +1,75 @@ +import { useState } from "react"; +import FileRow from "../FileRow"; +import { CaretDown, FolderNotch } from "@phosphor-icons/react"; +import { middleTruncate } from "@/utils/directories"; + +export default function FolderRow({ + item, + selected, + onRowClick, + toggleSelection, + isSelected, + autoExpanded = false, +}) { + const [expanded, setExpanded] = useState(autoExpanded); + + const handleExpandClick = (event) => { + event.stopPropagation(); + setExpanded(!expanded); + }; + + return ( + <> + +
+
{ + event.stopPropagation(); + toggleSelection(item); + }} + > + {selected &&
} +
+
+ +
+ +

+ {middleTruncate(item.name, 35)} +

+
+

+

+ + {expanded && ( + <> + {item.items.map((fileItem) => ( + + ))} + + )} + + ); +} diff --git a/frontend/src/components/Modals/MangeWorkspace/Documents/Directory/FolderSelectionPopup/index.jsx b/frontend/src/components/Modals/MangeWorkspace/Documents/Directory/FolderSelectionPopup/index.jsx new file mode 100644 index 0000000..5261b89 --- /dev/null +++ b/frontend/src/components/Modals/MangeWorkspace/Documents/Directory/FolderSelectionPopup/index.jsx @@ -0,0 +1,24 @@ +import { middleTruncate } from "@/utils/directories"; + +export default function FolderSelectionPopup({ folders, onSelect, onClose }) { + const handleFolderSelect = (folder) => { + onSelect(folder); + onClose(); + }; + + return ( +

+
    + {folders.map((folder) => ( +
  • handleFolderSelect(folder)} + className="px-4 py-2 text-xs text-gray-700 hover:bg-gray-200 rounded-lg cursor-pointer whitespace-nowrap" + > + {middleTruncate(folder.name, 25)} +
    • + ))} +
+
+ ); +} diff --git a/frontend/src/components/Modals/MangeWorkspace/Documents/Directory/MoveToFolderIcon.jsx b/frontend/src/components/Modals/MangeWorkspace/Documents/Directory/MoveToFolderIcon.jsx new file mode 100644 index 0000000..3916fc7 --- /dev/null +++ b/frontend/src/components/Modals/MangeWorkspace/Documents/Directory/MoveToFolderIcon.jsx @@ -0,0 +1,44 @@ +export default function MoveToFolderIcon({ + className, + width = 18, + height = 18, +}) { + return ( + + + + + + + ); +} diff --git a/frontend/src/components/Modals/MangeWorkspace/Documents/Directory/index.jsx b/frontend/src/components/Modals/MangeWorkspace/Documents/Directory/index.jsx new file mode 100644 index 0000000..d479a6c --- /dev/null +++ b/frontend/src/components/Modals/MangeWorkspace/Documents/Directory/index.jsx @@ -0,0 +1,316 @@ +import UploadFile from "../UploadFile"; +import PreLoader from "@/components/Preloader"; +import { memo, useEffect, useState } from "react"; +import FolderRow from "./FolderRow"; +import System from "@/models/system"; +import { Plus, Trash } from "@phosphor-icons/react"; +import Document from "@/models/document"; +import showToast from "@/utils/toast"; +import FolderSelectionPopup from "./FolderSelectionPopup"; +import MoveToFolderIcon from "./MoveToFolderIcon"; + +function Directory({ + files, + setFiles, + loading, + setLoading, + workspace, + fetchKeys, + selectedItems, + setSelectedItems, + setHighlightWorkspace, + moveToWorkspace, + setLoadingMessage, + loadingMessage, +}) { + const [amountSelected, setAmountSelected] = useState(0); + const [newFolderName, setNewFolderName] = useState(""); + const [showNewFolderInput, setShowNewFolderInput] = useState(false); + const [showFolderSelection, setShowFolderSelection] = useState(false); + + useEffect(() => { + setAmountSelected(Object.keys(selectedItems).length); + }, [selectedItems]); + + const deleteFiles = async (event) => { + event.stopPropagation(); + if ( + !window.confirm( + "Are you sure you want to delete these files and folders?\nThis will remove the files from the system and remove them from any existing workspaces automatically.\nThis action is not reversible." + ) + ) { + return false; + } + + try { + const toRemove = []; + const foldersToRemove = []; + + for (const itemId of Object.keys(selectedItems)) { + for (const folder of files.items) { + const foundItem = folder.items.find((file) => file.id === itemId); + if (foundItem) { + toRemove.push(`${folder.name}/${foundItem.name}`); + break; + } + } + } + for (const folder of files.items) { + if (folder.name === "custom-documents") { + continue; + } + + if (isSelected(folder.id, folder)) { + foldersToRemove.push(folder.name); + } + } + + setLoading(true); + setLoadingMessage( + `Removing ${toRemove.length} documents and ${foldersToRemove.length} folders. Please wait.` + ); + await System.deleteDocuments(toRemove); + for (const folderName of foldersToRemove) { + await System.deleteFolder(folderName); + } + + await fetchKeys(true); + setSelectedItems({}); + } catch (error) { + console.error("Failed to delete files and folders:", error); + } finally { + setLoading(false); + setSelectedItems({}); + } + }; + + const toggleSelection = (item) => { + setSelectedItems((prevSelectedItems) => { + const newSelectedItems = { ...prevSelectedItems }; + if (item.type === "folder") { + // select all files in the folder + if (newSelectedItems[item.name]) { + delete newSelectedItems[item.name]; + item.items.forEach((file) => delete newSelectedItems[file.id]); + } else { + newSelectedItems[item.name] = true; + item.items.forEach((file) => (newSelectedItems[file.id] = true)); + } + } else { + // single file selections + if (newSelectedItems[item.id]) { + delete newSelectedItems[item.id]; + } else { + newSelectedItems[item.id] = true; + } + } + + return newSelectedItems; + }); + }; + + // check if item is selected based on selectedItems state + const isSelected = (id, item) => { + if (item && item.type === "folder") { + if (!selectedItems[item.name]) { + return false; + } + return item.items.every((file) => selectedItems[file.id]); + } + + return !!selectedItems[id]; + }; + + const createNewFolder = () => { + setShowNewFolderInput(true); + }; + + const confirmNewFolder = async () => { + if (newFolderName.trim() !== "") { + const newFolder = { + name: newFolderName, + type: "folder", + items: [], + }; + + // If folder failed to create - silently fail. + const { success } = await Document.createFolder(newFolderName); + if (success) { + setFiles({ + ...files, + items: [...files.items, newFolder], + }); + } + + setNewFolderName(""); + setShowNewFolderInput(false); + } + }; + + const moveToFolder = async (folder) => { + const toMove = []; + for (const itemId of Object.keys(selectedItems)) { + for (const currentFolder of files.items) { + const foundItem = currentFolder.items.find( + (file) => file.id === itemId + ); + if (foundItem) { + toMove.push({ ...foundItem, folderName: currentFolder.name }); + break; + } + } + } + setLoading(true); + setLoadingMessage(`Moving ${toMove.length} documents. Please wait.`); + const { success, message } = await Document.moveToFolder( + toMove, + folder.name + ); + if (!success) { + showToast(`Error moving files: ${message}`, "error"); + setLoading(false); + return; + } + + if (success && message) { + // show info if some files were not moved due to being embedded + showToast(message, "info"); + } else { + showToast(`Successfully moved ${toMove.length} documents.`, "success"); + } + await fetchKeys(true); + setSelectedItems({}); + setLoading(false); + }; + + return ( +
+
+
+

My Documents

+ {showNewFolderInput ? ( +
+ setNewFolderName(e.target.value)} + className="bg-zinc-900 text-white placeholder-white/20 text-sm rounded-md p-2.5 w-[150px] h-[32px]" + /> +
+ +
+
+ ) : ( + + )} +
+ +
+
+

Name

+

Date

+

Kind

+
+ +
+ {loading ? ( +
+ +

+ {loadingMessage} +

+
+ ) : files.items ? ( + files.items.map( + (item, index) => + item.type === "folder" && ( + toggleSelection(item)} + toggleSelection={toggleSelection} + isSelected={isSelected} + autoExpanded={index === 0} + /> + ) + ) + ) : ( +
+

+ No Documents +

+
+ )} +
+ {amountSelected !== 0 && ( +
+
+
+ +
+ + {showFolderSelection && ( + item.type === "folder" + )} + onSelect={moveToFolder} + onClose={() => setShowFolderSelection(false)} + /> + )} +
+ +
+
+
+ )} +
+ +
+
+ ); +} + +export default memo(Directory); diff --git a/frontend/src/components/Modals/MangeWorkspace/Documents/UploadFile/FileUploadProgress/index.jsx b/frontend/src/components/Modals/MangeWorkspace/Documents/UploadFile/FileUploadProgress/index.jsx new file mode 100644 index 0000000..104d45a --- /dev/null +++ b/frontend/src/components/Modals/MangeWorkspace/Documents/UploadFile/FileUploadProgress/index.jsx @@ -0,0 +1,138 @@ +import React, { useState, useEffect, memo } from "react"; +import truncate from "truncate"; +import { CheckCircle, XCircle } from "@phosphor-icons/react"; +import Workspace from "../../../../../../models/workspace"; +import { humanFileSize, milliToHms } from "../../../../../../utils/numbers"; +import PreLoader from "../../../../../Preloader"; + +function FileUploadProgressComponent({ + slug, + uuid, + file, + setFiles, + rejected = false, + reason = null, + onUploadSuccess, + onUploadError, + setLoading, + setLoadingMessage, +}) { + const [timerMs, setTimerMs] = useState(10); + const [status, setStatus] = useState("pending"); + const [error, setError] = useState(""); + const [isFadingOut, setIsFadingOut] = useState(false); + + const fadeOut = (cb) => { + setIsFadingOut(true); + cb?.(); + }; + + const beginFadeOut = () => { + setIsFadingOut(false); + setFiles((prev) => { + return prev.filter((item) => item.uid !== uuid); + }); + }; + + useEffect(() => { + async function uploadFile() { + setLoading(true); + setLoadingMessage("Uploading file..."); + const start = Number(new Date()); + const formData = new FormData(); + formData.append("file", file, file.name); + const timer = setInterval(() => { + setTimerMs(Number(new Date()) - start); + }, 100); + + // Chunk streaming not working in production so we just sit and wait + const { response, data } = await Workspace.uploadFile(slug, formData); + if (!response.ok) { + setStatus("failed"); + clearInterval(timer); + onUploadError(data.error); + setError(data.error); + } else { + setLoading(false); + setLoadingMessage(""); + setStatus("complete"); + clearInterval(timer); + onUploadSuccess(); + } + + // Begin fadeout timer to clear uploader queue. + setTimeout(() => { + fadeOut(() => setTimeout(() => beginFadeOut(), 300)); + }, 5000); + } + !!file && !rejected && uploadFile(); + }, []); + + if (rejected) { + return ( +
+
+ +
+
+

+ {truncate(file.name, 30)} +

+

{reason}

+
+
+ ); + } + + if (status === "failed") { + return ( +
+
+ +
+
+

+ {truncate(file.name, 30)} +

+

{error}

+
+
+ ); + } + + return ( +
+
+ {status !== "complete" ? ( +
+ +
+ ) : ( + + )} +
+
+

+ {truncate(file.name, 30)} +

+

+ {humanFileSize(file.size)} | {milliToHms(timerMs)} +

+
+
+ ); +} + +export default memo(FileUploadProgressComponent); diff --git a/frontend/src/components/Modals/MangeWorkspace/Documents/UploadFile/index.jsx b/frontend/src/components/Modals/MangeWorkspace/Documents/UploadFile/index.jsx new file mode 100644 index 0000000..8996829 --- /dev/null +++ b/frontend/src/components/Modals/MangeWorkspace/Documents/UploadFile/index.jsx @@ -0,0 +1,155 @@ +import { CloudArrowUp } from "@phosphor-icons/react"; +import { useEffect, useState } from "react"; +import showToast from "../../../../../utils/toast"; +import System from "../../../../../models/system"; +import { useDropzone } from "react-dropzone"; +import { v4 } from "uuid"; +import FileUploadProgress from "./FileUploadProgress"; +import Workspace from "../../../../../models/workspace"; +import debounce from "lodash.debounce"; + +export default function UploadFile({ + workspace, + fetchKeys, + setLoading, + setLoadingMessage, +}) { + const [ready, setReady] = useState(false); + const [files, setFiles] = useState([]); + const [fetchingUrl, setFetchingUrl] = useState(false); + + const handleSendLink = async (e) => { + e.preventDefault(); + setLoading(true); + setLoadingMessage("Scraping link..."); + setFetchingUrl(true); + const formEl = e.target; + const form = new FormData(formEl); + const { response, data } = await Workspace.uploadLink( + workspace.slug, + form.get("link") + ); + if (!response.ok) { + showToast(`Error uploading link: ${data.error}`, "error"); + } else { + fetchKeys(true); + showToast("Link uploaded successfully", "success"); + formEl.reset(); + } + setLoading(false); + setFetchingUrl(false); + }; + + // Don't spam fetchKeys, wait 1s between calls at least. + const handleUploadSuccess = debounce(() => fetchKeys(true), 1000); + const handleUploadError = (_msg) => null; // stubbed. + + const onDrop = async (acceptedFiles, rejections) => { + const newAccepted = acceptedFiles.map((file) => { + return { + uid: v4(), + file, + }; + }); + const newRejected = rejections.map((file) => { + return { + uid: v4(), + file: file.file, + rejected: true, + reason: file.errors[0].code, + }; + }); + setFiles([...newAccepted, ...newRejected]); + }; + + useEffect(() => { + async function checkProcessorOnline() { + const online = await System.checkDocumentProcessorOnline(); + setReady(online); + } + checkProcessorOnline(); + }, []); + + const { getRootProps, getInputProps } = useDropzone({ + onDrop, + disabled: !ready, + }); + + return ( +
+
+ + {ready === false ? ( +
+ +
+ Document Processor Unavailable +
+
+ We can't upload your files right now because the document + processor is offline. Please try again later. +
+
+ ) : files.length === 0 ? ( +
+ +
+ Click to upload or drag and drop +
+
+ supports text files, csv's, spreadsheets, audio files, and more! +
+
+ ) : ( +
+ {files.map((file) => ( + + ))} +
+ )} +
+
+ or submit a link +
+
+ + +
+
+ These files will be uploaded to the document processor running on this + AnythingLLM instance. These files are not sent or shared with a third + party. +
+
+ ); +} diff --git a/frontend/src/components/Modals/MangeWorkspace/Documents/WorkspaceDirectory/WorkspaceFileRow/index.jsx b/frontend/src/components/Modals/MangeWorkspace/Documents/WorkspaceDirectory/WorkspaceFileRow/index.jsx new file mode 100644 index 0000000..f473254 --- /dev/null +++ b/frontend/src/components/Modals/MangeWorkspace/Documents/WorkspaceDirectory/WorkspaceFileRow/index.jsx @@ -0,0 +1,185 @@ +import { memo, useState } from "react"; +import { + formatDate, + getFileExtension, + middleTruncate, +} from "@/utils/directories"; +import { ArrowUUpLeft, File, PushPin } from "@phosphor-icons/react"; +import Workspace from "@/models/workspace"; +import debounce from "lodash.debounce"; +import { Tooltip } from "react-tooltip"; +import showToast from "@/utils/toast"; + +export default function WorkspaceFileRow({ + item, + folderName, + workspace, + setLoading, + setLoadingMessage, + fetchKeys, + hasChanges, + movedItems, +}) { + const [showTooltip, setShowTooltip] = useState(false); + + const onRemoveClick = async () => { + setLoading(true); + + try { + setLoadingMessage(`Removing file from workspace`); + await Workspace.modifyEmbeddings(workspace.slug, { + adds: [], + deletes: [`${folderName}/${item.name}`], + }); + await fetchKeys(true); + } catch (error) { + console.error("Failed to remove document:", error); + } + + setLoadingMessage(""); + setLoading(false); + }; + + const handleShowTooltip = () => { + setShowTooltip(true); + }; + + const handleHideTooltip = () => { + setShowTooltip(false); + }; + + const isMovedItem = movedItems?.some((movedItem) => movedItem.id === item.id); + const handleMouseEnter = debounce(handleShowTooltip, 500); + const handleMouseLeave = debounce(handleHideTooltip, 500); + return ( +
+
+ +
+

+ {middleTruncate(item.title, 17)} +

+ {showTooltip && ( +
+ {item.title} +
+ )} +
+
+

+ {formatDate(item?.published)} +

+

+ {getFileExtension(item.url)} +

+
+ {hasChanges ? ( +
+ ) : ( +
+ + +
+ )} +
+
+ ); +} + +const PinItemToWorkspace = memo(({ workspace, docPath, item }) => { + const [pinned, setPinned] = useState( + item?.pinnedWorkspaces?.includes(workspace.id) || false + ); + const [hover, setHover] = useState(false); + const pinEvent = new CustomEvent("pinned_document"); + + const updatePinStatus = async () => { + try { + if (!pinned) window.dispatchEvent(pinEvent); + const success = await Workspace.setPinForDocument( + workspace.slug, + docPath, + !pinned + ); + + if (!success) { + showToast(`Failed to ${!pinned ? "pin" : "unpin"} document.`, "error", { + clear: true, + }); + return; + } + + showToast( + `Document ${!pinned ? "pinned to" : "unpinned from"} workspace`, + "success", + { clear: true } + ); + setPinned(!pinned); + } catch (error) { + showToast(`Failed to pin document. ${error.message}`, "error", { + clear: true, + }); + return; + } + }; + + if (!item) return
; + + return ( +
setHover(true)} + onMouseLeave={() => setHover(false)} + className="flex gap-x-2 items-center hover:bg-main-gradient p-[2px] rounded ml-2" + > + + +
+ ); +}); + +const RemoveItemFromWorkspace = ({ item, onClick }) => { + return ( +
+ + +
+ ); +}; diff --git a/frontend/src/components/Modals/MangeWorkspace/Documents/WorkspaceDirectory/index.jsx b/frontend/src/components/Modals/MangeWorkspace/Documents/WorkspaceDirectory/index.jsx new file mode 100644 index 0000000..4cfa55a --- /dev/null +++ b/frontend/src/components/Modals/MangeWorkspace/Documents/WorkspaceDirectory/index.jsx @@ -0,0 +1,191 @@ +import PreLoader from "@/components/Preloader"; +import { dollarFormat } from "@/utils/numbers"; +import WorkspaceFileRow from "./WorkspaceFileRow"; +import { memo, useEffect, useState } from "react"; +import ModalWrapper from "@/components/ModalWrapper"; +import { PushPin } from "@phosphor-icons/react"; +import { SEEN_DOC_PIN_ALERT } from "@/utils/constants"; + +function WorkspaceDirectory({ + workspace, + files, + highlightWorkspace, + loading, + loadingMessage, + setLoadingMessage, + setLoading, + fetchKeys, + hasChanges, + saveChanges, + embeddingCosts, + movedItems, +}) { + if (loading) { + return ( +
+
+

+ {workspace.name} +

+
+
+
+

Name

+

Date

+

Kind

+

+

+
+ +

+ {loadingMessage} +

+
+
+
+ ); + } + + return ( + <> +
+
+

+ {workspace.name} +

+
+
+
+

Name

+

Date

+

Kind

+

+

+
+ {Object.values(files.items).some( + (folder) => folder.items.length > 0 + ) || movedItems.length > 0 ? ( + <> + {files.items.map((folder) => + folder.items.map((item, index) => ( + + )) + )} + + ) : ( +
+

+ No Documents +

+
+ )} +
+
+ {hasChanges && ( +
+
+

+ {embeddingCosts === 0 + ? "" + : `Estimated Cost: ${ + embeddingCosts < 0.01 + ? `< $0.01` + : dollarFormat(embeddingCosts) + }`} +

+ +
+ + +
+ )} +
+ + + ); +} + +const PinAlert = memo(() => { + const [showAlert, setShowAlert] = useState(false); + function dismissAlert() { + setShowAlert(false); + window.localStorage.setItem(SEEN_DOC_PIN_ALERT, "1"); + window.removeEventListener(handlePinEvent); + } + + function handlePinEvent() { + if (!!window?.localStorage?.getItem(SEEN_DOC_PIN_ALERT)) return; + setShowAlert(true); + } + + useEffect(() => { + if (!window || !!window?.localStorage?.getItem(SEEN_DOC_PIN_ALERT)) return; + window?.addEventListener("pinned_document", handlePinEvent); + }, []); + + return ( + +
+
+
+
+ +

+ What is document pinning? +

+
+
+
+

+ When you pin a document in AnythingLLM we will inject the + entire content of the document into your prompt window for your + LLM to fully comprehend. +

+

+ This works best with large-context models or small files + that are critical to its knowledge-base. +

+

+ If you are not getting the answers you desire from AnythingLLM by + default then pinning is a great way to get higher quality answers + in a click. +

+
+ +
+ +
+
+
+ + ); +}); + +export default memo(WorkspaceDirectory); diff --git a/frontend/src/components/Modals/MangeWorkspace/Documents/index.jsx b/frontend/src/components/Modals/MangeWorkspace/Documents/index.jsx new file mode 100644 index 0000000..98244d5 --- /dev/null +++ b/frontend/src/components/Modals/MangeWorkspace/Documents/index.jsx @@ -0,0 +1,230 @@ +import { ArrowsDownUp } from "@phosphor-icons/react"; +import { useEffect, useState } from "react"; +import Workspace from "../../../../models/workspace"; +import System from "../../../../models/system"; +import showToast from "../../../../utils/toast"; +import Directory from "./Directory"; +import WorkspaceDirectory from "./WorkspaceDirectory"; + +// OpenAI Cost per token +// ref: https://openai.com/pricing#:~:text=%C2%A0/%201K%20tokens-,Embedding%20models,-Build%20advanced%20search + +const MODEL_COSTS = { + "text-embedding-ada-002": 0.0000001, // $0.0001 / 1K tokens + "text-embedding-3-small": 0.00000002, // $0.00002 / 1K tokens + "text-embedding-3-large": 0.00000013, // $0.00013 / 1K tokens +}; + +export default function DocumentSettings({ workspace, systemSettings }) { + const [highlightWorkspace, setHighlightWorkspace] = useState(false); + const [availableDocs, setAvailableDocs] = useState([]); + const [loading, setLoading] = useState(true); + const [workspaceDocs, setWorkspaceDocs] = useState([]); + const [selectedItems, setSelectedItems] = useState({}); + const [hasChanges, setHasChanges] = useState(false); + const [movedItems, setMovedItems] = useState([]); + const [embeddingsCost, setEmbeddingsCost] = useState(0); + const [loadingMessage, setLoadingMessage] = useState(""); + + async function fetchKeys(refetchWorkspace = false) { + setLoading(true); + const localFiles = await System.localFiles(); + const currentWorkspace = refetchWorkspace + ? await Workspace.bySlug(workspace.slug) + : workspace; + + const documentsInWorkspace = + currentWorkspace.documents.map((doc) => doc.docpath) || []; + + // Documents that are not in the workspace + const availableDocs = { + ...localFiles, + items: localFiles.items.map((folder) => { + if (folder.items && folder.type === "folder") { + return { + ...folder, + items: folder.items.filter( + (file) => + file.type === "file" && + !documentsInWorkspace.includes(`${folder.name}/${file.name}`) + ), + }; + } else { + return folder; + } + }), + }; + + // Documents that are already in the workspace + const workspaceDocs = { + ...localFiles, + items: localFiles.items.map((folder) => { + if (folder.items && folder.type === "folder") { + return { + ...folder, + items: folder.items.filter( + (file) => + file.type === "file" && + documentsInWorkspace.includes(`${folder.name}/${file.name}`) + ), + }; + } else { + return folder; + } + }), + }; + + setAvailableDocs(availableDocs); + setWorkspaceDocs(workspaceDocs); + setLoading(false); + } + + useEffect(() => { + fetchKeys(true); + }, []); + + const updateWorkspace = async (e) => { + e.preventDefault(); + setLoading(true); + showToast("Updating workspace...", "info", { autoClose: false }); + setLoadingMessage("This may take a while for large documents"); + + const changesToSend = { + adds: movedItems.map((item) => `${item.folderName}/${item.name}`), + }; + + setSelectedItems({}); + setHasChanges(false); + setHighlightWorkspace(false); + await Workspace.modifyEmbeddings(workspace.slug, changesToSend) + .then((res) => { + if (!!res.message) { + showToast(`Error: ${res.message}`, "error", { clear: true }); + return; + } + showToast("Workspace updated successfully.", "success", { + clear: true, + }); + }) + .catch((error) => { + showToast(`Workspace update failed: ${error}`, "error", { + clear: true, + }); + }); + + setMovedItems([]); + await fetchKeys(true); + setLoading(false); + setLoadingMessage(""); + }; + + const moveSelectedItemsToWorkspace = () => { + setHighlightWorkspace(false); + setHasChanges(true); + + const newMovedItems = []; + + for (const itemId of Object.keys(selectedItems)) { + for (const folder of availableDocs.items) { + const foundItem = folder.items.find((file) => file.id === itemId); + if (foundItem) { + newMovedItems.push({ ...foundItem, folderName: folder.name }); + break; + } + } + } + + let totalTokenCount = 0; + newMovedItems.forEach((item) => { + const { cached, token_count_estimate } = item; + if (!cached) { + totalTokenCount += token_count_estimate; + } + }); + + // Do not do cost estimation unless the embedding engine is OpenAi. + if (systemSettings?.EmbeddingEngine === "openai") { + const COST_PER_TOKEN = + MODEL_COSTS[ + systemSettings?.EmbeddingModelPref || "text-embedding-ada-002" + ]; + + const dollarAmount = (totalTokenCount / 1000) * COST_PER_TOKEN; + setEmbeddingsCost(dollarAmount); + } + + setMovedItems([...movedItems, ...newMovedItems]); + + let newAvailableDocs = JSON.parse(JSON.stringify(availableDocs)); + let newWorkspaceDocs = JSON.parse(JSON.stringify(workspaceDocs)); + + for (const itemId of Object.keys(selectedItems)) { + let foundItem = null; + let foundFolderIndex = null; + + newAvailableDocs.items = newAvailableDocs.items.map( + (folder, folderIndex) => { + const remainingItems = folder.items.filter((file) => { + const match = file.id === itemId; + if (match) { + foundItem = { ...file }; + foundFolderIndex = folderIndex; + } + return !match; + }); + + return { + ...folder, + items: remainingItems, + }; + } + ); + + if (foundItem) { + newWorkspaceDocs.items[foundFolderIndex].items.push(foundItem); + } + } + + setAvailableDocs(newAvailableDocs); + setWorkspaceDocs(newWorkspaceDocs); + setSelectedItems({}); + }; + + return ( +
+ +
+ +
+ +
+ ); +} diff --git a/frontend/src/components/Modals/MangeWorkspace/index.jsx b/frontend/src/components/Modals/MangeWorkspace/index.jsx new file mode 100644 index 0000000..2c6e658 --- /dev/null +++ b/frontend/src/components/Modals/MangeWorkspace/index.jsx @@ -0,0 +1,145 @@ +import React, { useState, useEffect, memo } from "react"; +import { X } from "@phosphor-icons/react"; +import { useParams } from "react-router-dom"; +import Workspace from "../../../models/workspace"; +import System from "../../../models/system"; +import { isMobile } from "react-device-detect"; +import useUser from "../../../hooks/useUser"; +import DocumentSettings from "./Documents"; +import DataConnectors from "./DataConnectors"; + +const noop = () => {}; +const ManageWorkspace = ({ hideModal = noop, providedSlug = null }) => { + const { slug } = useParams(); + const { user } = useUser(); + const [workspace, setWorkspace] = useState(null); + const [settings, setSettings] = useState({}); + const [selectedTab, setSelectedTab] = useState("documents"); + + useEffect(() => { + async function getSettings() { + const _settings = await System.keys(); + setSettings(_settings ?? {}); + } + getSettings(); + }, []); + + useEffect(() => { + async function fetchWorkspace() { + const workspace = await Workspace.bySlug(providedSlug ?? slug); + setWorkspace(workspace); + } + fetchWorkspace(); + }, [providedSlug, slug]); + + if (!workspace) return null; + + if (isMobile) { + return ( +
+
+
+
+
+

+ Editing "{workspace.name}" +

+

+ Editing these settings are only available on a desktop device. + Please access this page on your desktop to continue. +

+
+ +
+
+
+
+
+ ); + } + + return ( +
+
+
+
+
+ +
+ + {user?.role !== "default" && ( + + )} + + {selectedTab === "documents" ? ( + + ) : ( + + )} +
+
+
+ ); +}; + +export default memo(ManageWorkspace); + +const ModalTabSwitcher = ({ selectedTab, setSelectedTab }) => { + return ( +
+
+ + +
+
+ ); +}; +export function useManageWorkspaceModal() { + const { user } = useUser(); + const [showing, setShowing] = useState(false); + + const showModal = () => { + if (user?.role !== "default") { + setShowing(true); + } + }; + + const hideModal = () => { + setShowing(false); + }; + + return { showing, showModal, hideModal }; +} diff --git a/frontend/src/components/Modals/NewWorkspace.jsx b/frontend/src/components/Modals/NewWorkspace.jsx new file mode 100644 index 0000000..ed00f6f --- /dev/null +++ b/frontend/src/components/Modals/NewWorkspace.jsx @@ -0,0 +1,91 @@ +import React, { useRef, useState } from "react"; +import { X } from "@phosphor-icons/react"; +import Workspace from "@/models/workspace"; +import paths from "@/utils/paths"; + +const noop = () => false; +export default function NewWorkspaceModal({ hideModal = noop }) { + const formEl = useRef(null); + const [error, setError] = useState(null); + const handleCreate = async (e) => { + setError(null); + e.preventDefault(); + const data = {}; + const form = new FormData(formEl.current); + for (var [key, value] of form.entries()) data[key] = value; + const { workspace, message } = await Workspace.new(data); + if (!!workspace) { + window.location.href = paths.workspace.chat(workspace.slug); + } + setError(message); + }; + + return ( +
+
+
+
+
+

New Workspace

+ +
+
+
+
+
+ + +
+ {error && ( +

Error: {error}

+ )} +
+
+
+ +
+
+
+
+
+ ); +} + +export function useNewWorkspaceModal() { + const [showing, setShowing] = useState(false); + const showModal = () => { + setShowing(true); + }; + const hideModal = () => { + setShowing(false); + }; + + return { showing, showModal, hideModal }; +} diff --git a/frontend/src/components/Modals/Password/MultiUserAuth.jsx b/frontend/src/components/Modals/Password/MultiUserAuth.jsx new file mode 100644 index 0000000..e4de5e6 --- /dev/null +++ b/frontend/src/components/Modals/Password/MultiUserAuth.jsx @@ -0,0 +1,336 @@ +import React, { useEffect, useState } from "react"; +import System from "../../../models/system"; +import { AUTH_TOKEN, AUTH_USER } from "../../../utils/constants"; +import paths from "../../../utils/paths"; +import showToast from "@/utils/toast"; +import ModalWrapper from "@/components/ModalWrapper"; +import { useModal } from "@/hooks/useModal"; +import RecoveryCodeModal from "@/components/Modals/DisplayRecoveryCodeModal"; + +const RecoveryForm = ({ onSubmit, setShowRecoveryForm }) => { + const [username, setUsername] = useState(""); + const [recoveryCodeInputs, setRecoveryCodeInputs] = useState( + Array(2).fill("") + ); + + const handleRecoveryCodeChange = (index, value) => { + const updatedCodes = [...recoveryCodeInputs]; + updatedCodes[index] = value; + setRecoveryCodeInputs(updatedCodes); + }; + + const handleSubmit = (e) => { + e.preventDefault(); + const recoveryCodes = recoveryCodeInputs.filter( + (code) => code.trim() !== "" + ); + onSubmit(username, recoveryCodes); + }; + + return ( +
+
+
+

+ Password Reset +

+

+ Provide the necessary information below to reset your password. +

+
+
+
+
+
+ + setUsername(e.target.value)} + className="bg-zinc-900 text-white placeholder-white/20 text-sm rounded-md p-2.5 w-full h-[48px] md:w-[300px] md:h-[34px]" + required + /> +
+
+ + {recoveryCodeInputs.map((code, index) => ( +
+ + handleRecoveryCodeChange(index, e.target.value) + } + className="bg-zinc-900 text-white placeholder-white/20 text-sm rounded-md p-2.5 w-full h-[48px] md:w-[300px] md:h-[34px]" + required + /> +
+ ))} +
+
+
+
+ + +
+
+ ); +}; + +const ResetPasswordForm = ({ onSubmit }) => { + const [newPassword, setNewPassword] = useState(""); + const [confirmPassword, setConfirmPassword] = useState(""); + + const handleSubmit = (e) => { + e.preventDefault(); + onSubmit(newPassword, confirmPassword); + }; + + return ( +
+
+
+

+ Reset Password +

+

+ Enter your new password. +

+
+
+
+
+
+ setNewPassword(e.target.value)} + className="bg-zinc-900 text-white placeholder-white/20 text-sm rounded-md p-2.5 w-full h-[48px] md:w-[300px] md:h-[34px]" + required + /> +
+
+ setConfirmPassword(e.target.value)} + className="bg-zinc-900 text-white placeholder-white/20 text-sm rounded-md p-2.5 w-full h-[48px] md:w-[300px] md:h-[34px]" + required + /> +
+
+
+
+ +
+
+ ); +}; + +export default function MultiUserAuth() { + const [loading, setLoading] = useState(false); + const [error, setError] = useState(null); + const [recoveryCodes, setRecoveryCodes] = useState([]); + const [downloadComplete, setDownloadComplete] = useState(false); + const [user, setUser] = useState(null); + const [token, setToken] = useState(null); + const [showRecoveryForm, setShowRecoveryForm] = useState(false); + const [showResetPasswordForm, setShowResetPasswordForm] = useState(false); + + const { + isOpen: isRecoveryCodeModalOpen, + openModal: openRecoveryCodeModal, + closeModal: closeRecoveryCodeModal, + } = useModal(); + + const handleLogin = async (e) => { + setError(null); + setLoading(true); + e.preventDefault(); + const data = {}; + const form = new FormData(e.target); + for (var [key, value] of form.entries()) data[key] = value; + const { valid, user, token, message, recoveryCodes } = + await System.requestToken(data); + if (valid && !!token && !!user) { + setUser(user); + setToken(token); + + if (recoveryCodes) { + setRecoveryCodes(recoveryCodes); + openRecoveryCodeModal(); + } else { + window.localStorage.setItem(AUTH_USER, JSON.stringify(user)); + window.localStorage.setItem(AUTH_TOKEN, token); + window.location = paths.home(); + } + } else { + setError(message); + setLoading(false); + } + setLoading(false); + }; + + const handleDownloadComplete = () => setDownloadComplete(true); + const handleResetPassword = () => setShowRecoveryForm(true); + const handleRecoverySubmit = async (username, recoveryCodes) => { + const { success, resetToken, error } = await System.recoverAccount( + username, + recoveryCodes + ); + + if (success && resetToken) { + window.localStorage.setItem("resetToken", resetToken); + setShowRecoveryForm(false); + setShowResetPasswordForm(true); + } else { + showToast(error, "error", { clear: true }); + } + }; + + const handleResetSubmit = async (newPassword, confirmPassword) => { + const resetToken = window.localStorage.getItem("resetToken"); + + if (resetToken) { + const { success, error } = await System.resetPassword( + resetToken, + newPassword, + confirmPassword + ); + + if (success) { + window.localStorage.removeItem("resetToken"); + setShowResetPasswordForm(false); + showToast("Password reset successful", "success", { clear: true }); + } else { + showToast(error, "error", { clear: true }); + } + } else { + showToast("Invalid reset token", "error", { clear: true }); + } + }; + + useEffect(() => { + if (downloadComplete && user && token) { + window.localStorage.setItem(AUTH_USER, JSON.stringify(user)); + window.localStorage.setItem(AUTH_TOKEN, token); + window.location = paths.home(); + } + }, [downloadComplete, user, token]); + + if (showRecoveryForm) { + return ( + + ); + } + + if (showResetPasswordForm) + return ; + return ( + <> +
+
+
+
+
+

+ Welcome to +

+

+ AnythingLLM +

+
+

+ Sign in to your AnythingLLM account. +

+
+
+
+
+
+ +
+
+ +
+ {error &&

Error: {error}

} +
+
+
+ + +
+
+
+ + + + + + ); +} diff --git a/frontend/src/components/Modals/Password/SingleUserAuth.jsx b/frontend/src/components/Modals/Password/SingleUserAuth.jsx new file mode 100644 index 0000000..c1f328b --- /dev/null +++ b/frontend/src/components/Modals/Password/SingleUserAuth.jsx @@ -0,0 +1,116 @@ +import React, { useEffect, useState } from "react"; +import System from "../../../models/system"; +import { AUTH_TOKEN } from "../../../utils/constants"; +import useLogo from "../../../hooks/useLogo"; +import paths from "../../../utils/paths"; +import ModalWrapper from "@/components/ModalWrapper"; +import { useModal } from "@/hooks/useModal"; +import RecoveryCodeModal from "@/components/Modals/DisplayRecoveryCodeModal"; + +export default function SingleUserAuth() { + const [loading, setLoading] = useState(false); + const [error, setError] = useState(null); + const { logo: _initLogo } = useLogo(); + const [recoveryCodes, setRecoveryCodes] = useState([]); + const [downloadComplete, setDownloadComplete] = useState(false); + const [token, setToken] = useState(null); + + const { + isOpen: isRecoveryCodeModalOpen, + openModal: openRecoveryCodeModal, + closeModal: closeRecoveryCodeModal, + } = useModal(); + + const handleLogin = async (e) => { + setError(null); + setLoading(true); + e.preventDefault(); + const data = {}; + const form = new FormData(e.target); + for (var [key, value] of form.entries()) data[key] = value; + const { valid, token, message, recoveryCodes } = + await System.requestToken(data); + if (valid && !!token) { + setToken(token); + if (recoveryCodes) { + setRecoveryCodes(recoveryCodes); + openRecoveryCodeModal(); + } else { + window.localStorage.setItem(AUTH_TOKEN, token); + window.location = paths.home(); + } + } else { + setError(message); + setLoading(false); + } + setLoading(false); + }; + + const handleDownloadComplete = () => { + setDownloadComplete(true); + }; + + useEffect(() => { + if (downloadComplete && token) { + window.localStorage.setItem(AUTH_TOKEN, token); + window.location = paths.home(); + } + }, [downloadComplete, token]); + + return ( + <> +
+
+
+
+
+

+ Welcome to +

+

+ AnythingLLM +

+
+

+ Sign in to your AnythingLLM instance. +

+
+
+
+
+
+ +
+ + {error &&

Error: {error}

} +
+
+
+ +
+
+
+ + + + + + ); +} diff --git a/frontend/src/components/Modals/Password/index.jsx b/frontend/src/components/Modals/Password/index.jsx new file mode 100644 index 0000000..9305d03 --- /dev/null +++ b/frontend/src/components/Modals/Password/index.jsx @@ -0,0 +1,152 @@ +import React, { useState, useEffect } from "react"; +import System from "../../../models/system"; +import SingleUserAuth from "./SingleUserAuth"; +import MultiUserAuth from "./MultiUserAuth"; +import { + AUTH_TOKEN, + AUTH_USER, + AUTH_TIMESTAMP, +} from "../../../utils/constants"; +import useLogo from "../../../hooks/useLogo"; +import illustration from "@/media/illustrations/login-illustration.svg"; +import loginLogo from "@/media/illustrations/login-logo.svg"; + +export default function PasswordModal({ mode = "single" }) { + const { logo: _initLogo } = useLogo(); + return ( +
+
+
+ login illustration +
+
+ logo + {mode === "single" ? : } +
+
+ ); +} + +export function usePasswordModal(notry = false) { + const [auth, setAuth] = useState({ + loading: true, + requiresAuth: false, + mode: "single", + }); + + useEffect(() => { + async function checkAuthReq() { + if (!window) return; + + // If the last validity check is still valid + // we can skip the loading. + if (!System.needsAuthCheck() && notry === false) { + setAuth({ + loading: false, + requiresAuth: false, + mode: "multi", + }); + return; + } + + const settings = await System.keys(); + if (settings?.MultiUserMode) { + const currentToken = window.localStorage.getItem(AUTH_TOKEN); + if (!!currentToken) { + const valid = notry ? false : await System.checkAuth(currentToken); + if (!valid) { + setAuth({ + loading: false, + requiresAuth: true, + mode: "multi", + }); + window.localStorage.removeItem(AUTH_USER); + window.localStorage.removeItem(AUTH_TOKEN); + window.localStorage.removeItem(AUTH_TIMESTAMP); + return; + } else { + setAuth({ + loading: false, + requiresAuth: false, + mode: "multi", + }); + return; + } + } else { + setAuth({ + loading: false, + requiresAuth: true, + mode: "multi", + }); + return; + } + } else { + // Running token check in single user Auth mode. + // If Single user Auth is disabled - skip check + const requiresAuth = settings?.RequiresAuth || false; + if (!requiresAuth) { + setAuth({ + loading: false, + requiresAuth: false, + mode: "single", + }); + return; + } + + const currentToken = window.localStorage.getItem(AUTH_TOKEN); + if (!!currentToken) { + const valid = notry ? false : await System.checkAuth(currentToken); + if (!valid) { + setAuth({ + loading: false, + requiresAuth: true, + mode: "single", + }); + window.localStorage.removeItem(AUTH_TOKEN); + window.localStorage.removeItem(AUTH_USER); + window.localStorage.removeItem(AUTH_TIMESTAMP); + return; + } else { + setAuth({ + loading: false, + requiresAuth: false, + mode: "single", + }); + return; + } + } else { + setAuth({ + loading: false, + requiresAuth: true, + mode: "single", + }); + return; + } + } + } + checkAuthReq(); + }, []); + + return auth; +} diff --git a/frontend/src/components/Preloader.jsx b/frontend/src/components/Preloader.jsx new file mode 100644 index 0000000..4a81437 --- /dev/null +++ b/frontend/src/components/Preloader.jsx @@ -0,0 +1,18 @@ +export default function PreLoader({ size = "16" }) { + return ( +
+ ); +} + +export function FullScreenLoader() { + return ( +
+
+
+ ); +} diff --git a/frontend/src/components/PrivateRoute/index.jsx b/frontend/src/components/PrivateRoute/index.jsx new file mode 100644 index 0000000..1b4c71f --- /dev/null +++ b/frontend/src/components/PrivateRoute/index.jsx @@ -0,0 +1,141 @@ +import { useEffect, useState } from "react"; +import { Navigate } from "react-router-dom"; +import { FullScreenLoader } from "../Preloader"; +import validateSessionTokenForUser from "@/utils/session"; +import paths from "@/utils/paths"; +import { AUTH_TIMESTAMP, AUTH_TOKEN, AUTH_USER } from "@/utils/constants"; +import { userFromStorage } from "@/utils/request"; +import System from "@/models/system"; +import UserMenu from "../UserMenu"; + +// Used only for Multi-user mode only as we permission specific pages based on auth role. +// When in single user mode we just bypass any authchecks. +function useIsAuthenticated() { + const [isAuthd, setIsAuthed] = useState(null); + const [shouldRedirectToOnboarding, setShouldRedirectToOnboarding] = + useState(false); + const [multiUserMode, setMultiUserMode] = useState(false); + + useEffect(() => { + const validateSession = async () => { + const { + MultiUserMode, + RequiresAuth, + LLMProvider = null, + VectorDB = null, + } = await System.keys(); + + setMultiUserMode(MultiUserMode); + + // Check for the onboarding redirect condition + if ( + !MultiUserMode && + !RequiresAuth && // Not in Multi-user AND no password set. + !LLMProvider && + !VectorDB + ) { + setShouldRedirectToOnboarding(true); + setIsAuthed(true); + return; + } + + if (!MultiUserMode && !RequiresAuth) { + setIsAuthed(true); + return; + } + + // Single User password mode check + if (!MultiUserMode && RequiresAuth) { + const localAuthToken = localStorage.getItem(AUTH_TOKEN); + if (!localAuthToken) { + setIsAuthed(false); + return; + } + + const isValid = await validateSessionTokenForUser(); + setIsAuthed(isValid); + return; + } + + const localUser = localStorage.getItem(AUTH_USER); + const localAuthToken = localStorage.getItem(AUTH_TOKEN); + if (!localUser || !localAuthToken) { + setIsAuthed(false); + return; + } + + const isValid = await validateSessionTokenForUser(); + if (!isValid) { + localStorage.removeItem(AUTH_USER); + localStorage.removeItem(AUTH_TOKEN); + localStorage.removeItem(AUTH_TIMESTAMP); + setIsAuthed(false); + return; + } + + setIsAuthed(true); + }; + validateSession(); + }, []); + + return { isAuthd, shouldRedirectToOnboarding, multiUserMode }; +} + +// Allows only admin to access the route and if in single user mode, +// allows all users to access the route +export function AdminRoute({ Component }) { + const { isAuthd, shouldRedirectToOnboarding, multiUserMode } = + useIsAuthenticated(); + if (isAuthd === null) return ; + + if (shouldRedirectToOnboarding) { + return ; + } + + const user = userFromStorage(); + return isAuthd && (user?.role === "admin" || !multiUserMode) ? ( + + + + ) : ( + + ); +} + +// Allows manager and admin to access the route and if in single user mode, +// allows all users to access the route +export function ManagerRoute({ Component }) { + const { isAuthd, shouldRedirectToOnboarding, multiUserMode } = + useIsAuthenticated(); + if (isAuthd === null) return ; + + if (shouldRedirectToOnboarding) { + return ; + } + + const user = userFromStorage(); + return isAuthd && (user?.role !== "default" || !multiUserMode) ? ( + + + + ) : ( + + ); +} + +export default function PrivateRoute({ Component }) { + const { isAuthd, shouldRedirectToOnboarding } = useIsAuthenticated(); + if (isAuthd === null) return ; + + if (shouldRedirectToOnboarding) { + return ; + } + + return isAuthd ? ( + + + + ) : ( + + ); +} diff --git a/frontend/src/components/SettingsButton/index.jsx b/frontend/src/components/SettingsButton/index.jsx new file mode 100644 index 0000000..ac2d22c --- /dev/null +++ b/frontend/src/components/SettingsButton/index.jsx @@ -0,0 +1,33 @@ +import useUser from "@/hooks/useUser"; +import paths from "@/utils/paths"; +import { ArrowUUpLeft, Wrench } from "@phosphor-icons/react"; +import { Link } from "react-router-dom"; +import { useMatch } from "react-router-dom"; + +export default function SettingsButton() { + const isInSettings = !!useMatch("/settings/*"); + const { user } = useUser(); + + if (user && user?.role === "default") return null; + + if (isInSettings) + return ( + + + + ); + + return ( + + + + ); +} diff --git a/frontend/src/components/SettingsSidebar/index.jsx b/frontend/src/components/SettingsSidebar/index.jsx new file mode 100644 index 0000000..6b8f79e --- /dev/null +++ b/frontend/src/components/SettingsSidebar/index.jsx @@ -0,0 +1,376 @@ +import React, { useEffect, useRef, useState } from "react"; +import paths from "@/utils/paths"; +import useLogo from "@/hooks/useLogo"; +import { + EnvelopeSimple, + SquaresFour, + Users, + BookOpen, + ChatCenteredText, + Eye, + Key, + ChatText, + Database, + Lock, + House, + List, + FileCode, + Notepad, + CodeBlock, + Barcode, + ClosedCaptioning, + EyeSlash, + SplitVertical, + Microphone, +} from "@phosphor-icons/react"; +import useUser from "@/hooks/useUser"; +import { USER_BACKGROUND_COLOR } from "@/utils/constants"; +import { isMobile } from "react-device-detect"; +import Footer from "../Footer"; +import { Link } from "react-router-dom"; + +export default function SettingsSidebar() { + const { logo } = useLogo(); + const { user } = useUser(); + const sidebarRef = useRef(null); + const [showSidebar, setShowSidebar] = useState(false); + const [showBgOverlay, setShowBgOverlay] = useState(false); + + useEffect(() => { + function handleBg() { + if (showSidebar) { + setTimeout(() => { + setShowBgOverlay(true); + }, 300); + } else { + setShowBgOverlay(false); + } + } + handleBg(); + }, [showSidebar]); + + if (isMobile) { + return ( + <> +
+ +
+ Logo +
+
+
+
+
setShowSidebar(false)} + /> +
+
+ {/* Header Information */} +
+
+ Logo +
+
+ + + +
+
+ + {/* Primary Body */} +
+
+
+ +
+
+
+
+
+
+
+ + ); + } + + return ( +
+ + Logo + +
+
+
+ Instance Settings +
+
+
+
+ +
+
+
+
+
+
+
+
+
+ ); +} + +const Option = ({ + btnText, + icon, + href, + childLinks = [], + flex = false, + user = null, + allowedRole = [], + subOptions = null, + hidden = false, +}) => { + if (hidden) return null; + + const hasActiveChild = childLinks.includes(window.location.pathname); + const isActive = window.location.pathname === href; + + // Option only for multi-user + if (!flex && !allowedRole.includes(user?.role)) return null; + + // Option is dual-mode, but user exists, we need to check permissions + if (flex && !!user && !allowedRole.includes(user?.role)) return null; + + return ( + <> +
+ + {React.cloneElement(icon, { weight: isActive ? "fill" : "regular" })} +

+ {btnText} +

+ +
+ {!!subOptions && (isActive || hasActiveChild) && ( +
+ {subOptions} +
+ )} + + ); +}; + +const SidebarOptions = ({ user = null }) => ( + <> +

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