From 2440d96711b8d213d67147a515e448808c52daec Mon Sep 17 00:00:00 2001 From: Ke Xing <38187527+PeterXingke@users.noreply.github.com> Date: Sun, 4 Aug 2024 14:21:46 +0800 Subject: [PATCH 1/2] Add files via upload team xdlddw's submittion. --- Q2_main.log | 107 +++ Q2_result.png | Bin 0 -> 12156 bytes Q4_main.log | 644 ++++++++++++++++++ Q4_result.png | Bin 0 -> 1013403 bytes S2422-xdlddw-report.md | 127 ++++ compile_error.jpg | Bin 0 -> 21951 bytes compile_kmodel.py | 99 +++ llm_config.json | 15 + llm_export.py | 1432 ++++++++++++++++++++++++++++++++++++++++ 9 files changed, 2424 insertions(+) create mode 100644 Q2_main.log create mode 100644 Q2_result.png create mode 100644 Q4_main.log create mode 100644 Q4_result.png create mode 100644 S2422-xdlddw-report.md create mode 100644 compile_error.jpg create mode 100644 compile_kmodel.py create mode 100644 llm_config.json create mode 100644 llm_export.py diff --git a/Q2_main.log b/Q2_main.log new file mode 100644 index 0000000..f232c4f --- /dev/null +++ b/Q2_main.log @@ -0,0 +1,107 @@ +[1266] Log start +[1266] Cmd: ./llama-cli -m ggml-model-q2_k.gguf -p "I believe the meaning of life is" -n 128 +[1266] main: build = 3505 (b72c20b8) +[1266] main: built with riscv64-unknown-linux-gnu-gcc (Xuantie-900 linux-5.10.4 glibc gcc Toolchain V2.6.0 B-20220715) 10.2.0 for riscv64-unknown-linux-gnu +[1266] main: seed = 1266 +[1266] main: llama backend init +[1266] main: load the model and apply lora adapter, if any +[1266] llama_model_loader: loaded meta data with 23 key-value pairs and 291 tensors from ggml-model-q2_k.gguf (version GGUF V3 (latest)) +[1266] llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output. +[1266] llama_model_loader: - kv 0: general.architecture str = llama +[1266] llama_model_loader: - kv 1: general.name str = llama-3-chinese-instruct +[1266] llama_model_loader: - kv 2: llama.block_count u32 = 32 +[1266] llama_model_loader: - kv 3: llama.context_length u32 = 8192 +[1266] llama_model_loader: - kv 4: llama.embedding_length u32 = 4096 +[1266] llama_model_loader: - kv 5: llama.feed_forward_length u32 = 14336 +[1266] llama_model_loader: - kv 6: llama.attention.head_count u32 = 32 +[1266] llama_model_loader: - kv 7: llama.attention.head_count_kv u32 = 8 +[1266] llama_model_loader: - kv 8: llama.rope.freq_base f32 = 500000.000000 +[1266] llama_model_loader: - kv 9: llama.attention.layer_norm_rms_epsilon f32 = 0.000010 +[1266] llama_model_loader: - kv 10: general.file_type u32 = 10 +[1266] llama_model_loader: - kv 11: llama.vocab_size u32 = 128256 +[1266] llama_model_loader: - kv 12: llama.rope.dimension_count u32 = 128 +[1266] llama_model_loader: - kv 13: tokenizer.ggml.model str = gpt2 +[1266] llama_model_loader: - kv 14: tokenizer.ggml.pre str = llama-bpe +[1266] llama_model_loader: - kv 15: tokenizer.ggml.tokens arr[str,128256] = ["!", "\"", "#", "$", "%", "&", "'", ... +[1266] llama_model_loader: - kv 16: tokenizer.ggml.token_type arr[i32,128256] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ... +[1267] llama_model_loader: - kv 17: tokenizer.ggml.merges arr[str,280147] = ["Ġ Ġ", "Ġ ĠĠĠ", "ĠĠ ĠĠ", "... +[1267] llama_model_loader: - kv 18: tokenizer.ggml.bos_token_id u32 = 128000 +[1267] llama_model_loader: - kv 19: tokenizer.ggml.eos_token_id u32 = 128001 +[1267] llama_model_loader: - kv 20: tokenizer.ggml.padding_token_id u32 = 128001 +[1267] llama_model_loader: - kv 21: tokenizer.chat_template str = {% set loop_messages = messages %}{% ... +[1267] llama_model_loader: - kv 22: general.quantization_version u32 = 2 +[1267] llama_model_loader: - type f32: 65 tensors +[1267] llama_model_loader: - type q2_K: 129 tensors +[1267] llama_model_loader: - type q3_K: 64 tensors +[1267] llama_model_loader: - type q4_K: 32 tensors +[1267] llama_model_loader: - type q6_K: 1 tensors +[1272] llm_load_vocab: special tokens cache size = 256 +[1272] llm_load_vocab: token to piece cache size = 0.8000 MB +[1272] llm_load_print_meta: format = GGUF V3 (latest) +[1272] llm_load_print_meta: arch = llama +[1272] llm_load_print_meta: vocab type = BPE +[1272] llm_load_print_meta: n_vocab = 128256 +[1272] llm_load_print_meta: n_merges = 280147 +[1272] llm_load_print_meta: vocab_only = 0 +[1272] llm_load_print_meta: n_ctx_train = 8192 +[1272] llm_load_print_meta: n_embd = 4096 +[1272] llm_load_print_meta: n_layer = 32 +[1272] llm_load_print_meta: n_head = 32 +[1272] llm_load_print_meta: n_head_kv = 8 +[1272] llm_load_print_meta: n_rot = 128 +[1272] llm_load_print_meta: n_swa = 0 +[1272] llm_load_print_meta: n_embd_head_k = 128 +[1272] llm_load_print_meta: n_embd_head_v = 128 +[1272] llm_load_print_meta: n_gqa = 4 +[1272] llm_load_print_meta: n_embd_k_gqa = 1024 +[1272] llm_load_print_meta: n_embd_v_gqa = 1024 +[1272] llm_load_print_meta: f_norm_eps = 0.0e+00 +[1272] llm_load_print_meta: f_norm_rms_eps = 1.0e-05 +[1272] llm_load_print_meta: f_clamp_kqv = 0.0e+00 +[1272] llm_load_print_meta: f_max_alibi_bias = 0.0e+00 +[1272] llm_load_print_meta: f_logit_scale = 0.0e+00 +[1272] llm_load_print_meta: n_ff = 14336 +[1272] llm_load_print_meta: n_expert = 0 +[1272] llm_load_print_meta: n_expert_used = 0 +[1272] llm_load_print_meta: causal attn = 1 +[1272] llm_load_print_meta: pooling type = 0 +[1272] llm_load_print_meta: rope type = 0 +[1272] llm_load_print_meta: rope scaling = linear +[1272] llm_load_print_meta: freq_base_train = 500000.0 +[1272] llm_load_print_meta: freq_scale_train = 1 +[1272] llm_load_print_meta: n_ctx_orig_yarn = 8192 +[1272] llm_load_print_meta: rope_finetuned = unknown +[1272] llm_load_print_meta: ssm_d_conv = 0 +[1272] llm_load_print_meta: ssm_d_inner = 0 +[1272] llm_load_print_meta: ssm_d_state = 0 +[1272] llm_load_print_meta: ssm_dt_rank = 0 +[1272] llm_load_print_meta: model type = 8B +[1272] llm_load_print_meta: model ftype = Q2_K - Medium +[1272] llm_load_print_meta: model params = 8.03 B +[1272] llm_load_print_meta: model size = 2.95 GiB (3.16 BPW) +[1272] llm_load_print_meta: general.name = llama-3-chinese-instruct +[1272] llm_load_print_meta: BOS token = 128000 '<|begin_of_text|>' +[1272] llm_load_print_meta: EOS token = 128001 '<|end_of_text|>' +[1272] llm_load_print_meta: PAD token = 128001 '<|end_of_text|>' +[1272] llm_load_print_meta: LF token = 128 'Ä' +[1272] llm_load_print_meta: EOT token = 128009 '<|eot_id|>' +[1272] llm_load_print_meta: max token length = 256 +[1272] llm_load_tensors: ggml ctx size = 0.14 MiB +[1409] llm_load_tensors: CPU buffer size = 3024.38 MiB +[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] .[1409] +[1411] llama_new_context_with_model: n_ctx = 8192 +[1411] llama_new_context_with_model: n_batch = 2048 +[1411] llama_new_context_with_model: n_ubatch = 512 +[1411] llama_new_context_with_model: flash_attn = 0 +[1411] llama_new_context_with_model: freq_base = 500000.0 +[1411] llama_new_context_with_model: freq_scale = 1 +[1471] llama_kv_cache_init: CPU KV buffer size = 1024.00 MiB +[1471] llama_new_context_with_model: KV self size = 1024.00 MiB, K (f16): 512.00 MiB, V (f16): 512.00 MiB +[1471] llama_new_context_with_model: CPU output buffer size = 0.49 MiB +[1472] llama_new_context_with_model: CPU compute buffer size = 560.01 MiB +[1472] llama_new_context_with_model: graph nodes = 1030 +[1472] llama_new_context_with_model: graph splits = 1 +[1472] warming up the model with an empty run +[1851] n_ctx: 8192 +[1851] +[1851] system_info: n_threads = 1 / 1 | AVX = 0 | AVX_VNNI = 0 | AVX2 = 0 | AVX512 = 0 | AVX512_VBMI = 0 | AVX512_VNNI = 0 | AVX512_BF16 = 0 | FMA = 0 | NEON = 0 | SVE = 0 | ARM_FMA = 0 | F16C = 0 | FP16_VA = 0 | WASM_SIMD = 0 | BLAS = 0 | SSE3 = 0 | SSSE3 = 0 | VSX = 0 \ No newline at end of file diff --git a/Q2_result.png b/Q2_result.png new file mode 100644 index 0000000000000000000000000000000000000000..0ed20cf1aecb208b71db9b9de6fded03109439f9 GIT binary patch literal 12156 zcmb`NcT^MG+wZX;DheV>k*0t|rR$L@iCCxtVgn2iIwB=1O(X>o3sRy~J(MV*sDShi ziBb&+p|=200)!SYKp=fC=07!wfoMrjQMJcTH%w>Bk+STvEwTBImtl@*6*K| 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gcc Toolchain V2.6.0 B-20220715) 10.2.0 for riscv64-unknown-linux-gnu +[1953] main: seed = 1953 +[1953] main: llama backend init +[1953] main: load the model and apply lora adapter, if any +[1953] llama_model_loader: loaded meta data with 28 key-value pairs and 264 tensors from Llama-3-7B.Q4_K_S.gguf (version GGUF V3 (latest)) +[1953] llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output. +[1953] llama_model_loader: - kv 0: general.architecture str = llama +[1953] llama_model_loader: - kv 1: general.name str = Meta-Llama-3-7B-29Layers +[1953] llama_model_loader: - kv 2: llama.block_count u32 = 29 +[1953] llama_model_loader: - kv 3: llama.context_length u32 = 8192 +[1953] llama_model_loader: - kv 4: llama.embedding_length u32 = 4096 +[1953] llama_model_loader: - kv 5: llama.feed_forward_length u32 = 14336 +[1953] llama_model_loader: - kv 6: llama.attention.head_count u32 = 32 +[1953] llama_model_loader: - kv 7: llama.attention.head_count_kv u32 = 8 +[1953] llama_model_loader: - kv 8: llama.rope.freq_base f32 = 500000.000000 +[1953] llama_model_loader: - kv 9: llama.attention.layer_norm_rms_epsilon f32 = 0.000010 +[1953] llama_model_loader: - kv 10: general.file_type u32 = 14 +[1953] llama_model_loader: - kv 11: llama.vocab_size u32 = 128256 +[1953] llama_model_loader: - kv 12: llama.rope.dimension_count u32 = 128 +[1953] llama_model_loader: - kv 13: tokenizer.ggml.model str = gpt2 +[1953] llama_model_loader: - kv 14: tokenizer.ggml.pre str = llama-bpe +[1953] llama_model_loader: - kv 15: tokenizer.ggml.tokens arr[str,128256] = ["!", "\"", "#", "$", "%", "&", "'", ... +[1953] llama_model_loader: - kv 16: tokenizer.ggml.token_type arr[i32,128256] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ... +[1954] llama_model_loader: - kv 17: tokenizer.ggml.merges arr[str,280147] = ["Ġ Ġ", "Ġ ĠĠĠ", "ĠĠ ĠĠ", "... +[1954] llama_model_loader: - kv 18: tokenizer.ggml.bos_token_id u32 = 128000 +[1954] llama_model_loader: - kv 19: tokenizer.ggml.eos_token_id u32 = 128001 +[1954] llama_model_loader: - kv 20: general.quantization_version u32 = 2 +[1954] llama_model_loader: - kv 21: general.url str = https://huggingface.co/mradermacher/M... +[1954] llama_model_loader: - kv 22: mradermacher.quantize_version str = 2 +[1954] llama_model_loader: - kv 23: mradermacher.quantized_by str = mradermacher +[1954] llama_model_loader: - kv 24: mradermacher.quantized_at str = 2024-05-14T23:38:07+02:00 +[1954] llama_model_loader: - kv 25: mradermacher.quantized_on str = db2 +[1954] llama_model_loader: - kv 26: general.source.url str = https://huggingface.co/aloobun/Meta-L... +[1954] llama_model_loader: - kv 27: mradermacher.convert_type str = hf +[1954] llama_model_loader: - type f32: 59 tensors +[1954] llama_model_loader: - type q4_K: 197 tensors +[1954] llama_model_loader: - type q5_K: 7 tensors +[1954] llama_model_loader: - type q6_K: 1 tensors +[1956] llm_load_vocab: special tokens cache size = 256 +[1956] llm_load_vocab: token to piece cache size = 0.8000 MB +[1956] llm_load_print_meta: format = GGUF V3 (latest) +[1956] llm_load_print_meta: arch = llama +[1956] llm_load_print_meta: vocab type = BPE +[1956] llm_load_print_meta: n_vocab = 128256 +[1956] llm_load_print_meta: n_merges = 280147 +[1956] llm_load_print_meta: vocab_only = 0 +[1956] llm_load_print_meta: n_ctx_train = 8192 +[1956] llm_load_print_meta: n_embd = 4096 +[1956] llm_load_print_meta: n_layer = 29 +[1956] llm_load_print_meta: n_head = 32 +[1956] llm_load_print_meta: n_head_kv = 8 +[1956] llm_load_print_meta: n_rot = 128 +[1956] llm_load_print_meta: n_swa = 0 +[1956] llm_load_print_meta: n_embd_head_k = 128 +[1956] llm_load_print_meta: n_embd_head_v = 128 +[1956] llm_load_print_meta: n_gqa = 4 +[1956] llm_load_print_meta: n_embd_k_gqa = 1024 +[1956] llm_load_print_meta: n_embd_v_gqa = 1024 +[1956] llm_load_print_meta: f_norm_eps = 0.0e+00 +[1956] llm_load_print_meta: f_norm_rms_eps = 1.0e-05 +[1956] llm_load_print_meta: f_clamp_kqv = 0.0e+00 +[1956] llm_load_print_meta: f_max_alibi_bias = 0.0e+00 +[1956] llm_load_print_meta: f_logit_scale = 0.0e+00 +[1956] llm_load_print_meta: n_ff = 14336 +[1956] llm_load_print_meta: n_expert = 0 +[1956] llm_load_print_meta: n_expert_used = 0 +[1956] llm_load_print_meta: causal attn = 1 +[1956] llm_load_print_meta: pooling type = 0 +[1956] llm_load_print_meta: rope type = 0 +[1956] llm_load_print_meta: rope scaling = linear +[1956] llm_load_print_meta: freq_base_train = 500000.0 +[1956] llm_load_print_meta: freq_scale_train = 1 +[1956] llm_load_print_meta: n_ctx_orig_yarn = 8192 +[1956] llm_load_print_meta: rope_finetuned = unknown +[1956] llm_load_print_meta: ssm_d_conv = 0 +[1956] llm_load_print_meta: ssm_d_inner = 0 +[1956] llm_load_print_meta: ssm_d_state = 0 +[1956] llm_load_print_meta: ssm_dt_rank = 0 +[1956] llm_load_print_meta: model type = ?B +[1956] llm_load_print_meta: model ftype = Q4_K - Small +[1956] llm_load_print_meta: model params = 7.38 B +[1956] llm_load_print_meta: model size = 4.01 GiB (4.67 BPW) +[1956] llm_load_print_meta: general.name = Meta-Llama-3-7B-29Layers +[1956] llm_load_print_meta: BOS token = 128000 '<|begin_of_text|>' +[1956] llm_load_print_meta: EOS token = 128001 '<|end_of_text|>' +[1956] llm_load_print_meta: LF token = 128 'Ä' +[1956] llm_load_print_meta: EOT token = 128009 '<|eot_id|>' +[1956] llm_load_print_meta: max token length = 256 +[1956] llm_load_tensors: ggml ctx size = 0.12 MiB +[2142] llm_load_tensors: CPU buffer size = 4109.71 MiB +[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] .[2142] +[2144] llama_new_context_with_model: n_ctx = 8192 +[2144] llama_new_context_with_model: n_batch = 2048 +[2144] llama_new_context_with_model: n_ubatch = 512 +[2144] llama_new_context_with_model: flash_attn = 0 +[2144] llama_new_context_with_model: freq_base = 500000.0 +[2144] llama_new_context_with_model: freq_scale = 1 +[2175] llama_kv_cache_init: CPU KV buffer size = 928.00 MiB +[2175] llama_new_context_with_model: KV self size = 928.00 MiB, K (f16): 464.00 MiB, V (f16): 464.00 MiB +[2175] llama_new_context_with_model: CPU output buffer size = 0.49 MiB +[2175] llama_new_context_with_model: CPU compute buffer size = 560.01 MiB +[2175] llama_new_context_with_model: graph nodes = 934 +[2175] llama_new_context_with_model: graph splits = 1 +[2175] warming up the model with an empty run +[2469] n_ctx: 8192 +[2469] +[2469] system_info: n_threads = 1 / 1 | AVX = 0 | AVX_VNNI = 0 | AVX2 = 0 | AVX512 = 0 | AVX512_VBMI = 0 | AVX512_VNNI = 0 | AVX512_BF16 = 0 | FMA = 0 | NEON = 0 | SVE = 0 | ARM_FMA = 0 | F16C = 0 | FP16_VA = 0 | WASM_SIMD = 0 | BLAS = 0 | SSE3 = 0 | SSSE3 = 0 | VSX = 0 | MATMUL_INT8 = 0 | LLAMAFILE = 1 | +[2469] add_bos: 1 +[2469] tokenize the prompt +[2469] prompt: "I believe the meaning of life is" +[2469] tokens: [ '<|begin_of_text|>':128000, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374 ] +[2469] recalculate the cached logits (check): embd_inp.empty() false, n_matching_session_tokens 0, embd_inp.size() 8, session_tokens.size() 0, embd_inp.size() 8 +[2469] sampling: + repeat_last_n = 64, repeat_penalty = 1.000, frequency_penalty = 0.000, presence_penalty = 0.000 + top_k = 40, tfs_z = 1.000, top_p = 0.950, min_p = 0.050, typical_p = 1.000, temp = 0.800 + mirostat = 0, mirostat_lr = 0.100, mirostat_ent = 5.000 +[2469] sampling order: +CFG -> Penalties -> top_k -> tfs_z -> typical_p -> top_p -> min_p -> temperature +[2469] generate: n_ctx = 8192, n_batch = 2048, n_predict = 128, n_keep = 1 +[2469] + +[2469] embd_inp.size(): 8, n_consumed: 0 +[2469] eval: [ '<|begin_of_text|>':128000, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374 ] +[2892] n_past = 8 +[2892] last: [ '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '<|begin_of_text|>':128000, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' to':311 ] +[2892] n_remain: 127 +[2892] eval: [ ' to':311 ] +[3066] n_past = 9 +[3066] last: [ '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '<|begin_of_text|>':128000, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' to':311, ' love':3021 ] +[3066] n_remain: 126 +[3066] eval: [ ' love':3021 ] +[3239] n_past = 10 +[3239] last: [ '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '<|begin_of_text|>':128000, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' to':311, ' love':3021, ' the':279 ] +[3239] n_remain: 125 +[3239] eval: [ ' the':279 ] +[3412] n_past = 11 +[3412] last: [ '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '<|begin_of_text|>':128000, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' to':311, ' love':3021, ' the':279, ' universe':15861 ] +[3412] n_remain: 124 +[3412] eval: [ ' universe':15861 ] +[3584] n_past = 12 +[3584] last: [ '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '<|begin_of_text|>':128000, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' to':311, ' love':3021, ' the':279, ' universe':15861, ' and':323 ] +[3584] n_remain: 123 +[3584] eval: [ ' and':323 ] +[3755] n_past = 13 +[3755] last: [ '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '<|begin_of_text|>':128000, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' to':311, ' love':3021, ' the':279, ' universe':15861, ' and':323, ' everything':4395 ] +[3755] n_remain: 122 +[3755] eval: [ ' everything':4395 ] +[3925] n_past = 14 +[3925] last: [ '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '<|begin_of_text|>':128000, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' to':311, ' love':3021, ' the':279, ' universe':15861, ' and':323, ' everything':4395, ' in':304 ] +[3925] n_remain: 121 +[3925] eval: [ ' in':304 ] +[4096] n_past = 15 +[4096] last: [ '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '<|begin_of_text|>':128000, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' to':311, ' love':3021, ' the':279, ' universe':15861, ' and':323, ' everything':4395, ' in':304, ' it':433 ] +[4096] n_remain: 120 +[4096] eval: [ ' it':433 ] +[4267] n_past = 16 +[4267] last: [ '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '<|begin_of_text|>':128000, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' to':311, ' love':3021, ' the':279, ' universe':15861, ' and':323, ' everything':4395, ' in':304, ' it':433, '.':627 ] +[4267] n_remain: 119 +[4267] eval: [ '.':627 ] +[4437] n_past = 17 +[4437] last: [ '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '<|begin_of_text|>':128000, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' to':311, ' love':3021, ' the':279, ' universe':15861, ' and':323, ' everything':4395, ' in':304, ' it':433, '.':627, 'There':3947 ] +[4437] n_remain: 118 +[4437] eval: [ 'There':3947 ] +[4607] n_past = 18 +[4607] last: [ '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '<|begin_of_text|>':128000, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' to':311, ' love':3021, ' the':279, ' universe':15861, ' and':323, ' everything':4395, ' in':304, ' it':433, '.':627, 'There':3947, ' are':527 ] +[4607] n_remain: 117 +[4607] eval: [ ' are':527 ] +[4777] n_past = 19 +[4777] last: [ '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '<|begin_of_text|>':128000, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' to':311, ' love':3021, ' the':279, ' universe':15861, ' and':323, ' everything':4395, ' in':304, ' it':433, '.':627, 'There':3947, ' are':527, ' many':1690 ] +[4777] n_remain: 116 +[4777] eval: [ ' many':1690 ] +[4948] n_past = 20 +[4948] last: [ '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '<|begin_of_text|>':128000, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' to':311, ' love':3021, ' the':279, ' universe':15861, ' and':323, ' everything':4395, ' in':304, ' it':433, '.':627, 'There':3947, ' are':527, ' many':1690, ' ways':5627 ] +[4948] n_remain: 115 +[4948] eval: [ ' ways':5627 ] +[5118] n_past = 21 +[5118] last: [ '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '<|begin_of_text|>':128000, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' to':311, ' love':3021, ' the':279, ' universe':15861, ' and':323, ' everything':4395, ' in':304, ' it':433, '.':627, 'There':3947, ' are':527, ' many':1690, ' ways':5627, ' to':311 ] +[5118] n_remain: 114 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spiritual':18330, ' way':1648, ' and':323, ' the':279, ' artistic':32692, ' way':1648, '.':13, ' In':763, ' my':856, ' life':2324, ' I':358, ' have':617, ' been':1027, ' drawn':15107, ' to':311, ' the':279, ' scientific':12624, ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648 ] +[11595] n_remain: 76 +[11595] eval: [ ' way':1648 ] +[11765] n_past = 60 +[11765] last: [ '!':0, '!':0, '!':0, '<|begin_of_text|>':128000, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' to':311, ' love':3021, ' the':279, ' universe':15861, ' and':323, ' everything':4395, ' in':304, ' it':433, '.':627, 'There':3947, ' are':527, ' many':1690, ' ways':5627, ' to':311, ' do':656, ' this':420, '.':13, ' There':2684, ' is':374, ' the':279, ' scientific':12624, ' way':1648, ',':11, ' the':279, ' human':3823, 'ist':380, ' way':1648, ',':11, ' the':279, ' spiritual':18330, ' way':1648, ' and':323, ' the':279, ' artistic':32692, ' way':1648, '.':13, ' In':763, ' my':856, ' life':2324, ' I':358, ' have':617, ' been':1027, ' drawn':15107, ' to':311, ' the':279, ' scientific':12624, ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279 ] +[11765] n_remain: 75 +[11765] eval: [ ' the':279 ] +[11936] n_past = 61 +[11936] last: [ '!':0, '!':0, '<|begin_of_text|>':128000, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' to':311, ' love':3021, ' the':279, ' universe':15861, ' and':323, ' everything':4395, ' in':304, ' it':433, '.':627, 'There':3947, ' are':527, ' many':1690, ' ways':5627, ' to':311, ' do':656, ' this':420, '.':13, ' There':2684, ' is':374, ' the':279, ' scientific':12624, ' way':1648, ',':11, ' the':279, ' human':3823, 'ist':380, ' way':1648, ',':11, ' the':279, ' spiritual':18330, ' way':1648, ' and':323, ' the':279, ' artistic':32692, ' way':1648, '.':13, ' In':763, ' my':856, ' life':2324, ' I':358, ' have':617, ' been':1027, ' drawn':15107, ' to':311, ' the':279, ' scientific':12624, ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455 ] +[11936] n_remain: 74 +[11936] eval: [ ' most':1455 ] +[12106] n_past = 62 +[12106] last: [ '!':0, '<|begin_of_text|>':128000, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' to':311, ' love':3021, ' the':279, ' universe':15861, ' and':323, ' everything':4395, ' in':304, ' it':433, '.':627, 'There':3947, ' are':527, ' many':1690, ' ways':5627, ' to':311, ' do':656, ' this':420, '.':13, ' There':2684, ' is':374, ' the':279, ' scientific':12624, ' way':1648, ',':11, ' the':279, ' human':3823, 'ist':380, ' way':1648, ',':11, ' the':279, ' spiritual':18330, ' way':1648, ' and':323, ' the':279, ' artistic':32692, ' way':1648, '.':13, ' In':763, ' my':856, ' life':2324, ' I':358, ' have':617, ' been':1027, ' drawn':15107, ' to':311, ' the':279, ' scientific':12624, ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11 ] +[12106] n_remain: 73 +[12106] eval: [ ',':11 ] +[12277] n_past = 63 +[12277] last: [ '<|begin_of_text|>':128000, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' to':311, ' love':3021, ' the':279, ' universe':15861, ' and':323, ' everything':4395, ' in':304, ' it':433, '.':627, 'There':3947, ' are':527, ' many':1690, ' ways':5627, ' to':311, ' do':656, ' this':420, '.':13, ' There':2684, ' is':374, ' the':279, ' scientific':12624, ' way':1648, ',':11, ' the':279, ' human':3823, 'ist':380, ' way':1648, ',':11, ' the':279, ' spiritual':18330, ' way':1648, ' and':323, ' the':279, ' artistic':32692, ' way':1648, '.':13, ' In':763, ' my':856, ' life':2324, ' I':358, ' have':617, ' been':1027, ' drawn':15107, ' to':311, ' the':279, ' scientific':12624, ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051 ] +[12277] n_remain: 72 +[12277] eval: [ ' although':8051 ] +[12447] n_past = 64 +[12447] last: [ 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' to':311, ' love':3021, ' the':279, ' universe':15861, ' and':323, ' everything':4395, ' in':304, ' it':433, '.':627, 'There':3947, ' are':527, ' many':1690, ' ways':5627, ' to':311, ' do':656, ' this':420, '.':13, ' There':2684, ' is':374, ' the':279, ' scientific':12624, ' way':1648, ',':11, ' the':279, ' human':3823, 'ist':380, ' way':1648, ',':11, ' the':279, ' spiritual':18330, ' way':1648, ' and':323, ' the':279, ' artistic':32692, ' way':1648, '.':13, ' In':763, ' my':856, ' life':2324, ' I':358, ' have':617, ' been':1027, ' drawn':15107, ' to':311, ' the':279, ' scientific':12624, ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358 ] +[12447] n_remain: 71 +[12447] eval: [ ' I':358 ] +[12618] n_past = 65 +[12618] last: [ ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' to':311, ' love':3021, ' the':279, ' universe':15861, ' and':323, ' everything':4395, ' in':304, ' it':433, '.':627, 'There':3947, ' are':527, ' many':1690, ' ways':5627, ' to':311, ' do':656, ' this':420, '.':13, ' There':2684, ' is':374, ' the':279, ' scientific':12624, ' way':1648, ',':11, ' the':279, ' human':3823, 'ist':380, ' way':1648, ',':11, ' the':279, ' spiritual':18330, ' way':1648, ' and':323, ' the':279, ' artistic':32692, ' way':1648, '.':13, ' In':763, ' my':856, ' life':2324, ' I':358, ' have':617, ' been':1027, ' drawn':15107, ' to':311, ' the':279, ' scientific':12624, ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617 ] +[12618] n_remain: 70 +[12618] eval: [ ' have':617 ] +[12788] n_past = 66 +[12788] last: [ ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' to':311, ' love':3021, ' the':279, ' universe':15861, ' and':323, ' everything':4395, ' in':304, ' it':433, '.':627, 'There':3947, ' are':527, ' many':1690, ' ways':5627, ' to':311, ' do':656, ' this':420, '.':13, ' There':2684, ' is':374, ' the':279, ' scientific':12624, ' way':1648, ',':11, ' the':279, ' human':3823, 'ist':380, ' way':1648, ',':11, ' the':279, ' spiritual':18330, ' way':1648, ' and':323, ' the':279, ' artistic':32692, ' way':1648, '.':13, ' In':763, ' my':856, ' life':2324, ' I':358, ' have':617, ' been':1027, ' drawn':15107, ' to':311, ' the':279, ' scientific':12624, ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101 ] +[12788] n_remain: 69 +[12788] eval: [ ' also':1101 ] +[12959] n_past = 67 +[12959] last: [ ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' to':311, ' love':3021, ' the':279, ' universe':15861, ' and':323, ' everything':4395, ' in':304, ' it':433, '.':627, 'There':3947, ' are':527, ' many':1690, ' ways':5627, ' to':311, ' do':656, ' this':420, '.':13, ' There':2684, ' is':374, ' the':279, ' scientific':12624, ' way':1648, ',':11, ' the':279, ' human':3823, 'ist':380, ' way':1648, ',':11, ' the':279, ' spiritual':18330, ' way':1648, ' and':323, ' the':279, ' artistic':32692, ' way':1648, '.':13, ' In':763, ' my':856, ' life':2324, ' I':358, ' have':617, ' been':1027, ' drawn':15107, ' to':311, ' the':279, ' scientific':12624, ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027 ] +[12959] n_remain: 68 +[12959] eval: [ ' been':1027 ] +[13130] n_past = 68 +[13130] last: [ ' of':315, ' life':2324, ' is':374, ' to':311, ' love':3021, ' the':279, ' universe':15861, ' and':323, ' everything':4395, ' in':304, ' it':433, '.':627, 'There':3947, ' are':527, ' many':1690, ' ways':5627, ' to':311, ' do':656, ' this':420, '.':13, ' There':2684, ' is':374, ' the':279, ' scientific':12624, ' way':1648, ',':11, ' the':279, ' human':3823, 'ist':380, ' way':1648, ',':11, ' the':279, ' spiritual':18330, ' way':1648, ' and':323, ' the':279, ' artistic':32692, ' way':1648, '.':13, ' In':763, ' my':856, ' life':2324, ' I':358, ' have':617, ' been':1027, ' drawn':15107, ' to':311, ' the':279, ' scientific':12624, ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173 ] +[13130] n_remain: 67 +[13130] eval: [ ' interested':8173 ] +[13300] n_past = 69 +[13300] last: [ ' life':2324, ' is':374, ' to':311, ' love':3021, ' the':279, ' universe':15861, ' and':323, ' everything':4395, ' in':304, ' it':433, '.':627, 'There':3947, ' are':527, ' many':1690, ' ways':5627, ' to':311, ' do':656, ' this':420, '.':13, ' There':2684, ' is':374, ' the':279, ' scientific':12624, ' way':1648, ',':11, ' the':279, ' human':3823, 'ist':380, ' way':1648, ',':11, ' the':279, ' spiritual':18330, ' way':1648, ' and':323, ' the':279, ' artistic':32692, ' way':1648, '.':13, ' In':763, ' my':856, ' life':2324, ' I':358, ' have':617, ' been':1027, ' drawn':15107, ' to':311, ' the':279, ' scientific':12624, ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304 ] +[13300] n_remain: 66 +[13300] eval: [ ' in':304 ] +[13471] n_past = 70 +[13471] last: [ ' is':374, ' to':311, ' love':3021, ' the':279, ' universe':15861, ' and':323, ' everything':4395, ' in':304, ' it':433, '.':627, 'There':3947, ' are':527, ' many':1690, ' ways':5627, ' to':311, ' do':656, ' this':420, '.':13, ' There':2684, ' is':374, ' the':279, ' scientific':12624, ' way':1648, ',':11, ' the':279, ' human':3823, 'ist':380, ' way':1648, ',':11, ' the':279, ' spiritual':18330, ' way':1648, ' and':323, ' the':279, ' artistic':32692, ' way':1648, '.':13, ' In':763, ' my':856, ' life':2324, ' I':358, ' have':617, ' been':1027, ' drawn':15107, ' to':311, ' the':279, ' scientific':12624, ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279 ] +[13471] n_remain: 65 +[13471] eval: [ ' the':279 ] +[13641] n_past = 71 +[13641] last: [ ' to':311, ' love':3021, ' the':279, ' universe':15861, ' and':323, ' everything':4395, ' in':304, ' it':433, '.':627, 'There':3947, ' are':527, ' many':1690, ' ways':5627, ' to':311, ' do':656, ' this':420, '.':13, ' There':2684, ' is':374, ' the':279, ' scientific':12624, ' way':1648, ',':11, ' the':279, ' human':3823, 'ist':380, ' way':1648, ',':11, ' the':279, ' spiritual':18330, ' way':1648, ' and':323, ' the':279, ' artistic':32692, ' way':1648, '.':13, ' In':763, ' my':856, ' life':2324, ' I':358, ' have':617, ' been':1027, ' drawn':15107, ' to':311, ' the':279, ' scientific':12624, ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330 ] +[13641] n_remain: 64 +[13641] eval: [ ' spiritual':18330 ] +[13812] n_past = 72 +[13812] last: [ ' love':3021, ' the':279, ' universe':15861, ' and':323, ' everything':4395, ' in':304, ' it':433, '.':627, 'There':3947, ' are':527, ' many':1690, ' ways':5627, ' to':311, ' do':656, ' this':420, '.':13, ' There':2684, ' is':374, ' the':279, ' scientific':12624, ' way':1648, ',':11, ' the':279, ' human':3823, 'ist':380, ' way':1648, ',':11, ' the':279, ' spiritual':18330, ' way':1648, ' and':323, ' the':279, ' artistic':32692, ' way':1648, '.':13, ' In':763, ' my':856, ' life':2324, ' I':358, ' have':617, ' been':1027, ' drawn':15107, ' to':311, ' the':279, ' scientific':12624, ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323 ] +[13812] n_remain: 63 +[13812] eval: [ ' and':323 ] +[13983] n_past = 73 +[13983] last: [ ' the':279, ' universe':15861, ' and':323, ' everything':4395, ' in':304, ' it':433, '.':627, 'There':3947, ' are':527, ' many':1690, ' ways':5627, ' to':311, ' do':656, ' this':420, '.':13, ' There':2684, ' is':374, ' the':279, ' scientific':12624, ' way':1648, ',':11, ' the':279, ' human':3823, 'ist':380, ' way':1648, ',':11, ' the':279, ' spiritual':18330, ' way':1648, ' and':323, ' the':279, ' artistic':32692, ' way':1648, '.':13, ' In':763, ' my':856, ' life':2324, ' I':358, ' have':617, ' been':1027, ' drawn':15107, ' to':311, ' the':279, ' scientific':12624, ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692 ] +[13983] n_remain: 62 +[13983] eval: [ ' artistic':32692 ] +[14153] n_past = 74 +[14153] last: [ ' universe':15861, ' and':323, ' everything':4395, ' in':304, ' it':433, '.':627, 'There':3947, ' are':527, ' many':1690, ' ways':5627, ' to':311, ' do':656, ' this':420, '.':13, ' There':2684, ' is':374, ' the':279, ' scientific':12624, ' way':1648, ',':11, ' the':279, ' human':3823, 'ist':380, ' way':1648, ',':11, ' the':279, ' spiritual':18330, ' way':1648, ' and':323, ' the':279, ' artistic':32692, ' way':1648, '.':13, ' In':763, ' my':856, ' life':2324, ' I':358, ' have':617, ' been':1027, ' drawn':15107, ' to':311, ' the':279, ' scientific':12624, ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648 ] +[14153] n_remain: 61 +[14153] eval: [ ' way':1648 ] +[14324] n_past = 75 +[14324] last: [ ' and':323, ' everything':4395, ' in':304, ' it':433, '.':627, 'There':3947, ' are':527, ' many':1690, ' ways':5627, ' to':311, ' do':656, ' this':420, '.':13, ' There':2684, ' is':374, ' the':279, ' scientific':12624, ' way':1648, ',':11, ' the':279, ' human':3823, 'ist':380, ' way':1648, ',':11, ' the':279, ' spiritual':18330, ' way':1648, ' and':323, ' the':279, ' artistic':32692, ' way':1648, '.':13, ' In':763, ' my':856, ' life':2324, ' I':358, ' have':617, ' been':1027, ' drawn':15107, ' to':311, ' the':279, ' scientific':12624, ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627 ] +[14324] n_remain: 60 +[14324] eval: [ '.':627 ] +[14494] n_past = 76 +[14494] last: [ ' everything':4395, ' in':304, ' it':433, '.':627, 'There':3947, ' are':527, ' many':1690, ' ways':5627, ' to':311, ' do':656, ' this':420, '.':13, ' There':2684, ' is':374, ' the':279, ' scientific':12624, ' way':1648, ',':11, ' the':279, ' human':3823, 'ist':380, ' way':1648, ',':11, ' the':279, ' spiritual':18330, ' way':1648, ' and':323, ' the':279, ' artistic':32692, ' way':1648, '.':13, ' In':763, ' my':856, ' life':2324, ' I':358, ' have':617, ' been':1027, ' drawn':15107, ' to':311, ' the':279, ' scientific':12624, ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791 ] +[14494] n_remain: 59 +[14494] eval: [ 'The':791 ] +[14665] n_past = 77 +[14665] last: [ ' in':304, ' it':433, '.':627, 'There':3947, ' are':527, ' many':1690, ' ways':5627, ' to':311, ' do':656, ' this':420, '.':13, ' There':2684, ' is':374, ' the':279, ' scientific':12624, ' way':1648, ',':11, ' the':279, ' human':3823, 'ist':380, ' way':1648, ',':11, ' the':279, ' spiritual':18330, ' way':1648, ' and':323, ' the':279, ' artistic':32692, ' way':1648, '.':13, ' In':763, ' my':856, ' life':2324, ' I':358, ' have':617, ' been':1027, ' drawn':15107, ' to':311, ' the':279, ' scientific':12624, ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624 ] +[14665] n_remain: 58 +[14665] eval: [ ' scientific':12624 ] +[14836] n_past = 78 +[14836] last: [ ' it':433, '.':627, 'There':3947, ' are':527, ' many':1690, ' ways':5627, ' to':311, ' do':656, ' this':420, '.':13, ' There':2684, ' is':374, ' the':279, ' scientific':12624, ' way':1648, ',':11, ' the':279, ' human':3823, 'ist':380, ' way':1648, ',':11, ' the':279, ' spiritual':18330, ' way':1648, ' and':323, ' the':279, ' artistic':32692, ' way':1648, '.':13, ' In':763, ' my':856, ' life':2324, ' I':358, ' have':617, ' been':1027, ' drawn':15107, ' to':311, ' the':279, ' scientific':12624, ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624, ' way':1648 ] +[14836] n_remain: 57 +[14836] eval: [ ' way':1648 ] +[15007] n_past = 79 +[15007] last: [ '.':627, 'There':3947, ' are':527, ' many':1690, ' ways':5627, ' to':311, ' do':656, ' this':420, '.':13, ' There':2684, ' is':374, ' the':279, ' scientific':12624, ' way':1648, ',':11, ' the':279, ' human':3823, 'ist':380, ' way':1648, ',':11, ' the':279, ' spiritual':18330, ' way':1648, ' and':323, ' the':279, ' artistic':32692, ' way':1648, '.':13, ' In':763, ' my':856, ' life':2324, ' I':358, ' have':617, ' been':1027, ' drawn':15107, ' to':311, ' the':279, ' scientific':12624, ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624, ' way':1648, ',':11 ] +[15007] n_remain: 56 +[15007] eval: [ ',':11 ] +[15178] n_past = 80 +[15178] last: [ 'There':3947, ' are':527, ' many':1690, ' ways':5627, ' to':311, ' do':656, ' this':420, '.':13, ' There':2684, ' is':374, ' the':279, ' scientific':12624, ' way':1648, ',':11, ' the':279, ' human':3823, 'ist':380, ' way':1648, ',':11, ' the':279, ' spiritual':18330, ' way':1648, ' and':323, ' the':279, ' artistic':32692, ' way':1648, '.':13, ' In':763, ' my':856, ' life':2324, ' I':358, ' have':617, ' been':1027, ' drawn':15107, ' to':311, ' the':279, ' scientific':12624, ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624, ' way':1648, ',':11, ' is':374 ] +[15178] n_remain: 55 +[15178] eval: [ ' is':374 ] +[15348] n_past = 81 +[15348] last: [ ' are':527, ' many':1690, ' ways':5627, ' to':311, ' do':656, ' this':420, '.':13, ' There':2684, ' is':374, ' the':279, ' scientific':12624, ' way':1648, ',':11, ' the':279, ' human':3823, 'ist':380, ' way':1648, ',':11, ' the':279, ' spiritual':18330, ' way':1648, ' and':323, ' the':279, ' artistic':32692, ' way':1648, '.':13, ' In':763, ' my':856, ' life':2324, ' I':358, ' have':617, ' been':1027, ' drawn':15107, ' to':311, ' the':279, ' scientific':12624, ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624, ' way':1648, ',':11, ' is':374, ' the':279 ] +[15348] n_remain: 54 +[15348] eval: [ ' the':279 ] +[15519] n_past = 82 +[15519] last: [ ' many':1690, ' ways':5627, ' to':311, ' do':656, ' this':420, '.':13, ' There':2684, ' is':374, ' the':279, ' scientific':12624, ' way':1648, ',':11, ' the':279, ' human':3823, 'ist':380, ' way':1648, ',':11, ' the':279, ' spiritual':18330, ' way':1648, ' and':323, ' the':279, ' artistic':32692, ' way':1648, '.':13, ' In':763, ' my':856, ' life':2324, ' I':358, ' have':617, ' been':1027, ' drawn':15107, ' to':311, ' the':279, ' scientific':12624, ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624, ' way':1648, ',':11, ' is':374, ' the':279, ' way':1648 ] +[15519] n_remain: 53 +[15519] eval: [ ' way':1648 ] +[15689] n_past = 83 +[15689] last: [ ' ways':5627, ' to':311, ' do':656, ' this':420, '.':13, ' There':2684, ' is':374, ' the':279, ' scientific':12624, ' way':1648, ',':11, ' the':279, ' human':3823, 'ist':380, ' way':1648, ',':11, ' the':279, ' spiritual':18330, ' way':1648, ' and':323, ' the':279, ' artistic':32692, ' way':1648, '.':13, ' In':763, ' my':856, ' life':2324, ' I':358, ' have':617, ' been':1027, ' drawn':15107, ' to':311, ' the':279, ' scientific':12624, ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624, ' way':1648, ',':11, ' is':374, ' the':279, ' way':1648, ' that':430 ] +[15689] n_remain: 52 +[15689] eval: [ ' that':430 ] +[15860] n_past = 84 +[15860] last: [ ' to':311, ' do':656, ' this':420, '.':13, ' There':2684, ' is':374, ' the':279, ' scientific':12624, ' way':1648, ',':11, ' the':279, ' human':3823, 'ist':380, ' way':1648, ',':11, ' the':279, ' spiritual':18330, ' way':1648, ' and':323, ' the':279, ' artistic':32692, ' way':1648, '.':13, ' In':763, ' my':856, ' life':2324, ' I':358, ' have':617, ' been':1027, ' drawn':15107, ' to':311, ' the':279, ' scientific':12624, ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624, ' way':1648, ',':11, ' is':374, ' the':279, ' way':1648, ' that':430, ' the':279 ] +[15860] n_remain: 51 +[15860] eval: [ ' the':279 ] +[16031] n_past = 85 +[16031] last: [ ' do':656, ' this':420, '.':13, ' There':2684, ' is':374, ' the':279, ' scientific':12624, ' way':1648, ',':11, ' the':279, ' human':3823, 'ist':380, ' way':1648, ',':11, ' the':279, ' spiritual':18330, ' way':1648, ' and':323, ' the':279, ' artistic':32692, ' way':1648, '.':13, ' In':763, ' my':856, ' life':2324, ' I':358, ' have':617, ' been':1027, ' drawn':15107, ' to':311, ' the':279, ' scientific':12624, ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624, ' way':1648, ',':11, ' is':374, ' the':279, ' way':1648, ' that':430, ' the':279, ' world':1917 ] +[16031] n_remain: 50 +[16031] eval: [ ' world':1917 ] +[16201] n_past = 86 +[16201] last: [ ' this':420, '.':13, ' There':2684, ' is':374, ' the':279, ' scientific':12624, ' way':1648, ',':11, ' the':279, ' human':3823, 'ist':380, ' way':1648, ',':11, ' the':279, ' spiritual':18330, ' way':1648, ' and':323, ' the':279, ' artistic':32692, ' way':1648, '.':13, ' In':763, ' my':856, ' life':2324, ' I':358, ' have':617, ' been':1027, ' drawn':15107, ' to':311, ' the':279, ' scientific':12624, ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624, ' way':1648, ',':11, ' is':374, ' the':279, ' way':1648, ' that':430, ' the':279, ' world':1917, ' is':374 ] +[16201] n_remain: 49 +[16201] eval: [ ' is':374 ] +[16372] n_past = 87 +[16372] last: [ '.':13, ' There':2684, ' is':374, ' the':279, ' scientific':12624, ' way':1648, ',':11, ' the':279, ' human':3823, 'ist':380, ' way':1648, ',':11, ' the':279, ' spiritual':18330, ' way':1648, ' and':323, ' the':279, ' artistic':32692, ' way':1648, '.':13, ' In':763, ' my':856, ' life':2324, ' I':358, ' have':617, ' been':1027, ' drawn':15107, ' to':311, ' the':279, ' scientific':12624, ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624, ' way':1648, ',':11, ' is':374, ' the':279, ' way':1648, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972 ] +[16372] n_remain: 48 +[16372] eval: [ ' real':1972 ] +[16543] n_past = 88 +[16543] last: [ ' There':2684, ' is':374, ' the':279, ' scientific':12624, ' way':1648, ',':11, ' the':279, ' human':3823, 'ist':380, ' way':1648, ',':11, ' the':279, ' spiritual':18330, ' way':1648, ' and':323, ' the':279, ' artistic':32692, ' way':1648, '.':13, ' In':763, ' my':856, ' life':2324, ' I':358, ' have':617, ' been':1027, ' drawn':15107, ' to':311, ' the':279, ' scientific':12624, ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624, ' way':1648, ',':11, ' is':374, ' the':279, ' way':1648, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' and':323 ] +[16543] n_remain: 47 +[16543] eval: [ ' and':323 ] +[16713] n_past = 89 +[16713] last: [ ' is':374, ' the':279, ' scientific':12624, ' way':1648, ',':11, ' the':279, ' human':3823, 'ist':380, ' way':1648, ',':11, ' the':279, ' spiritual':18330, ' way':1648, ' and':323, ' the':279, ' artistic':32692, ' way':1648, '.':13, ' In':763, ' my':856, ' life':2324, ' I':358, ' have':617, ' been':1027, ' drawn':15107, ' to':311, ' the':279, ' scientific':12624, ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624, ' way':1648, ',':11, ' is':374, ' the':279, ' way':1648, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' and':323, ' that':430 ] +[16713] n_remain: 46 +[16713] eval: [ ' that':430 ] +[16884] n_past = 90 +[16884] last: [ ' the':279, ' scientific':12624, ' way':1648, ',':11, ' the':279, ' human':3823, 'ist':380, ' way':1648, ',':11, ' the':279, ' spiritual':18330, ' way':1648, ' and':323, ' the':279, ' artistic':32692, ' way':1648, '.':13, ' In':763, ' my':856, ' life':2324, ' I':358, ' have':617, ' been':1027, ' drawn':15107, ' to':311, ' the':279, ' scientific':12624, ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624, ' way':1648, ',':11, ' is':374, ' the':279, ' way':1648, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' and':323, ' that':430, ' there':1070 ] +[16884] n_remain: 45 +[16884] eval: [ ' there':1070 ] +[17054] n_past = 91 +[17054] last: [ ' scientific':12624, ' way':1648, ',':11, ' the':279, ' human':3823, 'ist':380, ' way':1648, ',':11, ' the':279, ' spiritual':18330, ' way':1648, ' and':323, ' the':279, ' artistic':32692, ' way':1648, '.':13, ' In':763, ' my':856, ' life':2324, ' I':358, ' have':617, ' been':1027, ' drawn':15107, ' to':311, ' the':279, ' scientific':12624, ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624, ' way':1648, ',':11, ' is':374, ' the':279, ' way':1648, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' and':323, ' that':430, ' there':1070, ' are':527 ] +[17054] n_remain: 44 +[17054] eval: [ ' are':527 ] +[17225] n_past = 92 +[17225] last: [ ' way':1648, ',':11, ' the':279, ' human':3823, 'ist':380, ' way':1648, ',':11, ' the':279, ' spiritual':18330, ' way':1648, ' and':323, ' the':279, ' artistic':32692, ' way':1648, '.':13, ' In':763, ' my':856, ' life':2324, ' I':358, ' have':617, ' been':1027, ' drawn':15107, ' to':311, ' the':279, ' scientific':12624, ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624, ' way':1648, ',':11, ' is':374, ' the':279, ' way':1648, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' and':323, ' that':430, ' there':1070, ' are':527, ' no':912 ] +[17225] n_remain: 43 +[17225] eval: [ ' no':912 ] +[17396] n_past = 93 +[17396] last: [ ',':11, ' the':279, ' human':3823, 'ist':380, ' way':1648, ',':11, ' the':279, ' spiritual':18330, ' way':1648, ' and':323, ' the':279, ' artistic':32692, ' way':1648, '.':13, ' In':763, ' my':856, ' life':2324, ' I':358, ' have':617, ' been':1027, ' drawn':15107, ' to':311, ' the':279, ' scientific':12624, ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624, ' way':1648, ',':11, ' is':374, ' the':279, ' way':1648, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' and':323, ' that':430, ' there':1070, ' are':527, ' no':912, ' supernatural':50058 ] +[17396] n_remain: 42 +[17396] eval: [ ' supernatural':50058 ] +[17566] n_past = 94 +[17566] last: [ ' the':279, ' human':3823, 'ist':380, ' way':1648, ',':11, ' the':279, ' spiritual':18330, ' way':1648, ' and':323, ' the':279, ' artistic':32692, ' way':1648, '.':13, ' In':763, ' my':856, ' life':2324, ' I':358, ' have':617, ' been':1027, ' drawn':15107, ' to':311, ' the':279, ' scientific':12624, ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624, ' way':1648, ',':11, ' is':374, ' the':279, ' way':1648, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' and':323, ' that':430, ' there':1070, ' are':527, ' no':912, ' supernatural':50058, ' explanations':41941 ] +[17566] n_remain: 41 +[17566] eval: [ ' explanations':41941 ] +[17737] n_past = 95 +[17737] last: [ ' human':3823, 'ist':380, ' way':1648, ',':11, ' the':279, ' spiritual':18330, ' way':1648, ' and':323, ' the':279, ' artistic':32692, ' way':1648, '.':13, ' In':763, ' my':856, ' life':2324, ' I':358, ' have':617, ' been':1027, ' drawn':15107, ' to':311, ' the':279, ' scientific':12624, ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624, ' way':1648, ',':11, ' is':374, ' the':279, ' way':1648, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' and':323, ' that':430, ' there':1070, ' are':527, ' no':912, ' supernatural':50058, ' explanations':41941, ' for':369 ] +[17737] n_remain: 40 +[17737] eval: [ ' for':369 ] +[17908] n_past = 96 +[17908] last: [ 'ist':380, ' way':1648, ',':11, ' the':279, ' spiritual':18330, ' way':1648, ' and':323, ' the':279, ' artistic':32692, ' way':1648, '.':13, ' In':763, ' my':856, ' life':2324, ' I':358, ' have':617, ' been':1027, ' drawn':15107, ' to':311, ' the':279, ' scientific':12624, ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624, ' way':1648, ',':11, ' is':374, ' the':279, ' way':1648, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' and':323, ' that':430, ' there':1070, ' are':527, ' no':912, ' supernatural':50058, ' explanations':41941, ' for':369, ' the':279 ] +[17908] n_remain: 39 +[17908] eval: [ ' the':279 ] +[18078] n_past = 97 +[18078] last: [ ' way':1648, ',':11, ' the':279, ' spiritual':18330, ' way':1648, ' and':323, ' the':279, ' artistic':32692, ' way':1648, '.':13, ' In':763, ' my':856, ' life':2324, ' I':358, ' have':617, ' been':1027, ' drawn':15107, ' to':311, ' the':279, ' scientific':12624, ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624, ' way':1648, ',':11, ' is':374, ' the':279, ' way':1648, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' and':323, ' that':430, ' there':1070, ' are':527, ' no':912, ' supernatural':50058, ' explanations':41941, ' for':369, ' the':279, ' world':1917 ] +[18078] n_remain: 38 +[18078] eval: [ ' world':1917 ] +[18249] n_past = 98 +[18249] last: [ ',':11, ' the':279, ' spiritual':18330, ' way':1648, ' and':323, ' the':279, ' artistic':32692, ' way':1648, '.':13, ' In':763, ' my':856, ' life':2324, ' I':358, ' have':617, ' been':1027, ' drawn':15107, ' to':311, ' the':279, ' scientific':12624, ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624, ' way':1648, ',':11, ' is':374, ' the':279, ' way':1648, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' and':323, ' that':430, ' there':1070, ' are':527, ' no':912, ' supernatural':50058, ' explanations':41941, ' for':369, ' the':279, ' world':1917, ',':11 ] +[18249] n_remain: 37 +[18249] eval: [ ',':11 ] +[18420] n_past = 99 +[18420] last: [ ' the':279, ' spiritual':18330, ' way':1648, ' and':323, ' the':279, ' artistic':32692, ' way':1648, '.':13, ' In':763, ' my':856, ' life':2324, ' I':358, ' have':617, ' been':1027, ' drawn':15107, ' to':311, ' the':279, ' scientific':12624, ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624, ' way':1648, ',':11, ' is':374, ' the':279, ' way':1648, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' and':323, ' that':430, ' there':1070, ' are':527, ' no':912, ' supernatural':50058, ' explanations':41941, ' for':369, ' the':279, ' world':1917, ',':11, ' nor':6463 ] +[18420] n_remain: 36 +[18420] eval: [ ' nor':6463 ] +[18591] n_past = 100 +[18591] last: [ ' spiritual':18330, ' way':1648, ' and':323, ' the':279, ' artistic':32692, ' way':1648, '.':13, ' In':763, ' my':856, ' life':2324, ' I':358, ' have':617, ' been':1027, ' drawn':15107, ' to':311, ' the':279, ' scientific':12624, ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624, ' way':1648, ',':11, ' is':374, ' the':279, ' way':1648, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' and':323, ' that':430, ' there':1070, ' are':527, ' no':912, ' supernatural':50058, ' explanations':41941, ' for':369, ' the':279, ' world':1917, ',':11, ' nor':6463, ' gods':29913 ] +[18591] n_remain: 35 +[18591] eval: [ ' gods':29913 ] +[18761] n_past = 101 +[18761] last: [ ' way':1648, ' and':323, ' the':279, ' artistic':32692, ' way':1648, '.':13, ' In':763, ' my':856, ' life':2324, ' I':358, ' have':617, ' been':1027, ' drawn':15107, ' to':311, ' the':279, ' scientific':12624, ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624, ' way':1648, ',':11, ' is':374, ' the':279, ' way':1648, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' and':323, ' that':430, ' there':1070, ' are':527, ' no':912, ' supernatural':50058, ' explanations':41941, ' for':369, ' the':279, ' world':1917, ',':11, ' nor':6463, ' gods':29913, ',':11 ] +[18761] n_remain: 34 +[18761] eval: [ ',':11 ] +[18932] n_past = 102 +[18932] last: [ ' and':323, ' the':279, ' artistic':32692, ' way':1648, '.':13, ' In':763, ' my':856, ' life':2324, ' I':358, ' have':617, ' been':1027, ' drawn':15107, ' to':311, ' the':279, ' scientific':12624, ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624, ' way':1648, ',':11, ' is':374, ' the':279, ' way':1648, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' and':323, ' that':430, ' there':1070, ' are':527, ' no':912, ' supernatural':50058, ' explanations':41941, ' for':369, ' the':279, ' world':1917, ',':11, ' nor':6463, ' gods':29913, ',':11, ' angels':46968 ] +[18932] n_remain: 33 +[18932] eval: [ ' angels':46968 ] +[19103] n_past = 103 +[19103] last: [ ' the':279, ' artistic':32692, ' way':1648, '.':13, ' In':763, ' my':856, ' life':2324, ' I':358, ' have':617, ' been':1027, ' drawn':15107, ' to':311, ' the':279, ' scientific':12624, ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624, ' way':1648, ',':11, ' is':374, ' the':279, ' way':1648, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' and':323, ' that':430, ' there':1070, ' are':527, ' no':912, ' supernatural':50058, ' explanations':41941, ' for':369, ' the':279, ' world':1917, ',':11, ' nor':6463, ' gods':29913, ',':11, ' angels':46968, ' or':477 ] +[19103] n_remain: 32 +[19103] eval: [ ' or':477 ] +[19274] n_past = 104 +[19274] last: [ ' artistic':32692, ' way':1648, '.':13, ' In':763, ' my':856, ' life':2324, ' I':358, ' have':617, ' been':1027, ' drawn':15107, ' to':311, ' the':279, ' scientific':12624, ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624, ' way':1648, ',':11, ' is':374, ' the':279, ' way':1648, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' and':323, ' that':430, ' there':1070, ' are':527, ' no':912, ' supernatural':50058, ' explanations':41941, ' for':369, ' the':279, ' world':1917, ',':11, ' nor':6463, ' gods':29913, ',':11, ' angels':46968, ' or':477, ' demons':45075 ] +[19274] n_remain: 31 +[19274] eval: [ ' demons':45075 ] +[19445] n_past = 105 +[19445] last: [ ' way':1648, '.':13, ' In':763, ' my':856, ' life':2324, ' I':358, ' have':617, ' been':1027, ' drawn':15107, ' to':311, ' the':279, ' scientific':12624, ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624, ' way':1648, ',':11, ' is':374, ' the':279, ' way':1648, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' and':323, ' that':430, ' there':1070, ' are':527, ' no':912, ' supernatural':50058, ' explanations':41941, ' for':369, ' the':279, ' world':1917, ',':11, ' nor':6463, ' gods':29913, ',':11, ' angels':46968, ' or':477, ' demons':45075, '.':13 ] +[19445] n_remain: 30 +[19445] eval: [ '.':13 ] +[19615] n_past = 106 +[19615] last: [ '.':13, ' In':763, ' my':856, ' life':2324, ' I':358, ' have':617, ' been':1027, ' drawn':15107, ' to':311, ' the':279, ' scientific':12624, ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624, ' way':1648, ',':11, ' is':374, ' the':279, ' way':1648, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' and':323, ' that':430, ' there':1070, ' are':527, ' no':912, ' supernatural':50058, ' explanations':41941, ' for':369, ' the':279, ' world':1917, ',':11, ' nor':6463, ' gods':29913, ',':11, ' angels':46968, ' or':477, ' demons':45075, '.':13, ' I':358 ] +[19615] n_remain: 29 +[19615] eval: [ ' I':358 ] +[19786] n_past = 107 +[19786] last: [ ' In':763, ' my':856, ' life':2324, ' I':358, ' have':617, ' been':1027, ' drawn':15107, ' to':311, ' the':279, ' scientific':12624, ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624, ' way':1648, ',':11, ' is':374, ' the':279, ' way':1648, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' and':323, ' that':430, ' there':1070, ' are':527, ' no':912, ' supernatural':50058, ' explanations':41941, ' for':369, ' the':279, ' world':1917, ',':11, ' nor':6463, ' gods':29913, ',':11, ' angels':46968, ' or':477, ' demons':45075, '.':13, ' I':358, ' am':1097 ] +[19786] n_remain: 28 +[19786] eval: [ ' am':1097 ] +[19957] n_past = 108 +[19957] last: [ ' my':856, ' life':2324, ' I':358, ' have':617, ' been':1027, ' drawn':15107, ' to':311, ' the':279, ' scientific':12624, ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624, ' way':1648, ',':11, ' is':374, ' the':279, ' way':1648, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' and':323, ' that':430, ' there':1070, ' are':527, ' no':912, ' supernatural':50058, ' explanations':41941, ' for':369, ' the':279, ' world':1917, ',':11, ' nor':6463, ' gods':29913, ',':11, ' angels':46968, ' or':477, ' demons':45075, '.':13, ' I':358, ' am':1097, ' not':539 ] +[19957] n_remain: 27 +[19957] eval: [ ' not':539 ] +[20128] n_past = 109 +[20128] last: [ ' life':2324, ' I':358, ' have':617, ' been':1027, ' drawn':15107, ' to':311, ' the':279, ' scientific':12624, ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624, ' way':1648, ',':11, ' is':374, ' the':279, ' way':1648, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' and':323, ' that':430, ' there':1070, ' are':527, ' no':912, ' supernatural':50058, ' explanations':41941, ' for':369, ' the':279, ' world':1917, ',':11, ' nor':6463, ' gods':29913, ',':11, ' angels':46968, ' or':477, ' demons':45075, '.':13, ' I':358, ' am':1097, ' not':539, ' sure':2771 ] +[20128] n_remain: 26 +[20128] eval: [ ' sure':2771 ] +[20298] n_past = 110 +[20299] last: [ ' I':358, ' have':617, ' been':1027, ' drawn':15107, ' to':311, ' the':279, ' scientific':12624, ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624, ' way':1648, ',':11, ' is':374, ' the':279, ' way':1648, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' and':323, ' that':430, ' there':1070, ' are':527, ' no':912, ' supernatural':50058, ' explanations':41941, ' for':369, ' the':279, ' world':1917, ',':11, ' nor':6463, ' gods':29913, ',':11, ' angels':46968, ' or':477, ' demons':45075, '.':13, ' I':358, ' am':1097, ' not':539, ' sure':2771, ' I':358 ] +[20299] n_remain: 25 +[20299] eval: [ ' I':358 ] +[20469] n_past = 111 +[20469] last: [ ' have':617, ' been':1027, ' drawn':15107, ' to':311, ' the':279, ' scientific':12624, ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624, ' way':1648, ',':11, ' is':374, ' the':279, ' way':1648, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' and':323, ' that':430, ' there':1070, ' are':527, ' no':912, ' supernatural':50058, ' explanations':41941, ' for':369, ' the':279, ' world':1917, ',':11, ' nor':6463, ' gods':29913, ',':11, ' angels':46968, ' or':477, ' demons':45075, '.':13, ' I':358, ' am':1097, ' not':539, ' sure':2771, ' I':358, ' believe':4510 ] +[20469] n_remain: 24 +[20469] eval: [ ' believe':4510 ] +[20640] n_past = 112 +[20640] last: [ ' been':1027, ' drawn':15107, ' to':311, ' the':279, ' scientific':12624, ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624, ' way':1648, ',':11, ' is':374, ' the':279, ' way':1648, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' and':323, ' that':430, ' there':1070, ' are':527, ' no':912, ' supernatural':50058, ' explanations':41941, ' for':369, ' the':279, ' world':1917, ',':11, ' nor':6463, ' gods':29913, ',':11, ' angels':46968, ' or':477, ' demons':45075, '.':13, ' I':358, ' am':1097, ' not':539, ' sure':2771, ' I':358, ' believe':4510, ' the':279 ] +[20640] n_remain: 23 +[20640] eval: [ ' the':279 ] +[20811] n_past = 113 +[20811] last: [ ' drawn':15107, ' to':311, ' the':279, ' scientific':12624, ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624, ' way':1648, ',':11, ' is':374, ' the':279, ' way':1648, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' and':323, ' that':430, ' there':1070, ' are':527, ' no':912, ' supernatural':50058, ' explanations':41941, ' for':369, ' the':279, ' world':1917, ',':11, ' nor':6463, ' gods':29913, ',':11, ' angels':46968, ' or':477, ' demons':45075, '.':13, ' I':358, ' am':1097, ' not':539, ' sure':2771, ' I':358, ' believe':4510, ' the':279, ' universe':15861 ] +[20811] n_remain: 22 +[20811] eval: [ ' universe':15861 ] +[20982] n_past = 114 +[20982] last: [ ' to':311, ' the':279, ' scientific':12624, ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624, ' way':1648, ',':11, ' is':374, ' the':279, ' way':1648, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' and':323, ' that':430, ' there':1070, ' are':527, ' no':912, ' supernatural':50058, ' explanations':41941, ' for':369, ' the':279, ' world':1917, ',':11, ' nor':6463, ' gods':29913, ',':11, ' angels':46968, ' or':477, ' demons':45075, '.':13, ' I':358, ' am':1097, ' not':539, ' sure':2771, ' I':358, ' believe':4510, ' the':279, ' universe':15861, ' exists':6866 ] +[20982] n_remain: 21 +[20982] eval: [ ' exists':6866 ] +[21152] n_past = 115 +[21152] last: [ ' the':279, ' scientific':12624, ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624, ' way':1648, ',':11, ' is':374, ' the':279, ' way':1648, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' and':323, ' that':430, ' there':1070, ' are':527, ' no':912, ' supernatural':50058, ' explanations':41941, ' for':369, ' the':279, ' world':1917, ',':11, ' nor':6463, ' gods':29913, ',':11, ' angels':46968, ' or':477, ' demons':45075, '.':13, ' I':358, ' am':1097, ' not':539, ' sure':2771, ' I':358, ' believe':4510, ' the':279, ' universe':15861, ' exists':6866, ',':11 ] +[21152] n_remain: 20 +[21152] eval: [ ',':11 ] +[21323] n_past = 116 +[21323] last: [ ' scientific':12624, ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624, ' way':1648, ',':11, ' is':374, ' the':279, ' way':1648, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' and':323, ' that':430, ' there':1070, ' are':527, ' no':912, ' supernatural':50058, ' explanations':41941, ' for':369, ' the':279, ' world':1917, ',':11, ' nor':6463, ' gods':29913, ',':11, ' angels':46968, ' or':477, ' demons':45075, '.':13, ' I':358, ' am':1097, ' not':539, ' sure':2771, ' I':358, ' believe':4510, ' the':279, ' universe':15861, ' exists':6866, ',':11, ' I':358 ] +[21323] n_remain: 19 +[21323] eval: [ ' I':358 ] +[21494] n_past = 117 +[21494] last: [ ' way':1648, ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624, ' way':1648, ',':11, ' is':374, ' the':279, ' way':1648, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' and':323, ' that':430, ' there':1070, ' are':527, ' no':912, ' supernatural':50058, ' explanations':41941, ' for':369, ' the':279, ' world':1917, ',':11, ' nor':6463, ' gods':29913, ',':11, ' angels':46968, ' or':477, ' demons':45075, '.':13, ' I':358, ' am':1097, ' not':539, ' sure':2771, ' I':358, ' believe':4510, ' the':279, ' universe':15861, ' exists':6866, ',':11, ' I':358, ' believe':4510 ] +[21494] n_remain: 18 +[21494] eval: [ ' believe':4510 ] +[21665] n_past = 118 +[21665] last: [ ' and':323, ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624, ' way':1648, ',':11, ' is':374, ' the':279, ' way':1648, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' and':323, ' that':430, ' there':1070, ' are':527, ' no':912, ' supernatural':50058, ' explanations':41941, ' for':369, ' the':279, ' world':1917, ',':11, ' nor':6463, ' gods':29913, ',':11, ' angels':46968, ' or':477, ' demons':45075, '.':13, ' I':358, ' am':1097, ' not':539, ' sure':2771, ' I':358, ' believe':4510, ' the':279, ' universe':15861, ' exists':6866, ',':11, ' I':358, ' believe':4510, ' that':430 ] +[21665] n_remain: 17 +[21665] eval: [ ' that':430 ] +[21836] n_past = 119 +[21836] last: [ ' the':279, ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624, ' way':1648, ',':11, ' is':374, ' the':279, ' way':1648, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' and':323, ' that':430, ' there':1070, ' are':527, ' no':912, ' supernatural':50058, ' explanations':41941, ' for':369, ' the':279, ' world':1917, ',':11, ' nor':6463, ' gods':29913, ',':11, ' angels':46968, ' or':477, ' demons':45075, '.':13, ' I':358, ' am':1097, ' not':539, ' sure':2771, ' I':358, ' believe':4510, ' the':279, ' universe':15861, ' exists':6866, ',':11, ' I':358, ' believe':4510, ' that':430, ' the':279 ] +[21836] n_remain: 16 +[21836] eval: [ ' the':279 ] +[22007] n_past = 120 +[22007] last: [ ' human':3823, 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624, ' way':1648, ',':11, ' is':374, ' the':279, ' way':1648, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' and':323, ' that':430, ' there':1070, ' are':527, ' no':912, ' supernatural':50058, ' explanations':41941, ' for':369, ' the':279, ' world':1917, ',':11, ' nor':6463, ' gods':29913, ',':11, ' angels':46968, ' or':477, ' demons':45075, '.':13, ' I':358, ' am':1097, ' not':539, ' sure':2771, ' I':358, ' believe':4510, ' the':279, ' universe':15861, ' exists':6866, ',':11, ' I':358, ' believe':4510, ' that':430, ' the':279, ' world':1917 ] +[22007] n_remain: 15 +[22007] eval: [ ' world':1917 ] +[22177] n_past = 121 +[22177] last: [ 'ist':380, ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624, ' way':1648, ',':11, ' is':374, ' the':279, ' way':1648, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' and':323, ' that':430, ' there':1070, ' are':527, ' no':912, ' supernatural':50058, ' explanations':41941, ' for':369, ' the':279, ' world':1917, ',':11, ' nor':6463, ' gods':29913, ',':11, ' angels':46968, ' or':477, ' demons':45075, '.':13, ' I':358, ' am':1097, ' not':539, ' sure':2771, ' I':358, ' believe':4510, ' the':279, ' universe':15861, ' exists':6866, ',':11, ' I':358, ' believe':4510, ' that':430, ' the':279, ' world':1917, ' is':374 ] +[22177] n_remain: 14 +[22177] eval: [ ' is':374 ] +[22348] n_past = 122 +[22348] last: [ ' way':1648, ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624, ' way':1648, ',':11, ' is':374, ' the':279, ' way':1648, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' and':323, ' that':430, ' there':1070, ' are':527, ' no':912, ' supernatural':50058, ' explanations':41941, ' for':369, ' the':279, ' world':1917, ',':11, ' nor':6463, ' gods':29913, ',':11, ' angels':46968, ' or':477, ' demons':45075, '.':13, ' I':358, ' am':1097, ' not':539, ' sure':2771, ' I':358, ' believe':4510, ' the':279, ' universe':15861, ' exists':6866, ',':11, ' I':358, ' believe':4510, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972 ] +[22348] n_remain: 13 +[22348] eval: [ ' real':1972 ] +[22519] n_past = 123 +[22519] last: [ ' the':279, ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624, ' way':1648, ',':11, ' is':374, ' the':279, ' way':1648, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' and':323, ' that':430, ' there':1070, ' are':527, ' no':912, ' supernatural':50058, ' explanations':41941, ' for':369, ' the':279, ' world':1917, ',':11, ' nor':6463, ' gods':29913, ',':11, ' angels':46968, ' or':477, ' demons':45075, '.':13, ' I':358, ' am':1097, ' not':539, ' sure':2771, ' I':358, ' believe':4510, ' the':279, ' universe':15861, ' exists':6866, ',':11, ' I':358, ' believe':4510, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' but':719 ] +[22519] n_remain: 12 +[22519] eval: [ ' but':719 ] +[22690] n_past = 124 +[22690] last: [ ' most':1455, ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624, ' way':1648, ',':11, ' is':374, ' the':279, ' way':1648, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' and':323, ' that':430, ' there':1070, ' are':527, ' no':912, ' supernatural':50058, ' explanations':41941, ' for':369, ' the':279, ' world':1917, ',':11, ' nor':6463, ' gods':29913, ',':11, ' angels':46968, ' or':477, ' demons':45075, '.':13, ' I':358, ' am':1097, ' not':539, ' sure':2771, ' I':358, ' believe':4510, ' the':279, ' universe':15861, ' exists':6866, ',':11, ' I':358, ' believe':4510, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' but':719, ' I':358 ] +[22690] n_remain: 11 +[22690] eval: [ ' I':358 ] +[22861] n_past = 125 +[22861] last: [ ',':11, ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624, ' way':1648, ',':11, ' is':374, ' the':279, ' way':1648, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' and':323, ' that':430, ' there':1070, ' are':527, ' no':912, ' supernatural':50058, ' explanations':41941, ' for':369, ' the':279, ' world':1917, ',':11, ' nor':6463, ' gods':29913, ',':11, ' angels':46968, ' or':477, ' demons':45075, '.':13, ' I':358, ' am':1097, ' not':539, ' sure':2771, ' I':358, ' believe':4510, ' the':279, ' universe':15861, ' exists':6866, ',':11, ' I':358, ' believe':4510, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' but':719, ' I':358, ' am':1097 ] +[22861] n_remain: 10 +[22861] eval: [ ' am':1097 ] +[23031] n_past = 126 +[23031] last: [ ' although':8051, ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624, ' way':1648, ',':11, ' is':374, ' the':279, ' way':1648, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' and':323, ' that':430, ' there':1070, ' are':527, ' no':912, ' supernatural':50058, ' explanations':41941, ' for':369, ' the':279, ' world':1917, ',':11, ' nor':6463, ' gods':29913, ',':11, ' angels':46968, ' or':477, ' demons':45075, '.':13, ' I':358, ' am':1097, ' not':539, ' sure':2771, ' I':358, ' believe':4510, ' the':279, ' universe':15861, ' exists':6866, ',':11, ' I':358, ' believe':4510, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' but':719, ' I':358, ' am':1097, ' not':539 ] +[23031] n_remain: 9 +[23031] eval: [ ' not':539 ] +[23202] n_past = 127 +[23202] last: [ ' I':358, ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624, ' way':1648, ',':11, ' is':374, ' the':279, ' way':1648, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' and':323, ' that':430, ' there':1070, ' are':527, ' no':912, ' supernatural':50058, ' explanations':41941, ' for':369, ' the':279, ' world':1917, ',':11, ' nor':6463, ' gods':29913, ',':11, ' angels':46968, ' or':477, ' demons':45075, '.':13, ' I':358, ' am':1097, ' not':539, ' sure':2771, ' I':358, ' believe':4510, ' the':279, ' universe':15861, ' exists':6866, ',':11, ' I':358, ' believe':4510, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' but':719, ' I':358, ' am':1097, ' not':539, ' sure':2771 ] +[23202] n_remain: 8 +[23202] eval: [ ' sure':2771 ] +[23373] n_past = 128 +[23373] last: [ ' have':617, ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624, ' way':1648, ',':11, ' is':374, ' the':279, ' way':1648, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' and':323, ' that':430, ' there':1070, ' are':527, ' no':912, ' supernatural':50058, ' explanations':41941, ' for':369, ' the':279, ' world':1917, ',':11, ' nor':6463, ' gods':29913, ',':11, ' angels':46968, ' or':477, ' demons':45075, '.':13, ' I':358, ' am':1097, ' not':539, ' sure':2771, ' I':358, ' believe':4510, ' the':279, ' universe':15861, ' exists':6866, ',':11, ' I':358, ' believe':4510, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' but':719, ' I':358, ' am':1097, ' not':539, ' sure':2771, ' it':433 ] +[23373] n_remain: 7 +[23373] eval: [ ' it':433 ] +[23544] n_past = 129 +[23544] last: [ ' also':1101, ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624, ' way':1648, ',':11, ' is':374, ' the':279, ' way':1648, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' and':323, ' that':430, ' there':1070, ' are':527, ' no':912, ' supernatural':50058, ' explanations':41941, ' for':369, ' the':279, ' world':1917, ',':11, ' nor':6463, ' gods':29913, ',':11, ' angels':46968, ' or':477, ' demons':45075, '.':13, ' I':358, ' am':1097, ' not':539, ' sure':2771, ' I':358, ' believe':4510, ' the':279, ' universe':15861, ' exists':6866, ',':11, ' I':358, ' believe':4510, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' but':719, ' I':358, ' am':1097, ' not':539, ' sure':2771, ' it':433, ' exists':6866 ] +[23544] n_remain: 6 +[23544] eval: [ ' exists':6866 ] +[23715] n_past = 130 +[23715] last: [ ' been':1027, ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624, ' way':1648, ',':11, ' is':374, ' the':279, ' way':1648, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' and':323, ' that':430, ' there':1070, ' are':527, ' no':912, ' supernatural':50058, ' explanations':41941, ' for':369, ' the':279, ' world':1917, ',':11, ' nor':6463, ' gods':29913, ',':11, ' angels':46968, ' or':477, ' demons':45075, '.':13, ' I':358, ' am':1097, ' not':539, ' sure':2771, ' I':358, ' believe':4510, ' the':279, ' universe':15861, ' exists':6866, ',':11, ' I':358, ' believe':4510, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' but':719, ' I':358, ' am':1097, ' not':539, ' sure':2771, ' it':433, ' exists':6866, ',':11 ] +[23715] n_remain: 5 +[23715] eval: [ ',':11 ] +[23886] n_past = 131 +[23886] last: [ ' interested':8173, ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624, ' way':1648, ',':11, ' is':374, ' the':279, ' way':1648, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' and':323, ' that':430, ' there':1070, ' are':527, ' no':912, ' supernatural':50058, ' explanations':41941, ' for':369, ' the':279, ' world':1917, ',':11, ' nor':6463, ' gods':29913, ',':11, ' angels':46968, ' or':477, ' demons':45075, '.':13, ' I':358, ' am':1097, ' not':539, ' sure':2771, ' I':358, ' believe':4510, ' the':279, ' universe':15861, ' exists':6866, ',':11, ' I':358, ' believe':4510, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' but':719, ' I':358, ' am':1097, ' not':539, ' sure':2771, ' it':433, ' exists':6866, ',':11, ' I':358 ] +[23886] n_remain: 4 +[23886] eval: [ ' I':358 ] +[24057] n_past = 132 +[24057] last: [ ' in':304, ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624, ' way':1648, ',':11, ' is':374, ' the':279, ' way':1648, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' and':323, ' that':430, ' there':1070, ' are':527, ' no':912, ' supernatural':50058, ' explanations':41941, ' for':369, ' the':279, ' world':1917, ',':11, ' nor':6463, ' gods':29913, ',':11, ' angels':46968, ' or':477, ' demons':45075, '.':13, ' I':358, ' am':1097, ' not':539, ' sure':2771, ' I':358, ' believe':4510, ' the':279, ' universe':15861, ' exists':6866, ',':11, ' I':358, ' believe':4510, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' but':719, ' I':358, ' am':1097, ' not':539, ' sure':2771, ' it':433, ' exists':6866, ',':11, ' I':358, ' am':1097 ] +[24057] n_remain: 3 +[24057] eval: [ ' am':1097 ] +[24228] n_past = 133 +[24228] last: [ ' the':279, ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624, ' way':1648, ',':11, ' is':374, ' the':279, ' way':1648, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' and':323, ' that':430, ' there':1070, ' are':527, ' no':912, ' supernatural':50058, ' explanations':41941, ' for':369, ' the':279, ' world':1917, ',':11, ' nor':6463, ' gods':29913, ',':11, ' angels':46968, ' or':477, ' demons':45075, '.':13, ' I':358, ' am':1097, ' not':539, ' sure':2771, ' I':358, ' believe':4510, ' the':279, ' universe':15861, ' exists':6866, ',':11, ' I':358, ' believe':4510, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' but':719, ' I':358, ' am':1097, ' not':539, ' sure':2771, ' it':433, ' exists':6866, ',':11, ' I':358, ' am':1097, ' not':539 ] +[24228] n_remain: 2 +[24228] eval: [ ' not':539 ] +[24399] n_past = 134 +[24399] last: [ ' spiritual':18330, ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624, ' way':1648, ',':11, ' is':374, ' the':279, ' way':1648, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' and':323, ' that':430, ' there':1070, ' are':527, ' no':912, ' supernatural':50058, ' explanations':41941, ' for':369, ' the':279, ' world':1917, ',':11, ' nor':6463, ' gods':29913, ',':11, ' angels':46968, ' or':477, ' demons':45075, '.':13, ' I':358, ' am':1097, ' not':539, ' sure':2771, ' I':358, ' believe':4510, ' the':279, ' universe':15861, ' exists':6866, ',':11, ' I':358, ' believe':4510, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' but':719, ' I':358, ' am':1097, ' not':539, ' sure':2771, ' it':433, ' exists':6866, ',':11, ' I':358, ' am':1097, ' not':539, ' sure':2771 ] +[24399] n_remain: 1 +[24399] eval: [ ' sure':2771 ] +[24570] n_past = 135 +[24570] last: [ ' and':323, ' artistic':32692, ' way':1648, '.':627, 'The':791, ' scientific':12624, ' way':1648, ',':11, ' is':374, ' the':279, ' way':1648, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' and':323, ' that':430, ' there':1070, ' are':527, ' no':912, ' supernatural':50058, ' explanations':41941, ' for':369, ' the':279, ' world':1917, ',':11, ' nor':6463, ' gods':29913, ',':11, ' angels':46968, ' or':477, ' demons':45075, '.':13, ' I':358, ' am':1097, ' not':539, ' sure':2771, ' I':358, ' believe':4510, ' the':279, ' universe':15861, ' exists':6866, ',':11, ' I':358, ' believe':4510, ' that':430, ' the':279, ' world':1917, ' is':374, ' real':1972, ' but':719, ' I':358, ' am':1097, ' not':539, ' sure':2771, ' it':433, ' exists':6866, ',':11, ' I':358, ' am':1097, ' not':539, ' sure':2771, ' what':1148 ] +[24570] n_remain: 0 +[24570] +[24570] llama_print_timings: load time = 512670.38 ms +[24570] llama_print_timings: sample time = 121.89 ms / 128 runs ( 0.95 ms per token, 1050.09 tokens per second) +[24570] llama_print_timings: prompt eval time = 423199.98 ms / 8 tokens (52900.00 ms per token, 0.02 tokens per second) +[24570] llama_print_timings: eval time = 21677163.50 ms / 127 runs (170686.33 ms per token, 0.01 tokens per second) +[24570] llama_print_timings: total time = 22101103.40 ms / 135 tokens +[24576] Log end diff --git a/Q4_result.png b/Q4_result.png new file mode 100644 index 0000000000000000000000000000000000000000..64efac0a4c435418916d650c0a6ff82cf52fec06 GIT binary patch literal 1013403 zcmeFZc|27A`#+3|B&ifh8KshJNwUu*l}ge(6(VD8c-vw^VjPlG6eT3fkV<9W$ug8J z+mP%s_OTB$7_*)8J45g9=W~DW@9&TMe%$vTzsKX_iaF=JmUGT)xvuB+ysqi#)hhxDNvgFEor`MXWSp&*NZRruW-?6=`_MvbzeS?0_Z*@wAFJ_{ZF)=n^;x?bCiQ?HMQFQgq#wMOf zg$tsae80BI988@ovEkXUQ<{gr4THTF(j3Tx4s1vO%ls#K+X^b(b@tDY04V!l)A$EZ zo3+XHg8R>4mZ9K zDgTYiGxWoy=;$_{6Z>;JIy5~l?8{UA_K{Bs9hkG-rhaU!)AEtAOh&}2^eO5+|MSi0 zks6NTo$y0P;`hrA_gdZANU1a4eIz#@B#y3?%k$X68?4RK_R7)tf4nu~TJ%__>By7yn4OAkI& 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zN)qDs(9)V?ZkKuG;g@N2i3{!1W1T&^Bdv2TPu?8>%1q5`#>8Nh3Sd9HcwCd5(m4Di zDub5`_dixsY7K_ua_Y)G4gDSAtH60qI4pSE_g80si<0&cVmcR~U41U-vGc=DM0!#i zwr z4#VaFZndNATuf694&13R*-Gi&@V(q5Z(D{1sC+e%dD_v))!9oj>7<_JTGeS_W1(MY zIGjdd*k)y>zgZgqn=R*Q@Vpcx_bl?=hOWu`1X{{At(2zl^NYUviDIU%&TmdaBT|aV zlDWxIw{~5=lK=C)lllH-9pqUj51y6BjUh_losu 512MB（内存），也就是K230的内存放不下llama的权重矩阵，需要增加swap内存才能推理，这样会极大的影响推理的速度。 + +### 1、编译K230 sdk +- 参考官方手册，编译并运行docker环境 +``` +git clone https://gitee.com/kendryte/k230_sdk.git +cd k230_sdk +source tools/get_download_url.sh && make prepare_sourcecode +docker build -f tools/docker/Dockerfile -t k230_docker tools/docker +docker run -u root -it -v $(pwd):$(pwd) -v $(pwd)/toolchain:/opt/toolchain -w $(pwd) k230_docker /bin/bash +``` +- 调整config文件使linux在大核上运行 +- 调整sharefs文件为5G +- 编译CANMV-K230板子镜像 +``` +make CONF=k230_canmv_defconfig +``` + +### 2、编译llama.cpp +- 下载llama.cpp源码 +``` +git clone https://github.com/ggerganov/llama.cpp +cd llama.cpp && vim Makefile +``` +- 修改 makefile里面的CC为自己的路径 +``` +ifdef RISCV_CROSS_COMPILE +CC := /home/xingke/desktop/k230_sdk/toolchain/Xuantie-900-gcc-linux-5.10.4-glibc-x86_64-V2.6.0/bin/riscv64-unknown-linux-gnu-gcc +CXX := /home/xingke/desktop/k230_sdk/toolchain/Xuantie-900-gcc-linux-5.10.4-glibc-x86_64-V2.6.0/bin/riscv64-unknown-linux-gnu-g++ +``` +- 交叉编译llama.cpp +``` +make RISCV=1 RISCV_CROSS_COMPILE=1 LLAMA_STATIC=1 LLAMA_NO_OPENMP=1 +``` + +### 3、库名移植 +- 将k230__sdk的库名和llama.cpp库名对齐 +``` +ln -s /lib64xthead/lp64d/ld-2.33.so /lib/ld-linux-riscv64-lp64d.so.1 +``` + +### 4、测试 +- 将llama.cli和量化好的q4模型拷贝到sharefs中 +- matmult测试 +``` +./llama-benchmark-matmult +``` +- 最简单的矩阵乘法需要763.12MB的内存，所以对512MB内存的K230来说，运行llama3，内存偏小。 +- llama-cli 测试（Q4） +``` +./llama-cli -m Llama-3-7B.Q4_K_S.gguf -p "I believe the meaning of life is" -n 128 +- prompt eval time = 51.9s/per token +- eval time = 170s/per token +``` + +- llama-cli 测试（Q2） +``` +./llama-cli -m ggml-model-q2_k.gguf -p "I believe the meaning of life is" -n 128 +- prompt eval time = 65.5s/per token +- eval time = 179s/per token +``` + +- 因为使用了swap交换内存进行扩容，所以推理的速度还是比较慢的。 + + +## 方法2：使用nncase完成部署 + +### 1、环境选择 +- 因为转换30G的llama3模型文件需要200G左右的内存，这里选择了autodl的环境，Python 3.8(ubuntu20.04)，240G内存的镜像。 + +### 2、配置虚拟环境myenv并下载llm-export +``` +conda config --set ssl_verify no +conda create -n myenv python=3.9 +git clone https://github.com/wangzhaode/llm-export.git +pip install -r requirements +pip install --upgrade onnxruntime +pip install transformers==4.40.0 +``` + +### 3、安装 nncase (这里是自动配置的nncase 2.9.0、dotnet7.0) +``` +pip install --upgrade pip +pip install nncase +pip install nncase-kpu +pip install onnxsim scikit-learn +wget https://packages.microsoft.com/config/ubuntu/20.04/packages-microsoft-prod.deb -O packages-microsoft-prod.deb +sudo dpkg -i packages-microsoft-prod.deb +sudo apt update +sudo apt install -y apt-transport-https +sudo apt install -y dotnet-sdk-7.0 +``` + +### 4、将llama3 转换成onnx +- git 下载Llama-3-8B-Instruct库，并重新命名为Llama-3 +``` +python llm_export.py --path ../Llama-3 --type Llama-3-8B-Instruct --onnx_path ../Llama-3-onnx --export_test --test TEST --export +``` +会生成30G的llama3.onnx文件以及llm_config.json + +### 5、将onnx文件转成kmodel +- 编写compile_model.py脚本，将30G的llama3.onnx转成kmodel，并参考了[shape_bucket]文档： +https://github.com/kendryte/nncase/blob/0e8dabdb5a3cfec5474eee62900bd392fc7432f9/docs/shape_bucket.md#L4 +增加了shape_bucket_options选项，可惜的是没有转换成功 +- nncase2.9.0应该是只支持转换2GB的模型。 diff --git a/compile_error.jpg b/compile_error.jpg new file mode 100644 index 0000000000000000000000000000000000000000..b841e1dcec63ca72819a1a4a2488da47d1337a54 GIT binary patch literal 21951 zcmc$`cUTkKyZ0U2RzO5i#4RP_R#6dRrxOL0CZH4}H6kJkLg+|K+)A-QPz00~3mqW} z2BbzsiFBm}2oN;_CLtiCkusTgVE@kVT-SS@^StjL=Xst#U`R4ES+i!X@A}@K`yTF` zvA0x|-zpD-!4$2nPB_9~%b76PvfMR)K<`{?G5ZN^mW4T5n!_r))uB&dEB%h!9f!eQ z;}xXdtDx6%!B(zeFxcjui$BY(9e4bO!CaiJPaJo??!_51uH=2rn*yQ~byapeOQ_Us zyz+S;rhny6{9l$uYkx$@e_5B1X<2)8TlkZYTYOZDq~F(Vt-iUUQ+c5ksn>b?!svD5 zwodL5v+MaS+Zd-V&u5vKbb?cK8HYYe2W3L&>tR7R)7C+o(Y0C{(B|!*=0?ya_)tPP 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z%Nf#U%(dfriGjG*mcOEwB<~>E@6hEB8OGyK$_(cVWgy)HIUQ)63sNLlttH+?OOKEb2v!d5c;9k7hckAv-YIKRdq$ z>DT|a#6OM45LpkuXJgVKZ?2k^Xj4gbIH%4NE)v-B$0axc?k~LvEa45BV?D2#Bg9Ks df2pTISVp^Sht?(FIrQ!&A^Q&QZABi>`!7)-|7QRI literal 0 HcmV?d00001 diff --git a/compile_kmodel.py b/compile_kmodel.py new file mode 100644 index 0000000..db8c03c --- /dev/null +++ b/compile_kmodel.py @@ -0,0 +1,99 @@ +import nncase +import numpy as np +from nncase_base_func import * + +def compile_kmodel(model_path, dump_path, calib_data): + """ + Set compile options and ptq options. + Compile kmodel. + Dump the compile-time result to 'compile_options.dump_dir' + """ + print("\n---------- compile ----------") + print("Simplify...") + model_file = model_simplify(model_path) + + print("Set options...") + # import_options + import_options = nncase.ImportOptions() + + ############################################ + # 你需要修改下面这段代码中的参数来适配你的模型。 + # 详细的说明可以参考docs/USAGE_v2.md. + ############################################ + # compile_options + compile_options = nncase.CompileOptions() + compile_options.target = "k230" #"cpu" + compile_options.dump_ir = True # if False, will not dump the compile-time result. + compile_options.dump_asm = True + compile_options.dump_dir = dump_path + compile_options.input_file = "./Llama-3-onnx/llm_config.json" + + # preprocess args + compile_options.preprocess = False + if compile_options.preprocess: + compile_options.input_type = "uint8" # "uint8" "float32" + compile_options.input_shape = [1,224,320,3] + compile_options.input_range = [0,1] + compile_options.input_layout = "NHWC" # "NHWC" + compile_options.swapRB = False + compile_options.mean = [0,0,0] + compile_options.std = [1,1,1] + compile_options.letterbox_value = 0 + compile_options.output_layout = "NHWC" # "NHWC" + + # quantize options + ptq_options = nncase.PTQTensorOptions() + ptq_options.quant_type = "int8" # datatype : "float32", "int8", "int16" + ptq_options.w_quant_type = "int8" # datatype : "float32", "int8", "int16" + ptq_options.calibrate_method = "NoClip" # "Kld" + ptq_options.finetune_weights_method = "NoFineTuneWeights" + ptq_options.dump_quant_error = False + ptq_options.dump_quant_error_symmetric_for_signed = False + + # mix quantize options + # more details in docs/MixQuant.md + ptq_options.quant_scheme = "" + ptq_options.quant_scheme_strict_mode = False + ptq_options.export_quant_scheme = False + ptq_options.export_weight_range_by_channel = False + + # dynamci + shape_bucket_options = nncase.ShapeBucketOptions() + shape_bucket_options.shape_bucket_enable = True + shape_bucket_options.shape_bucket_range_info = {"seq_len": [0, 128255], "history_len": [0, 256]} + shape_bucket_options.shape_bucket_segments_count = 2 + ############################################ + + ptq_options.samples_count = len(calib_data[0]) + ptq_options.set_tensor_data(calib_data) + + print("Compiling...") + compiler = nncase.Compiler(compile_options) + # import + model_content = read_model_file(model_file) + if model_path.split(".")[-1] == "onnx": + compiler.import_onnx(model_content, import_options) + elif model_path.split(".")[-1] == "tflite": + compiler.import_tflite(model_content, import_options) + + compiler.use_ptq(ptq_options) + + # compile + compiler.compile() + kmodel = compiler.gencode_tobytes() + + kmodel_path = os.path.join(dump_path, "test.kmodel") + with open(kmodel_path, 'wb') as f: + f.write(kmodel) + print("----------------end-----------------") + return kmodel_path + +if __name__ == '__main__': + # compile kmodel multiple inputs + model_path = "/root/autodl-tmp/Llama-3-onnx/llm.onnx" + dump_path = "/root/autodl-tmp/Llama-3-kmodel/llm.kmodel" + seqlen = 3 + history_len = 1 + # 校正集的数量为2 + calib_data =[[]]#np.random.randint[[(0, 128255, size=[seqlen,], dtype='int64'),np.random.randint(0, 128255, size=[seqlen,], dtype='int64')],[np.random.rand(1, 1, seqlen, seqlen).astype(np.float32),np.random.rand(1, 1, seqlen, seqlen).astype(np.float32)],[np.random.randint(0, seqlen-1, size=[1,seqlen], dtype='int64'),np.random.randint(0, seqlen-1, size=[1,seqlen], dtype='int64')],[np.random.rand(32, 2, 1, history_len, 8, 128).astype(np.float32),np.random.rand(32, 2, 1, history_len, 8, 128).astype(np.float32)]] + kmodel_path = compile_kmodel(model_path, dump_path, calib_data) diff --git a/llm_config.json b/llm_config.json new file mode 100644 index 0000000..6cb92c4 --- /dev/null +++ b/llm_config.json @@ -0,0 +1,15 @@ +{ + "hidden_size": 4096, + "layer_nums": 32, + "attention_mask": "float", + "key_value_shape": [ + 2, + 1, + 0, + 8, + 128 + ], + "prompt_template": "<|begin_of_text|><|start_header_id|>user<|end_header_id|>\n\n%s<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n", + "is_visual": false, + "is_single": true +} \ No newline at end of file diff --git a/llm_export.py b/llm_export.py new file mode 100644 index 0000000..66b179f --- /dev/null +++ b/llm_export.py @@ -0,0 +1,1432 @@ +import os +import base64 +import glob +import json +import shutil +import argparse +import torch +import numpy as np +from onnxslim import slim +import onnxruntime as ort +import sentencepiece as spm +from transformers import AutoModel, AutoModelForCausalLM, AutoTokenizer +from peft import LoraConfig, TaskType, get_peft_model, PeftModel +try: + import _tools as MNNTools +except: + MNNTools = None + +def onnx2mnn(onnx_path, mnn_dir, quant_bit = 4, asymmetric = True, external_data = False, bizCode : str= None): + model_name, model_extension = os.path.splitext(os.path.basename(onnx_path)) + if model_extension != '.onnx': + return + mnn_name = model_name + '.mnn' + mnn_path = os.path.join(mnn_dir, mnn_name) + convert_args = [ + '', + '-f', + 'ONNX', + '--modelFile', + str(onnx_path), + '--MNNModel', + str(mnn_path), + '--weightQuantBits', + str(quant_bit), + ] + if asymmetric: + convert_args.append("--weightQuantAsymmetric") + if external_data: + convert_args.append("--saveExternalData") + if bizCode is not None: + convert_args.append("--bizCode") + convert_args.append(str(bizCode)) + MNNTools.mnnconvert(convert_args) + +# some wrapper class for export +class Embedding(torch.nn.Module): + def __init__(self, embed, using_bf16: bool = False): + super().__init__() + self.bf16 = using_bf16 + self.embed_dim = embed.weight.shape[-1] + if using_bf16: + # using bf16 embedding weight + self.embed = embed.bfloat16() + else: + self.embed = embed + + def forward(self, input_ids): + res = self.embed(input_ids) + if self.bf16: + res = res.float() + return res.view(-1, 1, self.embed_dim) + +class Lm(torch.nn.Module): + def __init__(self, lm): + super().__init__() + self.lm = lm + + def forward(self, hidden_states): + m_logits = self.lm(hidden_states) + # token = torch.argmax(m_logits) + return m_logits + +class LLM(torch.nn.Module): + ''' + Base class for all llm model. Inherits from [`torch.nn.Module`]. + ''' + + def __init__(self, args): + super().__init__() + self.quant_bit = 4 + self.asymmetric = True + self.onnx_path = args.onnx_path + self.mnn_path = args.mnn_path + if not os.path.exists(self.onnx_path): + os.makedirs(self.onnx_path) + if not os.path.exists(self.mnn_path): + os.makedirs(self.mnn_path) + self.export_mnn = args.export_mnn + self.export_verbose = args.export_verbose + self.export_test = args.export_test + # default is False, just set True when using below command: + # `python llm_export ../path --export --embed_bin` to export single model without embedding + self.without_embed = False + self.embed_bin = args.embed_bin + if self.embed_bin: + self.embed_bf16 = True + else: + self.embed_bf16 = args.embed_bf16 + self.skip_slim = args.skip_slim + tokenizer_model = os.path.join(args.path, 'tokenizer.model') + ice_text_model = os.path.join(args.path, 'ice_text.model') + try: + if os.path.exists(tokenizer_model): + self.sp_model = spm.SentencePieceProcessor(tokenizer_model) + elif os.path.exists(ice_text_model): + self.sp_model = spm.SentencePieceProcessor(ice_text_model) + else: + self.sp_model = None + except: + self.sp_model = None + merge_file = os.path.join(args.path, 'merges.txt') + if os.path.exists(merge_file): + self.merge_txt = merge_file + else: + self.merge_txt = None + self.stop_ids = [] + self.max_length = 1024 + self.hidden_size = 4096 + self.visual = None # defualt is not visual + self.lora_path = args.lora_path + self.load_hf(args.path) + self.load_model() + self.llm_config = { + 'hidden_size' : self.hidden_size, + 'layer_nums' : self.block_nums, + 'attention_mask': self.attention_mask_type, + 'key_value_shape': self.past_kv_shape[1:], + "prompt_template": self.build_prompt('%s'), + 'is_visual': False + } + + def load_hf(self, model_path: str): + self.tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True) + try: + self.model = AutoModelForCausalLM.from_pretrained(model_path, trust_remote_code=True).float().eval() + except: + self.model = AutoModel.from_pretrained(model_path, trust_remote_code=True).float().eval() + self.config = self.model.config + if self.lora_path is not None: + adapter = PeftModel.from_pretrained(self.model, model_id=self.lora_path) + self.model = adapter.merge_and_unload(progressbar=True) + + def load_model(self): + raise NotImplementedError + + def get_attention_mask(self) -> torch.Tensor: + raise NotImplementedError + + def get_position_ids(self) -> torch.Tensor: + raise NotImplementedError + + def export_vocab(self): + raise NotImplementedError + + def visual_embed(self, input_ids): + raise NotImplementedError + + def __embedding(self, input_ids): + if self.visual is not None and self.token_len == 0: + input_embeds = self.visual_embed(input_ids) + else: + input_embeds = self.embed(input_ids) + return input_embeds + + def __decode(self, hidden_states, attention_mask, position_ids, past_key_values): + presents = [] + for i in range(self.block_nums): + hidden_states, kv = self.blocks[i](hidden_states, attention_mask, position_ids, past_key_values[i]) + presents.append(kv) + logits = self.lm(hidden_states).reshape(-1) + presents = torch.stack(presents) + self.seq_len += 1 #当前序列的长度，自回归时 + self.token_len += 1 #表示处理过的token的个数，用与mask + return logits, presents + + def forward(self, input_ids, attention_mask, position_ids, past_key_values): + if self.without_embed: + return self.__decode(input_ids, attention_mask, position_ids, past_key_values) + return self.__decode(self.__embedding(input_ids), attention_mask, position_ids, past_key_values) + + # some test functions + def build_prompt(self, query): + if hasattr(self.tokenizer, 'build_prompt'): + prompt = self.tokenizer.build_prompt(query) + else: + prompt = query + return prompt + + def str_to_ids(self, prompt): + input_ids = self.tokenizer(prompt, return_tensors="pt")['input_ids'] + return input_ids + + def id_to_str(self, token_id): + word = self.tokenizer._convert_id_to_token(int(token_id)) + word = self.tokenizer.convert_tokens_to_string([word]) + return word + + def response(self, query): + prompt = self.build_prompt(query) + input_ids = self.str_to_ids(prompt) + self.seq_len = input_ids.numel() + self.context_len = self.seq_len - 2 + self.token_len = 0 + past_key_values = [None for i in range(self.block_nums)] + token_id = input_ids + while self.token_len < self.max_length: + attention_mask = self.get_attention_mask() + position_ids = self.get_position_ids() + logits, past_key_values = self.forward(token_id, attention_mask, position_ids, past_key_values) + token_id = torch.argmax(logits) + if token_id in self.stop_ids: + print("", end='\n') + break + word = self.id_to_str(token_id) + print(word, end="", flush=True) + + # some export functions + def assert_equal(self, torch_outs, onnx_outs): + if type(torch_outs) not in (list, tuple): + torch_outs = (torch_outs, ) + onnx_outs = (onnx_outs, ) + same = True + for orig, onnx in zip(torch_outs, onnx_outs): + orig = orig.detach().numpy() + if not np.allclose(orig, onnx, rtol=1e-3, atol=1e-3): + print('Error: onnx outputs dont match original. [shape = {}] onnx: {}, original: {}'.format(onnx.shape, onnx, orig)) + same = False + break + if same: + print('onnx test SUCCESS') + + def export_lm(self): + model = self.lm + hidden_states = torch.randn(1, self.hidden_size) + onnx_model = f'./{self.onnx_path}/lm.onnx' + torch.onnx.export(model, (hidden_states), + onnx_model, + verbose=self.export_verbose, + input_names=['hidden_states'], + output_names=['logits'], + do_constant_folding=True, + opset_version=15) + if not self.skip_slim: + slim(onnx_model, output_model=onnx_model) + # test lm + if self.export_test: + original_outs = model(hidden_states) + ort_session = ort.InferenceSession(onnx_model, providers=['CPUExecutionProvider']) + inputs = { + 'hidden_states' : hidden_states.numpy(), + } + onnx_outs = ort_session.run(None, inputs) + self.assert_equal(original_outs, onnx_outs) + if self.export_mnn: + onnx2mnn(onnx_model, self.mnn_path, self.quant_bit, self.asymmetric) + + def export_visual(self): + if self.visual is None: + return + input_images = torch.randn((1, 3, self.image_size, self.image_size)) + model = self.visual + onnx_model = f'./{self.onnx_path}/visual.onnx' + torch.onnx.export(model, (input_images), + onnx_model, + verbose=self.export_verbose, + input_names=['input_images'], + output_names=['image_embeds'], + dynamic_axes={"input_images": { + 0: "size" + }}, + do_constant_folding=True, + opset_version=15) + if not self.skip_slim: + slim(onnx_model, output_model=onnx_model) + # test + if self.export_test: + original_outs = model(input_images) + ort_session = ort.InferenceSession(onnx_model, providers=['CPUExecutionProvider']) + inputs = { + 'input_images' : input_images.numpy(), + } + onnx_outs = ort_session.run(None, inputs)[0] + self.assert_equal(original_outs, onnx_outs) + if self.export_mnn: + onnx2mnn(onnx_model, self.mnn_path) + + def export_embed(self): + model = self.embed + if self.embed_bin: + import ctypes + tensor_data = model.embed.weight.data + data_ptr = tensor_data.untyped_storage().data_ptr() + buffer = (ctypes.c_byte * (tensor_data.numel() * 2)).from_address(data_ptr) + with open(f'./{self.onnx_path}/embeddings_bf16.bin', 'wb') as f: + f.write(buffer) + return + input_ids = torch.arange(3, dtype=torch.long) + onnx_model = f'./{self.onnx_path}/embedding.onnx' + torch.onnx.export(model, (input_ids), + onnx_model, + verbose=self.export_verbose, + input_names=['input_ids'], + output_names=['inputs_embeds'], + dynamic_axes={"input_ids": { + 0: "length" + }}, + do_constant_folding=True, + opset_version=15) + if not self.skip_slim: + slim(onnx_model, output_model=onnx_model) + # test + if self.export_test: + original_outs = model(input_ids) + ort_session = ort.InferenceSession(onnx_model, providers=['CPUExecutionProvider']) + inputs = { + 'input_ids' : input_ids.numpy(), + } + onnx_outs = ort_session.run(None, inputs) + self.assert_equal(original_outs, onnx_outs) + if self.export_mnn: + onnx2mnn(onnx_model, self.mnn_path) + + def export_block(self, block_id: int): + self.seq_len = 3 + self.token_len = 0 + inputs_embeds = torch.randn((self.seq_len, 1, self.hidden_size)) + attention_mask = self.get_attention_mask() + position_ids = self.get_position_ids() + past_key_values = torch.zeros(self.past_kv_shape[1:]) + model = self.blocks[block_id] + onnx_model = f'./{self.onnx_path}/block_{block_id}.onnx' + torch.onnx.export( + model, (inputs_embeds, attention_mask, position_ids, past_key_values), + onnx_model, + verbose=self.export_verbose, + input_names=[ + 'inputs_embeds', 'attention_mask', 'position_ids', 'past_key_values' + ], + output_names=['hidden_states', 'presents'], + dynamic_axes=self.block_dynamic_axes, + do_constant_folding=True, + opset_version=15) + if not self.skip_slim: + slim(onnx_model, output_model=onnx_model) + if self.export_test: + original_outs = model(inputs_embeds, attention_mask, position_ids, past_key_values) + ort_session = ort.InferenceSession(onnx_model, providers=['CPUExecutionProvider']) + inputs = { + 'inputs_embeds' : inputs_embeds.detach().numpy(), + 'attention_mask' : attention_mask.numpy(), + 'position_ids' : position_ids.numpy(), + 'past_key_values' : past_key_values.numpy() + } + onnx_outs = ort_session.run(None, inputs) + self.assert_equal(original_outs, onnx_outs) + if self.export_mnn: + onnx2mnn(onnx_model, self.mnn_path, self.quant_bit, self.asymmetric) + + def export_blocks(self): + for i in range(self.block_nums): + self.export_block(i) + + def export_config(self, is_single = True): + self.llm_config['is_single'] = is_single + with open(f'./{self.onnx_path}/llm_config.json', 'w', encoding='utf-8') as f: + json.dump(self.llm_config, f, ensure_ascii=False, indent=4) + + def export(self): + model = self + self.seq_len = 3 #举例输入长度3，当前，后面自回归会增加的 + self.token_len = 0 + input_ids = torch.arange(3, dtype=torch.long) + attention_mask = self.get_attention_mask() + position_ids = self.get_position_ids() + past_key_values = torch.zeros(self.past_kv_shape) + onnx_model = f'./{self.onnx_path}/llm.onnx' + if self.embed_bin: + self.without_embed = True + input_ids = self.__embedding(input_ids) + print('export start ...') + torch.onnx.export( + model, (input_ids, attention_mask, position_ids, past_key_values), + onnx_model, + verbose=self.export_verbose, + input_names=[ + 'input_ids', 'attention_mask', 'position_ids', 'past_key_values' + ], + output_names=['logits', 'presents'], + dynamic_axes=self.model_dynamic_axes, + do_constant_folding=True, + opset_version=15) + print('export done!') + if not self.skip_slim: + slim(onnx_model, output_model=onnx_model) + for file_path in glob.glob(f'./{self.onnx_path}/onnx__*'): + try: + os.remove(file_path) + except FileNotFoundError: + pass + for file_path in glob.glob(f'./{self.onnx_path}/model.*'): + try: + os.remove(file_path) + except FileNotFoundError: + pass + if self.export_test: + # test + original_outs = model(input_ids, attention_mask, position_ids, past_key_values) + ort_session = ort.InferenceSession(onnx_model, providers=['CPUExecutionProvider']) + inputs = { + 'input_ids' : input_ids.detach().numpy(), + 'attention_mask' : attention_mask.numpy(), + 'position_ids' : position_ids.numpy(), + 'past_key_values' : past_key_values.numpy() + } + onnx_outs = ort_session.run(None, inputs) + self.assert_equal(original_outs, onnx_outs) + if self.export_mnn: + # single model is > 2G, using external_data + onnx2mnn(onnx_model, self.mnn_path, self.quant_bit, self.asymmetric, True) + if self.without_embed: + self.without_embed = False + + def export_tokenizer(self): + # TOKENIZER MAGIC NUMBER + MAGIC_NUMBER = 430 + # TOKENIZER TYPE + SENTENCEPIECE = 0; TIKTOIKEN = 1; BERT = 2; HUGGINGFACE = 3 + def write_line(fp, *args): + for arg in args: + for token in arg: + fp.write(str(token) + ' ') + fp.write('\n') + def write_header(fp, type, speicals, prefix = []): + fp.write(f'{MAGIC_NUMBER} {type}\n') + fp.write(f'{len(speicals)} {len(self.stop_ids)} {len(prefix)}\n') + write_line(fp, speicals, self.stop_ids, prefix) + + file_path = os.path.join(self.onnx_path, "tokenizer.txt") + special_list = list(self.tokenizer.added_tokens_decoder.keys()) + if hasattr(self.tokenizer, 'special_tokens'): + for k, v in self.tokenizer.special_tokens.items(): + special_list.append(v) + if hasattr(self.tokenizer, 'gmask_token_id'): + special_list.append(self.tokenizer.gmask_token_id) + vocab_list = [] + prefix_list = [] + if hasattr(self.tokenizer, 'get_prefix_tokens'): + prefix_list = self.tokenizer.get_prefix_tokens() + if self.sp_model is not None: + # senetencepiece + print('# senetencepiece tokenier') + NORMAL = 1; UNKNOWN = 2; CONTROL = 3 + USER_DEFINED = 4; UNUSED = 5; BYTE = 6 + for i in range(self.sp_model.GetPieceSize()): + token = self.sp_model.IdToPiece(i) + score = self.sp_model.GetScore(i) + type = NORMAL + if self.sp_model.IsUnknown(i): + type = UNKNOWN + elif self.sp_model.IsControl(i): + type = CONTROL + elif self.sp_model.IsUnused(i): + type = UNUSED + elif self.sp_model.IsByte(i): + type = BYTE + if self.model_name == 'Chatglm_6b': + if '' in token: token = '\n' + if '<|tab|>' in token: token = '\t' + if '<|blank_' in token: token = ' ' * int(token[8:token.find('|>')]) + if '▁' in token: token = token.replace('▁', ' ') + token_encode = base64.b64encode(token.encode("utf-8")).decode("utf8") + vocab_list.append(f'{token_encode} {score} {type}\n') + with open(file_path, "w", encoding="utf8") as fp: + write_header(fp, SENTENCEPIECE, special_list, prefix_list) + fp.write(f'{len(vocab_list)}\n') + for vocab in vocab_list: + fp.write(vocab) + elif hasattr(self.tokenizer, 'mergeable_ranks'): + print('# tiktoken tokenier') + # tikton + vocab_list = [] + for k, v in self.tokenizer.mergeable_ranks.items(): + line = base64.b64encode(k).decode("utf8") + "\n" + vocab_list.append(line) + if hasattr(self.tokenizer, 'special_tokens'): + for k, v in self.tokenizer.special_tokens.items(): + line = base64.b64encode(k.encode("utf-8")).decode("utf8") + "\n" + vocab_list.append(line) + if hasattr(self.tokenizer, 'added_tokens_decoder'): + for k, v in self.tokenizer.added_tokens_decoder.items(): + line = base64.b64encode(v.__str__().encode("utf-8")).decode("utf8") + "\n" + vocab_list.append(line) + with open(file_path, "w", encoding="utf8") as fp: + write_header(fp, TIKTOIKEN, special_list, prefix_list) + fp.write(f'{len(vocab_list)}\n') + for vocab in vocab_list: + fp.write(vocab) + elif self.merge_txt is not None: + # huggingface tokenizer + merge_list = [] + vocab = self.tokenizer.get_vocab() + special_list = list(self.tokenizer.added_tokens_decoder.keys()) + vocab_list = ['' for i in range(len(vocab))] + # load vocab + for k, v in vocab.items(): + vocab_list[int(v)] = k + # load merge + with open(self.merge_txt, 'rt') as merge: + for line in merge.readlines(): + merge_list.append(line) + # write to tokenizer.txt + with open(file_path, "w", encoding="utf8") as fp: + write_header(fp, HUGGINGFACE, special_list) + fp.write(f'{len(vocab_list)} {len(merge_list)}\n') + for v in vocab_list: + fp.write(v + '\n') + for m in merge_list: + fp.write(m) + else: + print('# other tiktoken tokenier') + # other tikton + def unicode_to_byte(u: int): + if u >= 256 and u <= 288: + return u - 256 + if u >= 289 and u <= 322: + return u - 162 + if u == 323: + return 173 + if u == 65372: # | + return 124 + if u == 9601: # _ + return 95 + return u + vocab = self.tokenizer.get_vocab() + vocab_list = ['' for i in range(len(vocab))] + for k, v in vocab.items(): + try: + vocab_list[int(v)] = bytes([unicode_to_byte(ord(c)) for c in k]).decode('utf-8', errors='ignore') + except: + vocab_list[int(v)] = k + special_list = list(self.tokenizer.added_tokens_decoder.keys()) + with open(file_path, "w", encoding="utf8") as fp: + write_header(fp, TIKTOIKEN, special_list) + fp.write(f'{len(vocab_list)}\n') + for v in vocab_list: + line = base64.b64encode(v.encode('utf-8')).decode("utf8") + "\n" + fp.write(line) + +# chatglm +class GLMBlock(torch.nn.Module): + def __init__(self, block, block_id, final_layernorm = None): + super().__init__() + self.block = block + self.block_id = block_id + self.hidden_size = 4096 + self.final_layernorm = final_layernorm + + def forward(self, hidden_states, attention_mask, position_ids, past_kv): + hidden_states, presents = self.block(hidden_states, + position_ids, + attention_mask, + self.block_id, + past_kv, + use_cache=True) + if self.final_layernorm is not None: + hidden_states = self.final_layernorm(hidden_states) + hidden_states = hidden_states.view(-1, self.hidden_size)[-1].view(1, 1, self.hidden_size) + if isinstance(presents, tuple): + presents = torch.stack(presents) + return hidden_states, presents + +class Chatglm_6b(LLM): + def __init__(self, args): + self.attention_mask_type = 'glm' + self.model_name = 'Chatglm_6b' + super().__init__(args) + + def load_model(self): + transformer = self.model.transformer + self.lm_ = self.model.lm_head + self.embed_ = transformer.word_embeddings + self.blocks_ = transformer.layers + self.final_layernorm_ = transformer.final_layernorm + # some wrapper + self.stop_ids.append(self.tokenizer._convert_token_to_id(self.tokenizer.eos_token)) + self.block_nums = len(self.blocks_) + self.lm = Lm(self.lm_) + # chatglm embedding and lm using same param, copy embedding when using bf16 + if self.embed_bf16: + import copy + embed_copy = copy.deepcopy(self.embed_) + self.embed = Embedding(embed_copy, self.embed_bf16) + else: + self.embed = Embedding(self.embed_, self.embed_bf16) + self.blocks = [GLMBlock(self.blocks_[i], i, self.final_layernorm_ if i == len(self.blocks_) - 1 else None) for i in range(self.block_nums)] + # some config for export + self.past_kv_shape = [28, 2, 0, 1, 32, 128] + self.block_dynamic_axes = { + "inputs_embeds" : { 0: "seq_len" }, + "attention_mask" : { 2: "seq_len", 3: "seq_len" }, + "position_ids" : { 2: "seq_len" }, + "past_key_values" : { 1: "history_len" } + } + self.model_dynamic_axes = { + "input_ids" : { 0: "seq_len" }, + "attention_mask" : { 2: "seq_len", 3: "seq_len" }, + "position_ids" : { 2: "seq_len" }, + "past_key_values" : { 2: "history_len" } + } + + def get_attention_mask(self) -> torch.Tensor: + if self.token_len: + return torch.zeros([1]).bool().reshape([1, 1, 1, 1]) + attention_mask = torch.zeros([self.seq_len, self.seq_len], dtype=torch.bool) + for i in range(self.seq_len - 1): + attention_mask[i][-1] = True + attention_mask = attention_mask.reshape([1, 1, self.seq_len, self.seq_len]) + return attention_mask + + def get_position_ids(self) -> torch.Tensor: + if self.token_len: + return torch.tensor([self.context_len, self.token_len + 1]).reshape([1, 2, 1]) + position_ids_0 = torch.arange(self.seq_len, dtype=torch.long) + position_ids_1 = torch.zeros(self.seq_len, dtype=torch.long) + position_ids_0[-1] = position_ids_0[-2] + position_ids_1[-1] = 1 + position_ids = torch.stack([position_ids_0, position_ids_1]).view(1, 2, -1) + return position_ids + + def build_prompt(self, query): + return f'{query}[gMASK]' + +# chatglm2 +class GLM2Block(torch.nn.Module): + def __init__(self, block, block_id, config, final_layernorm = None): + super().__init__() + self.block = block + self.block_id = block_id + self.final_layernorm = final_layernorm + self.config = config + self.hidden_size = 4096 + + def forward(self, hidden_states, attention_mask, position_ids, past_kv): + rope_ratio = self.config.rope_ratio + base = 10000 * rope_ratio + theta = 1.0 / (base ** (torch.arange(0, 64, 2, dtype=torch.float32) / 64)) + position_ids = position_ids.float().reshape(-1, 1) + idx_theta = position_ids * theta + rotary_pos_emb = torch.stack([torch.cos(idx_theta), torch.sin(idx_theta)], dim=-1).unsqueeze(0).contiguous() + hidden_states, presents = self.block(hidden_states, + attention_mask, + kv_cache=past_kv, + rotary_pos_emb=rotary_pos_emb) + if self.final_layernorm is not None: + hidden_states = self.final_layernorm(hidden_states) + hidden_states = hidden_states.view(-1, self.hidden_size)[-1].view(1, 1, self.hidden_size) + if isinstance(presents, tuple): + presents = torch.stack(presents) + return hidden_states, presents + +class Chatglm2_6b(LLM): + def __init__(self, args): + self.attention_mask_type = 'glm2' + super().__init__(args) + self.model_name = 'Chatglm2_6b' + if 'codegeex2-6b' in args.path: + self.model_name = 'Codegeex2_6b' + + def load_model(self): + transformer = self.model.transformer + self.lm_ = transformer.output_layer + self.embed_ = transformer.embedding.word_embeddings + self.blocks_ = transformer.encoder.layers + self.final_layernorm_ = transformer.encoder.final_layernorm + # some wrapper + if self.tokenizer.eos_token_id is None: + # codegeex2-6b + self.stop_ids.append(self.tokenizer.tokenizer.eos_id) + else: + self.stop_ids.append(self.tokenizer.eos_token_id) + if hasattr(self.config, 'eos_token_id'): + if type(self.config.eos_token_id) is list: + for eos_id in self.config.eos_token_id: + self.stop_ids.append(eos_id) + elif type(self.config.eos_token_id) is int: + self.stop_ids.append(self.config.eos_token_id) + self.block_nums = len(self.blocks_) + self.embed = Embedding(self.embed_, self.embed_bf16) + self.lm = Lm(self.lm_) + self.blocks = [GLM2Block(self.blocks_[i], i, self.config, self.final_layernorm_ if i == len(self.blocks_) - 1 else None) for i in range(self.block_nums)] + # some config for export + self.past_kv_shape = [28, 2, 0, 1, 2, 128] + self.block_dynamic_axes = { + "inputs_embeds" : { 0: "seq_len" }, + "attention_mask" : { 2: "seq_len", 3: "seq_len" }, + "position_ids" : { 0: "seq_len" }, + "past_key_values" : { 1: "history_len" } + } + self.model_dynamic_axes = { + "input_ids" : { 0: "seq_len" }, + "attention_mask" : { 2: "seq_len", 3: "seq_len" }, + "position_ids" : { 0: "seq_len" }, + "past_key_values" : { 2: "history_len" } + } + num_layers = self.config.num_layers + if num_layers > 28: + self.past_kv_shape = [num_layers, 2, 1, 2, 0, 128] + self.block_dynamic_axes = { + "inputs_embeds" : { 0: "seq_len" }, + "attention_mask" : { 2: "seq_len", 3: "seq_len" }, + "position_ids" : { 0: "seq_len" }, + "past_key_values" : { 3: "history_len" } + } + self.model_dynamic_axes = { + "input_ids" : { 0: "seq_len" }, + "attention_mask" : { 2: "seq_len", 3: "seq_len" }, + "position_ids" : { 0: "seq_len" }, + "past_key_values" : { 4: "history_len" } + } + + def get_attention_mask(self) -> torch.Tensor: + if self.token_len: + return torch.zeros([1, 1, 1, 1]).bool() + attention_mask = ~torch.tril(torch.ones([1, 1, self.seq_len, self.seq_len]).bool()) + return attention_mask + + def get_position_ids(self) -> torch.Tensor: + if self.token_len: + return torch.tensor([self.token_len], dtype=torch.long) + return torch.arange(self.seq_len, dtype=torch.long) + +# chatglm3 +class Chatglm3_6b(Chatglm2_6b): + def __init__(self, args): + super().__init__(args) + self.model_name = 'Chatglm3_6b' + + def build_prompt(self, query): + return f'<|user|>\n{query}\n<|assistant|>\n' + +# qwen +class QWENBlock(torch.nn.Module): + def __init__(self, name, block, block_id, hidden_size, final_layernorm = None): + super().__init__() + self.name = name + self.block = block + self.block_id = block_id + self.final_layernorm = final_layernorm + self.hidden_size = hidden_size + + def forward(self, hidden_states, attention_mask, position_ids, past_kv): + theta = 1.0 / (10000.0 ** (torch.arange(0, 128, 2, dtype=torch.float32) / 128)) + position_ids = position_ids.float().reshape(-1, 1) + idx_theta = position_ids * theta + rotary_pos_emb = torch.cat((idx_theta, idx_theta), dim=-1) + rotary_pos_emb = rotary_pos_emb.unsqueeze(1).unsqueeze(0) + if self.name != 'Qwen-7B': + rotary_pos_emb = torch.stack([torch.cos(rotary_pos_emb), torch.sin(rotary_pos_emb)]) + hidden_states = hidden_states.view(1, -1, self.hidden_size) + hidden_states, presents = self.block(hidden_states=hidden_states, + layer_past=past_kv, + attention_mask=attention_mask, + rotary_pos_emb=rotary_pos_emb, + use_cache=True) + if self.final_layernorm is not None: + hidden_states = self.final_layernorm(hidden_states) + hidden_states = hidden_states.view(-1, self.hidden_size)[-1].view(1, 1, self.hidden_size) + if isinstance(presents, tuple): + presents = torch.stack(presents) + return hidden_states, presents + +class QWEN18Block(torch.nn.Module): + def __init__(self, block, block_id, hidden_size, final_layernorm = None): + super().__init__() + self.block = block + self.block_id = block_id + self.final_layernorm = final_layernorm + self.hidden_size = hidden_size + + def forward(self, hidden_states, attention_mask, position_ids, past_kv): + theta = 1.0 / (10000.0 ** (torch.arange(0, 128, 2, dtype=torch.float32) / 128)) + position_ids = position_ids.float().reshape(-1, 1) + idx_theta = position_ids * theta + rotary_pos_emb = torch.cat((idx_theta, idx_theta), dim=-1).unsqueeze(1).unsqueeze(0) + rotary_pos_emb = torch.stack([torch.cos(rotary_pos_emb), torch.sin(rotary_pos_emb)]) + hidden_states = hidden_states.view(1, -1, self.hidden_size) + hidden_states, presents = self.block(hidden_states, + rotary_pos_emb, + past_kv, + attention_mask, + use_cache=True) + if self.final_layernorm is not None: + hidden_states = self.final_layernorm(hidden_states) + hidden_states = hidden_states.view(-1, self.hidden_size)[-1].view(1, 1, self.hidden_size) + if isinstance(presents, tuple): + presents = torch.stack(presents) + return hidden_states, presents + +class Qwen_Chat(LLM): + def __init__(self, args): + self.attention_mask_type = 'int' + super().__init__(args) + if 'VL' in self.model_name: + self.llm_config['is_visual'] = True + self.llm_config['attention_mask'] = 'float' + self.llm_config['img_size'] = 448 + self.llm_config['imgpad_len'] = 256 + self.llm_config['img_start'] = self.tokenizer.img_start_id + self.llm_config['img_end'] = self.tokenizer.img_end_id + self.llm_config['img_pad'] = self.tokenizer.img_pad_id + + + def load_model(self): + # Qwen models + self.model_name = 'Qwen-7B' + if '1_8' in model_path: + self.model_name = 'Qwen-1_8b' + if 'VL' in model_path: + self.model_name = 'Qwen-VL' + transformer = self.model.transformer + self.lm_ = self.model.lm_head + self.embed_ = transformer.wte + self.blocks_ = transformer.h + self.final_layernorm_ = transformer.ln_f + if hasattr(transformer, 'visual'): + self.visual = transformer.visual + self.image_start_id = transformer.config.visual['image_start_id'] + self.image_size = transformer.config.visual['image_size'] + # some wrapper + self.stop_ids.append(self.tokenizer.im_end_id) + self.block_nums = len(self.blocks_) + self.hidden_size = transformer.embed_dim + self.embed = Embedding(self.embed_, self.embed_bf16) + self.lm = Lm(self.lm_) + self.blocks = [QWENBlock(self.model_name, self.blocks_[i], i, self.hidden_size, self.final_layernorm_ if i == len(self.blocks_) - 1 else None) for i in range(self.block_nums)] + if self.block_nums == 32: + # qwen-7b, qwen-vl + self.past_kv_shape = [32, 2, 1, 0, 32, 128] + elif self.block_nums == 24: + # qwen-1.8b + self.past_kv_shape = [24, 2, 1, 0, 16, 128] + # some config for export + self.block_dynamic_axes = { + "inputs_embeds" : { 0: "seq_len" }, + "attention_mask" : { 2: "seq_len", 3: "seq_len" }, + "position_ids" : { 0: "seq_len" }, + "past_key_values" : { 2: "history_len" } + } + self.model_dynamic_axes = { + "input_ids" : { 0: "seq_len" }, + "attention_mask" : { 2: "seq_len", 3: "seq_len" }, + "position_ids" : { 0: "seq_len" }, + "past_key_values" : { 3: "history_len" } + } + + def build_prompt(self, query): + return f'\n<|im_start|>user\n{query}<|im_end|>\n<|im_start|>assistant\n' + + def get_attention_mask(self) -> torch.Tensor: + if self.model_name == 'Qwen-VL': + if self.token_len: + return torch.zeros([1, 1, 1, 1], dtype=torch.float32) + return (1 - torch.tril(torch.ones([1, 1, self.seq_len, self.seq_len]))) * torch.finfo(torch.float32).min + if self.token_len: + return torch.ones([1, 1, 1, 1]).bool() + return torch.tril(torch.ones([1, 1, self.seq_len, self.seq_len]).bool()) + + def get_position_ids(self) -> torch.Tensor: + if self.token_len: + return torch.tensor([self.seq_len - 1], dtype=torch.long) + return torch.arange(self.seq_len, dtype=torch.long) + + def visual_embed(self, input_ids): + if not torch.any(input_ids == self.image_start_id): + return self.embed(input_ids) + bos_pos = torch.where(input_ids == self.image_start_id) + eos_pos = torch.where(input_ids == self.image_start_id + 1) + img_pos = torch.stack((bos_pos[0], bos_pos[1], eos_pos[1]), dim=1) + images = [] + for i, a, b in img_pos: + image = input_ids[i][a + 1 : b - 1].tolist() + image = image[ : image.index(self.image_start_id + 2)] + images.append(bytes(image).decode('utf-8')) + images = self.visual.encode(images) + hidden_states = self.embed(input_ids).view(1, -1, self.hidden_size) + for idx, (i, a, b) in enumerate(img_pos): + hidden_states[i][a + 1 : b] = images[idx] + return hidden_states.view(-1, 1, self.hidden_size) + +class QWEN2Block(torch.nn.Module): + def __init__(self, name, block, block_id, config, final_layernorm = None): + super().__init__() + self.name = name + self.block = block + self.block_id = block_id + self.final_layernorm = final_layernorm + self.hidden_size = config.hidden_size + self.head_dim = config.hidden_size // config.num_attention_heads + self.rope_theta = config.rope_theta + + def forward(self, hidden_states, attention_mask, position_ids, past_kv): + theta = 1.0 / (self.rope_theta ** (torch.arange(0, self.head_dim, 2, dtype=torch.float32) / self.head_dim)) + position_ids = position_ids.float().reshape(-1, 1) + idx_theta = position_ids * theta + rotary_pos_emb = torch.cat((idx_theta, idx_theta), dim=-1) + rotary_pos_emb = rotary_pos_emb.unsqueeze(1).unsqueeze(0) + rotary_pos_emb = torch.stack([torch.cos(rotary_pos_emb), torch.sin(rotary_pos_emb)]) + hidden_states = hidden_states.view(1, -1, self.hidden_size) + hidden_states, presents = self.block(hidden_states=hidden_states, + attention_mask=attention_mask, + past_key_value=past_kv, + rotary_pos_emb=rotary_pos_emb, + use_cache=True) + + if self.final_layernorm is not None: + hidden_states = self.final_layernorm(hidden_states) + hidden_states = hidden_states.view(-1, self.hidden_size)[-1].view(1, 1, self.hidden_size) + if isinstance(presents, tuple): + presents = torch.stack(presents) + # print('###', presents.shape) + return hidden_states, presents + +class Qwen2_Chat(LLM): + def __init__(self, args): + self.attention_mask_type = 'float' + super().__init__(args) + + def load_model(self): + # Qwen2 models + self.model_name = 'Qwen2' + transformer = self.model.model + self.lm_ = self.model.lm_head + self.embed_ = transformer.embed_tokens + self.blocks_ = transformer.layers + self.final_layernorm_ = transformer.norm + # some wrapper + self.stop_ids.append(self.tokenizer.eos_token_id) + if hasattr(self.model, 'generation_config'): + for id in self.model.generation_config.eos_token_id: + self.stop_ids.append(id) + self.block_nums = self.config.num_hidden_layers + self.hidden_size = self.config.hidden_size + self.num_heads = self.config.num_attention_heads + self.kv_heads = self.config.num_key_value_heads + self.rope_theta = self.config.rope_theta + self.head_dim = self.hidden_size // self.num_heads + if self.embed_.weight is self.lm_.weight: + import copy + embed_copy = copy.deepcopy(self.embed_) + self.embed = Embedding(embed_copy, self.embed_bf16) + else: + self.embed = Embedding(self.embed_, self.embed_bf16) + self.lm = Lm(self.lm_) + self.past_kv_shape = [self.block_nums, 2, 1, 0, self.kv_heads, self.head_dim] + self.blocks = [QWEN2Block(self.model_name, self.blocks_[i], i, self.config, self.final_layernorm_ if i == len(self.blocks_) - 1 else None) for i in range(self.block_nums)] + # some config for export + self.block_dynamic_axes = { + "inputs_embeds" : { 0: "seq_len" }, + "attention_mask" : { 2: "seq_len", 3: "seq_len" }, + "position_ids" : { 0: "seq_len" }, + "past_key_values" : { 1: "history_len" } + } + self.model_dynamic_axes = { + "input_ids" : { 0: "seq_len" }, + "attention_mask" : { 2: "seq_len", 3: "seq_len" }, + "position_ids" : { 0: "seq_len" }, + "past_key_values" : { 2: "history_len" } + } + + def build_prompt(self, query): + return f'<|im_start|>user\n{query}<|im_end|>\n<|im_start|>assistant\n' + + def get_attention_mask(self) -> torch.Tensor: + if self.token_len: + return torch.zeros([1, 1, 1, self.seq_len], dtype=torch.float32) + return (1 - torch.tril(torch.ones([1, 1, self.seq_len, self.seq_len]))) * torch.finfo(torch.float32).min + + + def get_position_ids(self) -> torch.Tensor: + if self.token_len: + return torch.tensor([[self.seq_len - 1]], dtype=torch.long) + return torch.arange(self.seq_len, dtype=torch.long).unsqueeze(0) + + def visual_embed(self, input_ids): + if not torch.any(input_ids == self.image_start_id): + return self.embed(input_ids) + bos_pos = torch.where(input_ids == self.image_start_id) + eos_pos = torch.where(input_ids == self.image_start_id + 1) + img_pos = torch.stack((bos_pos[0], bos_pos[1], eos_pos[1]), dim=1) + images = [] + for i, a, b in img_pos: + image = input_ids[i][a + 1 : b - 1].tolist() + image = image[ : image.index(self.image_start_id + 2)] + images.append(bytes(image).decode('utf-8')) + images = self.visual.encode(images) + hidden_states = self.embed(input_ids).view(1, -1, self.hidden_size) + for idx, (i, a, b) in enumerate(img_pos): + hidden_states[i][a + 1 : b] = images[idx] + return hidden_states.view(-1, 1, self.hidden_size) + +# llama2 +class LLAMA2Block(torch.nn.Module): + def __init__(self, block, block_id, hidden_size, head_dim, final_layernorm = None): + super().__init__() + self.block = block + self.block_id = block_id + self.head_dim = head_dim + self.final_layernorm = final_layernorm + self.hidden_size = hidden_size + + def forward(self, hidden_states, attention_mask, position_ids, past_kv): + theta = 1.0 / (10000.0 ** (torch.arange(0, self.head_dim, 2, dtype=torch.float32) / self.head_dim)) + position_ids = position_ids.float().reshape(-1, 1) + idx_theta = position_ids * theta + rotary_pos_emb = torch.cat((idx_theta, idx_theta), dim=-1) + rotary_pos_emb = rotary_pos_emb.unsqueeze(1).unsqueeze(0) + rotary_pos_emb = torch.stack([torch.cos(rotary_pos_emb), torch.sin(rotary_pos_emb)]) + hidden_states = hidden_states.view(1, -1, self.hidden_size) + position_ids = position_ids.view(1, -1) + hidden_states, presents = self.block(hidden_states, + attention_mask, + position_ids, + past_kv, + rotary_pos_emb=rotary_pos_emb, + use_cache=True) + if self.final_layernorm is not None: + hidden_states = self.final_layernorm(hidden_states) + hidden_states = hidden_states.view(-1, self.hidden_size)[-1].view(1, 1, self.hidden_size) + if isinstance(presents, tuple): + presents = torch.stack(presents) + return hidden_states, presents + +class Llama2_7b_Chat(LLM): + def __init__(self, args): + self.attention_mask_type = 'float' + self.model_name = 'Llama2_7b' + if 'Baichuan2' in args.path: + self.model_name = 'Baichuan2_7B' + if 'internlm' in args.path: + self.model_name = 'Internlm_7b' + if 'TinyLlama' in args.path: + self.model_name = 'TinyLlama' + if 'Yi' in args.path: + self.model_name = 'Yi' + if 'deepseek' in args.path: + self.model_name = 'deepseek' + if 'Llama-3' in args.path: + self.model_name = 'Llama3_8B' + super().__init__(args) + + def load_model(self): + self.config = self.model.config + transformer = self.model.model + self.lm_ = self.model.lm_head + self.embed_ = transformer.embed_tokens + self.blocks_ = transformer.layers + self.final_layernorm_ = transformer.norm + # some wrapper + self.hidden_size = self.embed_.weight.shape[-1] + self.stop_ids.append(self.tokenizer.eos_token_id) + if hasattr(self.model, 'generation_config'): + self.stop_ids.append(self.model.generation_config.eos_token_id) + if self.model_name == 'Llama3_8B': + self.stop_ids.append(self.tokenizer.convert_tokens_to_ids("<|eot_id|>")) + self.block_nums = len(self.blocks_) + self.embed = Embedding(self.embed_, self.embed_bf16) + self.lm = Lm(self.lm_) + self.block_nums = self.config.num_hidden_layers + self.hidden_size = self.config.hidden_size + self.num_attention_heads = self.config.num_attention_heads + self.head_dim = self.hidden_size // self.num_attention_heads + if hasattr(self.config, 'num_key_value_heads'): + self.num_key_value_heads = self.config.num_key_value_heads + else: + self.num_key_value_heads = self.config.num_attention_heads + self.blocks = [LLAMA2Block(self.blocks_[i], i, self.hidden_size, self.head_dim, self.final_layernorm_ if i == len(self.blocks_) - 1 else None) for i in range(self.block_nums)] + self.past_kv_shape = [self.block_nums, 2, 1, 0, self.num_key_value_heads, self.head_dim] + self.block_dynamic_axes = { + "inputs_embeds" : { 0: "seq_len" }, + "attention_mask" : { 2: "seq_len", 3: "seq_len" }, + "position_ids" : { 1: "seq_len" }, + "past_key_values" : { 2: "history_len" } + } + self.model_dynamic_axes = { + "input_ids" : { 0: "seq_len" }, + "attention_mask" : { 2: "seq_len", 3: "seq_len" }, + "position_ids" : { 1: "seq_len" }, + "past_key_values" : { 3: "history_len" } + } + + def build_prompt(self, query): + if 'Baichuan2' in self.model_name: + return f'{query}' + if 'Internlm_7b' in self.model_name: + return f'<|User|>:{query}\n<|Bot|>:' + if 'TinyLlama' in self.model_name: + return f'<|system|>\nYou are a friendly chatbot who always responds in the style of a pirate\n<|user|>\n{query}\n<|assistant|>\n' + if 'Yi' in self.model_name: + return f'<|im_start|> user\n{query}<|im_end|>\n<|im_start|> assistant\n' + if 'deepseek' in self.model_name: + return f'<|begin_of_sentence|>User: {query}\n\nAssistant:' + if 'Llama3' in self.model_name: + return f'<|begin_of_text|><|start_header_id|>user<|end_header_id|>\n\n{query}<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n' + return f'[INST]{query}[/INST]' + + def get_attention_mask(self) -> torch.Tensor: + if self.token_len: + return torch.zeros([1, 1, 1, self.seq_len], dtype=torch.float32) + return (1 - torch.tril(torch.ones([1, 1, self.seq_len, self.seq_len]))) * torch.finfo(torch.float32).min + + def get_position_ids(self) -> torch.Tensor: + if self.token_len: + return torch.tensor([[self.seq_len - 1]], dtype=torch.long) + return torch.arange(self.seq_len, dtype=torch.long).unsqueeze(0) + +# phi-2 +class PHI2Block(torch.nn.Module): + def __init__(self, block, block_id, hidden_size): + super().__init__() + self.block = block + self.block_id = block_id + self.hidden_size = hidden_size + + def forward(self, hidden_states, attention_mask, position_ids, past_kv): + theta = 1.0 / (10000 ** (torch.arange(0, 32, 2, dtype=torch.float32) / 32)) + position_ids = position_ids.float().reshape(-1, 1) + idx_theta = position_ids * theta + rotary_pos_emb = torch.stack([torch.cos(idx_theta), torch.sin(idx_theta)], dim=0).contiguous() + hidden_states = hidden_states.view(1, -1, self.hidden_size) + hidden_states, presents = self.block(hidden_states, + past_kv, + rotary_pos_emb=rotary_pos_emb, + causal_mask=attention_mask + ) + if self.block_id == 31: + hidden_states = hidden_states[:, -1, :] + return hidden_states, presents + +class phi_2(LLM): + def __init__(self, args): + self.attention_mask_type = 'glm' + super().__init__(args) + self.model_name = 'phi-2' + self.asymmetric = False # TODO: some precision bug when using asymmetric + + def load_model(self): + transformer = self.model.transformer + self.lm_ = self.model.lm_head + self.embed_ = transformer.embd.wte + self.hidden_size = self.embed_.weight.shape[-1] + self.blocks_ = transformer.h + # self.final_layernorm_ = transformer.final_layernorm + # some wrapper + self.stop_ids.append(self.tokenizer.eos_token_id) + self.block_nums = len(self.blocks_) + self.embed = Embedding(self.embed_, self.embed_bf16) + self.lm = Lm(self.lm_) + self.blocks = [PHI2Block(self.blocks_[i], i, self.hidden_size) for i in range(self.block_nums)] + # some config for export + self.past_kv_shape = [len(self.blocks), 1, 0, 2, 32, 80] + self.block_dynamic_axes = { + "inputs_embeds" : { 0: "seq_len" }, + "attention_mask" : { 2: "seq_len", 3: "seq_len" }, + "position_ids" : { 0: "seq_len" }, + "past_key_values" : { 1: "history_len" } + } + self.model_dynamic_axes = { + "input_ids" : { 0: "seq_len" }, + "attention_mask" : { 2: "seq_len", 3: "seq_len" }, + "position_ids" : { 0: "seq_len" }, + "past_key_values" : { 2: "history_len" } + } + + def build_prompt(self, query): + return f'Instruct: {query}\nOutput:' + + def get_attention_mask(self) -> torch.Tensor: + if self.token_len: + return torch.zeros([1, 1, 1, 1]).bool() + attention_mask = ~torch.tril(torch.ones([1, 1, self.seq_len, self.seq_len]).bool()) + return attention_mask + + def get_position_ids(self) -> torch.Tensor: + if self.token_len: + return torch.tensor([[self.seq_len - 1]], dtype=torch.long) + return torch.arange(self.seq_len, dtype=torch.long).unsqueeze(0) + +# BGE is Embedding Model based Bert +class BGEBlock(torch.nn.Module): + def __init__(self, block, block_id, hidden_size): + super().__init__() + self.block = block + self.block_id = block_id + self.hidden_size = hidden_size + + def forward(self, hidden_states, attention_mask): + hidden_states = self.block(hidden_states, attention_mask)[0] + return hidden_states + +class bge(LLM): + def __init__(self, args): + self.attention_mask_type = 'int' + self.past_kv_shape = [] + super().__init__(args) + self.model_name = 'bge-large-zh' + + def forward(self, input_ids, position_ids, attention_mask): + input_ids = input_ids.view(1, -1) + token_type_ids = (1 - attention_mask).view(1, -1) + hidden_states = self.embed(input_ids, token_type_ids, position_ids)[0].unsqueeze(0) + for i in range(self.block_nums): + hidden_states = self.blocks[i](hidden_states, attention_mask) + # hidden_states = self.lm(hidden_states) # sentence_embeddings not need + sentence_embeddings = hidden_states[:, 0] + sentence_embeddings = torch.nn.functional.normalize(sentence_embeddings, p=2, dim=1) + return sentence_embeddings + + def response(self, query): + self.eval() + input_ids = self.tokenizer(query)['input_ids'] + self.seq_len = len(input_ids) + input_ids = torch.tensor(input_ids) + position_ids = self.get_position_ids() + attention_mask = self.get_attention_mask() + res = self.forward(input_ids, position_ids, attention_mask) + return res + + def load_model(self): + self.model = AutoModel.from_pretrained(model_path, trust_remote_code=True).float().eval() + transformer = self.model.encoder + self.lm_ = self.model.pooler + self.embed_ = self.model.embeddings + self.hidden_size = self.embed_.word_embeddings.weight.shape[-1] + self.blocks_ = transformer.layer + # some wrapper + self.stop_ids = [] + self.block_nums = len(self.blocks_) + self.embed = self.embed_ + self.lm = self.lm_ + self.blocks = [BGEBlock(self.blocks_[i], i, self.hidden_size) for i in range(self.block_nums)] + # some config for export + self.model_dynamic_axes = { + "input_ids" : { 0: "seq_len" }, + "position_ids" : { 1: "seq_len" }, + "attention_mask" : { 3: "seq_len" } + } + + def export(self): + model = self.eval() + self.seq_len = 3 + input_ids = torch.arange(3, dtype=torch.long) + position_ids = self.get_position_ids() + attention_mask = self.get_attention_mask() + onnx_model = f'./{self.onnx_path}/bge.onnx' + torch.onnx.export( + model, (input_ids, position_ids, attention_mask), + onnx_model, + verbose=self.export_verbose, + input_names=[ + 'input_ids', + 'position_ids', + 'attention_mask' + ], + output_names=['sentence_embeddings'], + dynamic_axes=self.model_dynamic_axes, + do_constant_folding=True, + opset_version=15) + if not self.skip_slim: + slim(onnx_model, output_model=onnx_model) + if self.export_test: + self.seq_len = 4 + position_ids = self.get_position_ids() + input_ids = torch.tensor([ 101, 872, 1962, 102 ], dtype=torch.long) + attention_mask = self.get_attention_mask() + # test + original_outs = model(input_ids, position_ids, attention_mask) + ort_session = ort.InferenceSession(onnx_model, providers=['CPUExecutionProvider']) + inputs = { + 'input_ids' : input_ids.detach().numpy(), + 'position_ids' : position_ids.detach().numpy(), + 'attention_mask' : attention_mask.detach().numpy() + } + onnx_outs = ort_session.run(None, inputs)[0] + self.assert_equal(original_outs, onnx_outs) + + token_str = None + if False: # save tokenizer in mnn + self.export_tokenizer() + token_path = os.path.join(self.onnx_path, "tokenizer.txt") + token_str = open(token_path, 'rt').read() + + if self.export_mnn: + onnx2mnn(onnx_model, self.mnn_path, 8, True, bizCode=token_str) + + def build_prompt(self, query): + return f'[CLS]{query}[SEP]' + + def get_position_ids(self) -> torch.Tensor: + return torch.arange(self.seq_len, dtype=torch.long).unsqueeze(0) + + def get_attention_mask(self) -> torch.Tensor: + return torch.ones([1, 1, 1, self.seq_len], dtype=torch.long) + +class LoraModule(torch.nn.Module): + def __init__(self, args): + super().__init__() + self.onnx_path = args.onnx_path + self.mnn_path = args.mnn_path + self.export_mnn = args.export_mnn + import peft + lora_weight = peft.load_peft_weights(args.path) + for k, v in lora_weight.items(): + k = k.replace('.', '/') + self.register_buffer(k, v.cpu()) + + def forward(self, dummpy): + return self._buffers + + def export(self): + onnx_model = f'./{self.onnx_path}/lora.onnx' + torch.onnx.export(self.eval(), torch.tensor([]), onnx_model) + if self.export_mnn: + onnx2mnn(onnx_model, self.mnn_path) + + +if __name__ == '__main__': + llm_models = { + 'chatglm-6b': Chatglm_6b, + 'chatglm2-6b': Chatglm2_6b, + 'codegeex2-6b': Chatglm2_6b, + 'chatglm3-6b': Chatglm3_6b, + 'glm-4-9b-chat': Chatglm3_6b, + 'Qwen-7B-Chat': Qwen_Chat, + 'Qwen-1_8B-Chat': Qwen_Chat, + 'Qwen-1_8B': Qwen_Chat, + 'Qwen-VL-Chat': Qwen_Chat, + 'Qwen1_5-0_5B-Chat': Qwen2_Chat, + 'Qwen1_5-1_8B-Chat': Qwen2_Chat, + 'Qwen1_5-4B-Chat': Qwen2_Chat, + 'Qwen1_5-7B-Chat': Qwen2_Chat, + 'Qwen2-0_5B-Instruct': Qwen2_Chat, + 'Qwen2-1_5B-Instruct': Qwen2_Chat, + 'Qwen2-7B-Instruct': Qwen2_Chat, + 'Baichuan2-7B-Chat': Llama2_7b_Chat, + 'Llama-2-7b-chat-ms': Llama2_7b_Chat, + 'Llama-3-8B-Instruct': Llama2_7b_Chat, + 'internlm-chat-7b': Llama2_7b_Chat, + 'TinyLlama-1_1B-Chat': Llama2_7b_Chat, + 'Yi-6B-Chat': Llama2_7b_Chat, + 'deepseek-llm-7b-chat': Llama2_7b_Chat, + 'phi-2': phi_2, + 'bge-large-zh': bge, + 'lora': LoraModule + } + parser = argparse.ArgumentParser(description='llm_exporter', formatter_class=argparse.RawTextHelpFormatter) + parser.add_argument('--path', type=str, default='THUDM/chatglm-6b', required=True, + help='path(`str` or `os.PathLike`):\nCan be either:' + '\n\t- A string, the *model id* of a pretrained model like `THUDM/chatglm-6b`. [TODO]' + '\n\t- A path to a *directory* clone from repo like `../chatglm-6b`.') + parser.add_argument('--type', type=str, choices=llm_models.keys(), default=None, + help='type(`str`, *optional*):' + '\n\tThe pretrain llm model type.' + ) + parser.add_argument('--lora_path', type=str, default=None, help='lora path, defaut is `None` mean not apply lora.') + parser.add_argument('--onnx_path', type=str, default='./onnx', help='export onnx model path, defaut is `./onnx`.') + parser.add_argument('--mnn_path', type=str, default='./mnn', help='export mnn model path, defaut is `./mnn`.') + parser.add_argument('--export_mnn', action='store_true', default=False, help='Whether or not to export mnn model after onnx.') + parser.add_argument('--export_verbose', action='store_true', default=False, help='Whether or not to export onnx with verbose.') + parser.add_argument('--export_test', action='store_true', help='Whether or not to export onnx with test using onnxruntime.') + parser.add_argument('--test', type=str, help='test model inference with query `TEST`.') + parser.add_argument('--export', action='store_true', help='export model to an `onnx` model.') + parser.add_argument('--export_split', action='store_true', + help='export model split to some `onnx` models:' + '\n\t- embedding model.' + '\n\t- block models.' + '\n\t- lm_head model.' + ) + parser.add_argument('--export_token', action='store_true', help='export llm tokenizer to a txt file.') + parser.add_argument('--export_embed', action='store_true', help='export llm embedding to an `onnx` model.') + parser.add_argument('--export_visual', action='store_true', help='export llm visual model to an `onnx` model.') + parser.add_argument('--export_lm', action='store_true', help='export llm lm_head to an `onnx` model.') + parser.add_argument('--export_block', type=int, help='export llm block [id] to an `onnx` model.') + parser.add_argument('--export_blocks', action='store_true', help='export llm all blocks to `onnx` models.') + parser.add_argument('--embed_bin', action='store_true', help='export embedding weight as bin file with dtype `bfloat16`') + parser.add_argument('--embed_bf16', action='store_true', help='using `bfloat16` replace `float32` in embedding.') + parser.add_argument('--skip_slim', action='store_true', help='Whether or not to skip onnx-slim.') + + + args = parser.parse_args() + model_path = args.path + model_type = args.type + # not sepcify model type, using path + if model_type is None: + for model in llm_models: + if model in model_path: + model_type = model + if model_type is None: + raise RuntimeError('Please specify model type.') + + # copy modeling py file to pretrain model for export + for file in glob.glob(f'./llm_models/{model_type}/*'): + shutil.copy2(file, model_path) + + llm_exporter = llm_models[model_type](args) + + # some actions + if args.test is not None: + llm_exporter.response(args.test) + + if args.export or args.export_split: + llm_exporter.export_config(args.export) + + if args.export: + llm_exporter.export() + + if args.export_token: + llm_exporter.export_tokenizer() + + if args.export_embed or args.export_split: + llm_exporter.export_embed() + + if args.export_visual or args.export_split: + llm_exporter.export_visual() + + if args.export_lm or args.export_split: + llm_exporter.export_lm() + + if args.export_blocks or args.export_split: + llm_exporter.export_blocks() + + if args.export_block is not None: + llm_exporter.export_block(args.export_block) \ No newline at end of file From 6ecebb210c2d586c1e2b24966f9b4bb573ce1232 Mon Sep 17 00:00:00 2001 From: Ke Xing <38187527+PeterXingke@users.noreply.github.com> Date: Tue, 6 Aug 2024 00:41:47 +0800 Subject: [PATCH 2/2] Add files via upload The Q2 model's result before is not completed. We rerun the Q2 model to generate 128 tokens spending about 5.7 hours. --- Q2_main_2.log | 645 ++++++++++++++++++++++++++++++++++++++++++++++++ Q2_result_2.jpg | Bin 0 -> 116144 bytes 2 files changed, 645 insertions(+) create mode 100644 Q2_main_2.log create mode 100644 Q2_result_2.jpg diff --git a/Q2_main_2.log b/Q2_main_2.log new file mode 100644 index 0000000..b80d151 --- /dev/null +++ b/Q2_main_2.log @@ -0,0 +1,645 @@ +[100] Log start +[100] Cmd: ./llama-cli -m Meta-Llama-3-7B-29Layers.Q2_K.gguf -p "I believe the meaning of life is" -n 128 +[100] main: build = 3505 (b72c20b8) +[100] main: built with riscv64-unknown-linux-gnu-gcc (Xuantie-900 linux-5.10.4 glibc gcc Toolchain V2.6.0 B-20220715) 10.2.0 for riscv64-unknown-linux-gnu +[100] main: seed = 100 +[100] main: llama backend init +[100] main: load the model and apply lora adapter, if any +[101] llama_model_loader: loaded meta data with 28 key-value pairs and 264 tensors from Meta-Llama-3-7B-29Layers.Q2_K.gguf (version GGUF V3 (latest)) +[101] llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output. +[101] llama_model_loader: - kv 0: general.architecture str = llama +[101] llama_model_loader: - kv 1: general.name str = Meta-Llama-3-7B-29Layers +[101] llama_model_loader: - kv 2: llama.block_count u32 = 29 +[101] llama_model_loader: - kv 3: llama.context_length u32 = 8192 +[101] llama_model_loader: - kv 4: llama.embedding_length u32 = 4096 +[101] llama_model_loader: - kv 5: llama.feed_forward_length u32 = 14336 +[101] llama_model_loader: - kv 6: llama.attention.head_count u32 = 32 +[101] llama_model_loader: - kv 7: llama.attention.head_count_kv u32 = 8 +[101] llama_model_loader: - kv 8: llama.rope.freq_base f32 = 500000.000000 +[101] llama_model_loader: - kv 9: llama.attention.layer_norm_rms_epsilon f32 = 0.000010 +[101] llama_model_loader: - kv 10: general.file_type u32 = 10 +[101] llama_model_loader: - kv 11: llama.vocab_size u32 = 128256 +[101] llama_model_loader: - kv 12: llama.rope.dimension_count u32 = 128 +[101] llama_model_loader: - kv 13: tokenizer.ggml.model str = gpt2 +[101] llama_model_loader: - kv 14: tokenizer.ggml.pre str = llama-bpe +[101] llama_model_loader: - kv 15: tokenizer.ggml.tokens arr[str,128256] = ["!", "\"", "#", "$", "%", "&", "'", ... +[101] llama_model_loader: - kv 16: tokenizer.ggml.token_type arr[i32,128256] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ... +[101] llama_model_loader: - kv 17: tokenizer.ggml.merges arr[str,280147] = ["Ġ Ġ", "Ġ ĠĠĠ", "ĠĠ ĠĠ", "... +[101] llama_model_loader: - kv 18: tokenizer.ggml.bos_token_id u32 = 128000 +[101] llama_model_loader: - kv 19: tokenizer.ggml.eos_token_id u32 = 128001 +[101] llama_model_loader: - kv 20: general.quantization_version u32 = 2 +[101] llama_model_loader: - kv 21: general.url str = https://huggingface.co/mradermacher/M... +[101] llama_model_loader: - kv 22: mradermacher.quantize_version str = 2 +[101] llama_model_loader: - kv 23: mradermacher.quantized_by str = mradermacher +[101] llama_model_loader: - kv 24: mradermacher.quantized_at str = 2024-05-14T23:42:57+02:00 +[101] llama_model_loader: - kv 25: mradermacher.quantized_on str = db2 +[101] llama_model_loader: - kv 26: general.source.url str = https://huggingface.co/aloobun/Meta-L... +[101] llama_model_loader: - kv 27: mradermacher.convert_type str = hf +[101] llama_model_loader: - type f32: 59 tensors +[101] llama_model_loader: - type q2_K: 117 tensors +[101] llama_model_loader: - type q3_K: 58 tensors +[101] llama_model_loader: - type q4_K: 29 tensors +[101] llama_model_loader: - type q6_K: 1 tensors +[106] llm_load_vocab: special tokens cache size = 256 +[106] llm_load_vocab: token to piece cache size = 0.8000 MB +[106] llm_load_print_meta: format = GGUF V3 (latest) +[106] llm_load_print_meta: arch = llama +[106] llm_load_print_meta: vocab type = BPE +[106] llm_load_print_meta: n_vocab = 128256 +[106] llm_load_print_meta: n_merges = 280147 +[106] llm_load_print_meta: vocab_only = 0 +[106] llm_load_print_meta: n_ctx_train = 8192 +[106] llm_load_print_meta: n_embd = 4096 +[106] llm_load_print_meta: n_layer = 29 +[106] llm_load_print_meta: n_head = 32 +[106] llm_load_print_meta: n_head_kv = 8 +[106] llm_load_print_meta: n_rot = 128 +[106] llm_load_print_meta: n_swa = 0 +[106] llm_load_print_meta: n_embd_head_k = 128 +[106] llm_load_print_meta: n_embd_head_v = 128 +[106] llm_load_print_meta: n_gqa = 4 +[106] llm_load_print_meta: n_embd_k_gqa = 1024 +[106] llm_load_print_meta: n_embd_v_gqa = 1024 +[106] llm_load_print_meta: f_norm_eps = 0.0e+00 +[106] llm_load_print_meta: f_norm_rms_eps = 1.0e-05 +[106] llm_load_print_meta: f_clamp_kqv = 0.0e+00 +[106] llm_load_print_meta: f_max_alibi_bias = 0.0e+00 +[106] llm_load_print_meta: f_logit_scale = 0.0e+00 +[106] llm_load_print_meta: n_ff = 14336 +[106] llm_load_print_meta: n_expert = 0 +[106] llm_load_print_meta: n_expert_used = 0 +[106] llm_load_print_meta: causal attn = 1 +[106] llm_load_print_meta: pooling type = 0 +[106] llm_load_print_meta: rope type = 0 +[106] llm_load_print_meta: rope scaling = linear +[106] llm_load_print_meta: freq_base_train = 500000.0 +[106] llm_load_print_meta: freq_scale_train = 1 +[106] llm_load_print_meta: n_ctx_orig_yarn = 8192 +[106] llm_load_print_meta: rope_finetuned = unknown +[106] llm_load_print_meta: ssm_d_conv = 0 +[106] llm_load_print_meta: ssm_d_inner = 0 +[106] llm_load_print_meta: ssm_d_state = 0 +[106] llm_load_print_meta: ssm_dt_rank = 0 +[106] llm_load_print_meta: model type = ?B +[106] llm_load_print_meta: model ftype = Q2_K - Medium +[106] llm_load_print_meta: model params = 7.38 B +[106] llm_load_print_meta: model size = 2.73 GiB (3.18 BPW) +[106] llm_load_print_meta: general.name = Meta-Llama-3-7B-29Layers +[106] llm_load_print_meta: BOS token = 128000 '<|begin_of_text|>' +[106] llm_load_print_meta: EOS token = 128001 '<|end_of_text|>' +[106] llm_load_print_meta: LF token = 128 'Ä' +[106] llm_load_print_meta: EOT token = 128009 '<|eot_id|>' +[106] llm_load_print_meta: max token length = 256 +[106] llm_load_tensors: ggml ctx size = 0.12 MiB +[233] llm_load_tensors: CPU buffer size = 2794.79 MiB +[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] .[233] +[234] llama_new_context_with_model: n_ctx = 8192 +[234] llama_new_context_with_model: n_batch = 2048 +[234] llama_new_context_with_model: n_ubatch = 512 +[234] llama_new_context_with_model: flash_attn = 0 +[234] llama_new_context_with_model: freq_base = 500000.0 +[234] llama_new_context_with_model: freq_scale = 1 +[289] llama_kv_cache_init: CPU KV buffer size = 928.00 MiB +[289] llama_new_context_with_model: KV self size = 928.00 MiB, K (f16): 464.00 MiB, V (f16): 464.00 MiB +[289] llama_new_context_with_model: CPU output buffer size = 0.49 MiB +[289] llama_new_context_with_model: CPU compute buffer size = 560.01 MiB +[289] llama_new_context_with_model: graph nodes = 934 +[289] llama_new_context_with_model: graph splits = 1 +[289] warming up the model with an empty run +[629] n_ctx: 8192 +[629] +[629] system_info: n_threads = 1 / 1 | AVX = 0 | AVX_VNNI = 0 | AVX2 = 0 | AVX512 = 0 | AVX512_VBMI = 0 | AVX512_VNNI = 0 | AVX512_BF16 = 0 | FMA = 0 | NEON = 0 | SVE = 0 | ARM_FMA = 0 | F16C = 0 | FP16_VA = 0 | WASM_SIMD = 0 | BLAS = 0 | SSE3 = 0 | SSSE3 = 0 | VSX = 0 | MATMUL_INT8 = 0 | LLAMAFILE = 1 | +[629] add_bos: 1 +[629] tokenize the prompt +[629] prompt: "I believe the meaning of life is" +[629] tokens: [ '<|begin_of_text|>':128000, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374 ] +[629] recalculate the cached logits (check): embd_inp.empty() false, n_matching_session_tokens 0, embd_inp.size() 8, session_tokens.size() 0, embd_inp.size() 8 +[629] sampling: + repeat_last_n = 64, repeat_penalty = 1.000, frequency_penalty = 0.000, presence_penalty = 0.000 + top_k = 40, tfs_z = 1.000, top_p = 0.950, min_p = 0.050, typical_p = 1.000, temp = 0.800 + mirostat = 0, mirostat_lr = 0.100, mirostat_ent = 5.000 +[629] sampling order: +CFG -> Penalties -> top_k -> tfs_z -> typical_p -> top_p -> min_p -> temperature +[629] generate: n_ctx = 8192, n_batch = 2048, n_predict = 128, n_keep = 1 +[629] + +[630] embd_inp.size(): 8, n_consumed: 0 +[630] eval: [ '<|begin_of_text|>':128000, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374 ] +[1096] n_past = 8 +[1096] last: [ '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '<|begin_of_text|>':128000, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' not':539 ] +[1096] n_remain: 127 +[1096] eval: [ ' not':539 ] +[1262] n_past = 9 +[1262] last: [ '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '<|begin_of_text|>':128000, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' not':539, ' life':2324 ] +[1262] n_remain: 126 +[1262] eval: [ ' life':2324 ] +[1422] n_past = 10 +[1422] last: [ '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '<|begin_of_text|>':128000, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' not':539, ' life':2324, ' itself':5196 ] +[1422] n_remain: 125 +[1422] eval: [ ' itself':5196 ] +[1584] n_past = 11 +[1584] last: [ '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '<|begin_of_text|>':128000, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' not':539, ' life':2324, ' itself':5196, '.':13 ] +[1584] n_remain: 124 +[1584] eval: [ '.':13 ] +[1747] n_past = 12 +[1747] last: [ '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '<|begin_of_text|>':128000, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' not':539, ' life':2324, ' itself':5196, '.':13, ' I':358 ] +[1747] n_remain: 123 +[1747] eval: [ ' I':358 ] +[1915] n_past = 13 +[1915] last: [ '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '<|begin_of_text|>':128000, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' not':539, ' life':2324, ' itself':5196, '.':13, ' I':358, ' believe':4510 ] +[1915] n_remain: 122 +[1915] eval: [ ' believe':4510 ] +[2078] n_past = 14 +[2078] last: [ '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '<|begin_of_text|>':128000, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' not':539, ' life':2324, ' itself':5196, '.':13, ' I':358, ' believe':4510, ' the':279 ] +[2078] n_remain: 121 +[2078] eval: [ ' the':279 ] +[2238] n_past = 15 +[2238] last: [ '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '<|begin_of_text|>':128000, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' not':539, ' life':2324, ' itself':5196, '.':13, ' I':358, ' believe':4510, ' the':279, ' meaning':7438 ] +[2238] n_remain: 120 +[2238] eval: [ ' meaning':7438 ] +[2402] n_past = 16 +[2403] last: [ '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '<|begin_of_text|>':128000, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' not':539, ' life':2324, ' itself':5196, '.':13, ' I':358, ' believe':4510, ' the':279, ' meaning':7438, ' of':315 ] +[2403] n_remain: 119 +[2403] eval: [ ' of':315 ] +[2563] n_past = 17 +[2563] last: [ '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '<|begin_of_text|>':128000, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' not':539, ' life':2324, ' itself':5196, '.':13, ' I':358, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324 ] +[2563] n_remain: 118 +[2563] eval: [ ' life':2324 ] +[2723] n_past = 18 +[2723] last: [ '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '<|begin_of_text|>':128000, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' not':539, ' life':2324, ' itself':5196, '.':13, ' I':358, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374 ] +[2723] n_remain: 117 +[2723] eval: [ ' is':374 ] +[2886] n_past = 19 +[2886] last: [ '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '<|begin_of_text|>':128000, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' not':539, ' life':2324, ' itself':5196, '.':13, ' I':358, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' that':430 ] +[2886] n_remain: 116 +[2886] eval: [ ' that':430 ] +[3048] n_past = 20 +[3048] last: [ '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '!':0, '<|begin_of_text|>':128000, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' not':539, ' life':2324, ' itself':5196, '.':13, ' 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believe':4510, ' the':279 ] +[17606] n_remain: 25 +[17606] eval: [ ' the':279 ] +[17767] n_past = 111 +[17767] last: [ ' us':603, ' are':527, ' looking':3411, ' out':704, ' instead':4619, ' of':315, ' looking':3411, ' in':304, 'wards':4102, '.':13, ' We':1226, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' the':279, ' best':1888, ' within':2949, ' ourselves':13520, ' and':323, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, '.':13, ' When':3277, ' we':584, ' are':527, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' anything':4205, ' else':775, '.':13, ' When':3277, ' we':584, ' are':527, ' in':304, ' touch':5916, ' with':449, ' others':3885, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, '.':627, 'I':40, ' believe':4510, ' the':279, ' meaning':7438 ] +[17767] n_remain: 24 +[17767] eval: [ ' meaning':7438 ] +[17929] n_past = 112 +[17929] last: [ ' are':527, ' looking':3411, ' out':704, ' instead':4619, ' of':315, ' looking':3411, ' in':304, 'wards':4102, '.':13, ' We':1226, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' the':279, ' best':1888, ' within':2949, ' ourselves':13520, ' and':323, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, '.':13, ' When':3277, ' we':584, ' are':527, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' anything':4205, ' else':775, '.':13, ' When':3277, ' we':584, ' are':527, ' in':304, ' touch':5916, ' with':449, ' others':3885, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, '.':627, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315 ] +[17929] n_remain: 23 +[17929] eval: [ ' of':315 ] +[18090] n_past = 113 +[18091] last: [ ' looking':3411, ' out':704, ' instead':4619, ' of':315, ' looking':3411, ' in':304, 'wards':4102, '.':13, ' We':1226, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' the':279, ' best':1888, ' within':2949, ' ourselves':13520, ' and':323, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, '.':13, ' When':3277, ' we':584, ' are':527, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' anything':4205, ' else':775, '.':13, ' When':3277, ' we':584, ' are':527, ' in':304, ' touch':5916, ' with':449, ' others':3885, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, '.':627, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324 ] +[18091] n_remain: 22 +[18091] eval: [ ' life':2324 ] +[18251] n_past = 114 +[18251] last: [ ' out':704, ' instead':4619, ' of':315, ' looking':3411, ' in':304, 'wards':4102, '.':13, ' We':1226, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' the':279, ' best':1888, ' within':2949, ' ourselves':13520, ' and':323, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, '.':13, ' When':3277, ' we':584, ' are':527, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' anything':4205, ' else':775, '.':13, ' When':3277, ' we':584, ' are':527, ' in':304, ' touch':5916, ' with':449, ' others':3885, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, '.':627, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374 ] +[18251] n_remain: 21 +[18251] eval: [ ' is':374 ] +[18414] n_past = 115 +[18414] last: [ ' instead':4619, ' of':315, ' looking':3411, ' in':304, 'wards':4102, '.':13, ' We':1226, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' the':279, ' best':1888, ' within':2949, ' ourselves':13520, ' and':323, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, '.':13, ' When':3277, ' we':584, ' are':527, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' anything':4205, ' else':775, '.':13, ' When':3277, ' we':584, ' are':527, ' in':304, ' touch':5916, ' with':449, ' others':3885, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, '.':627, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' not':539 ] +[18414] n_remain: 20 +[18414] eval: [ ' not':539 ] +[18577] n_past = 116 +[18577] last: [ ' of':315, ' looking':3411, ' in':304, 'wards':4102, '.':13, ' We':1226, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' the':279, ' best':1888, ' within':2949, ' ourselves':13520, ' and':323, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, '.':13, ' When':3277, ' we':584, ' are':527, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' anything':4205, ' else':775, '.':13, ' When':3277, ' we':584, ' are':527, ' in':304, ' touch':5916, ' with':449, ' others':3885, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, '.':627, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' not':539, ' life':2324 ] +[18577] n_remain: 19 +[18577] eval: [ ' life':2324 ] +[18737] n_past = 117 +[18737] last: [ ' looking':3411, ' in':304, 'wards':4102, '.':13, ' We':1226, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' the':279, ' best':1888, ' within':2949, ' ourselves':13520, ' and':323, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, '.':13, ' When':3277, ' we':584, ' are':527, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' anything':4205, ' else':775, '.':13, ' When':3277, ' we':584, ' are':527, ' in':304, ' touch':5916, ' with':449, ' others':3885, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, '.':627, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' not':539, ' life':2324, ' itself':5196 ] +[18737] n_remain: 18 +[18737] eval: [ ' itself':5196 ] +[18898] n_past = 118 +[18899] last: [ ' in':304, 'wards':4102, '.':13, ' We':1226, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' the':279, ' best':1888, ' within':2949, ' ourselves':13520, ' and':323, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, '.':13, ' When':3277, ' we':584, ' are':527, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' anything':4205, ' else':775, '.':13, ' When':3277, ' we':584, ' are':527, ' in':304, ' touch':5916, ' with':449, ' others':3885, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, '.':627, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' not':539, ' life':2324, ' itself':5196, '.':13 ] +[18899] n_remain: 17 +[18899] eval: [ '.':13 ] +[19059] n_past = 119 +[19059] last: [ 'wards':4102, '.':13, ' We':1226, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' the':279, ' best':1888, ' within':2949, ' ourselves':13520, ' and':323, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, '.':13, ' When':3277, ' we':584, ' are':527, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' anything':4205, ' else':775, '.':13, ' When':3277, ' we':584, ' are':527, ' in':304, ' touch':5916, ' with':449, ' others':3885, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, '.':627, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' not':539, ' life':2324, ' itself':5196, '.':13, ' I':358 ] +[19059] n_remain: 16 +[19059] eval: [ ' I':358 ] +[19224] n_past = 120 +[19224] last: [ '.':13, ' We':1226, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' the':279, ' best':1888, ' within':2949, ' ourselves':13520, ' and':323, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, '.':13, ' When':3277, ' we':584, ' are':527, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' anything':4205, ' else':775, '.':13, ' When':3277, ' we':584, ' are':527, ' in':304, ' touch':5916, ' with':449, ' others':3885, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, '.':627, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' not':539, ' life':2324, ' itself':5196, '.':13, ' I':358, ' believe':4510 ] +[19224] n_remain: 15 +[19224] eval: [ ' believe':4510 ] +[19385] n_past = 121 +[19385] last: [ ' We':1226, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' the':279, ' best':1888, ' within':2949, ' ourselves':13520, ' and':323, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, '.':13, ' When':3277, ' we':584, ' are':527, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' anything':4205, ' else':775, '.':13, ' When':3277, ' we':584, ' are':527, ' in':304, ' touch':5916, ' with':449, ' others':3885, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, '.':627, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' not':539, ' life':2324, ' itself':5196, '.':13, ' I':358, ' believe':4510, ' the':279 ] +[19385] n_remain: 14 +[19385] eval: [ ' the':279 ] +[19545] n_past = 122 +[19545] last: [ ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' the':279, ' best':1888, ' within':2949, ' ourselves':13520, ' and':323, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, '.':13, ' When':3277, ' we':584, ' are':527, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' anything':4205, ' else':775, '.':13, ' When':3277, ' we':584, ' are':527, ' in':304, ' touch':5916, ' with':449, ' others':3885, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, '.':627, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' not':539, ' life':2324, ' itself':5196, '.':13, ' I':358, ' believe':4510, ' the':279, ' meaning':7438 ] +[19545] n_remain: 13 +[19545] eval: [ ' meaning':7438 ] +[19708] n_past = 123 +[19708] last: [ ' not':539, ' in':304, ' touch':5916, ' with':449, ' the':279, ' best':1888, ' within':2949, ' ourselves':13520, ' and':323, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, '.':13, ' When':3277, ' we':584, ' are':527, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' anything':4205, ' else':775, '.':13, ' When':3277, ' we':584, ' are':527, ' in':304, ' touch':5916, ' with':449, ' others':3885, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, '.':627, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' not':539, ' life':2324, ' itself':5196, '.':13, ' I':358, ' believe':4510, ' the':279, ' meaning':7438, ' of':315 ] +[19708] n_remain: 12 +[19708] eval: [ ' of':315 ] +[19869] n_past = 124 +[19869] last: [ ' in':304, ' touch':5916, ' with':449, ' the':279, ' best':1888, ' within':2949, ' ourselves':13520, ' and':323, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, '.':13, ' When':3277, ' we':584, ' are':527, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' anything':4205, ' else':775, '.':13, ' When':3277, ' we':584, ' are':527, ' in':304, ' touch':5916, ' with':449, ' others':3885, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, '.':627, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' not':539, ' life':2324, ' itself':5196, '.':13, ' I':358, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324 ] +[19869] n_remain: 11 +[19869] eval: [ ' life':2324 ] +[20031] n_past = 125 +[20031] last: [ ' touch':5916, ' with':449, ' the':279, ' best':1888, ' within':2949, ' ourselves':13520, ' and':323, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, '.':13, ' When':3277, ' we':584, ' are':527, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' anything':4205, ' else':775, '.':13, ' When':3277, ' we':584, ' are':527, ' in':304, ' touch':5916, ' with':449, ' others':3885, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, '.':627, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' not':539, ' life':2324, ' itself':5196, '.':13, ' I':358, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374 ] +[20031] n_remain: 10 +[20031] eval: [ ' is':374 ] +[20195] n_past = 126 +[20196] last: [ ' with':449, ' the':279, ' best':1888, ' within':2949, ' ourselves':13520, ' and':323, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, '.':13, ' When':3277, ' we':584, ' are':527, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' anything':4205, ' else':775, '.':13, ' When':3277, ' we':584, ' are':527, ' in':304, ' touch':5916, ' with':449, ' others':3885, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, '.':627, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' not':539, ' life':2324, ' itself':5196, '.':13, ' I':358, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' that':430 ] +[20196] n_remain: 9 +[20196] eval: [ ' that':430 ] +[20355] n_past = 127 +[20355] last: [ ' the':279, ' best':1888, ' within':2949, ' ourselves':13520, ' and':323, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, '.':13, ' When':3277, ' we':584, ' are':527, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' anything':4205, ' else':775, '.':13, ' When':3277, ' we':584, ' are':527, ' in':304, ' touch':5916, ' with':449, ' others':3885, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, '.':627, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' not':539, ' life':2324, ' itself':5196, '.':13, ' I':358, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' that':430, ' we':584 ] +[20355] n_remain: 8 +[20355] eval: [ ' we':584 ] +[20517] n_past = 128 +[20518] last: [ ' best':1888, ' within':2949, ' ourselves':13520, ' and':323, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, '.':13, ' When':3277, ' we':584, ' are':527, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' anything':4205, ' else':775, '.':13, ' When':3277, ' we':584, ' are':527, ' in':304, ' touch':5916, ' with':449, ' others':3885, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, '.':627, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' not':539, ' life':2324, ' itself':5196, '.':13, ' I':358, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' that':430, ' we':584, ' are':527 ] +[20518] n_remain: 7 +[20518] eval: [ ' are':527 ] +[20681] n_past = 129 +[20681] last: [ ' within':2949, ' ourselves':13520, ' and':323, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, '.':13, ' When':3277, ' we':584, ' are':527, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' anything':4205, ' else':775, '.':13, ' When':3277, ' we':584, ' are':527, ' in':304, ' touch':5916, ' with':449, ' others':3885, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, '.':627, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' not':539, ' life':2324, ' itself':5196, '.':13, ' I':358, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' that':430, ' we':584, ' are':527, ' but':719 ] +[20681] n_remain: 6 +[20681] eval: [ ' but':719 ] +[20842] n_past = 130 +[20843] last: [ ' ourselves':13520, ' and':323, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, '.':13, ' When':3277, ' we':584, ' are':527, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' anything':4205, ' else':775, '.':13, ' When':3277, ' we':584, ' are':527, ' in':304, ' touch':5916, ' with':449, ' others':3885, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, '.':627, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' not':539, ' life':2324, ' itself':5196, '.':13, ' I':358, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' that':430, ' we':584, ' are':527, ' but':719, ' a':264 ] +[20843] n_remain: 5 +[20843] eval: [ ' a':264 ] +[21007] n_past = 131 +[21008] last: [ ' and':323, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, '.':13, ' When':3277, ' we':584, ' are':527, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' anything':4205, ' else':775, '.':13, ' When':3277, ' we':584, ' are':527, ' in':304, ' touch':5916, ' with':449, ' others':3885, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, '.':627, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' not':539, ' life':2324, ' itself':5196, '.':13, ' I':358, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' that':430, ' we':584, ' are':527, ' but':719, ' a':264, ' moment':4545 ] +[21008] n_remain: 4 +[21008] eval: [ ' moment':4545 ] +[21168] n_past = 132 +[21168] last: [ ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, '.':13, ' When':3277, ' we':584, ' are':527, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' anything':4205, ' else':775, '.':13, ' When':3277, ' we':584, ' are':527, ' in':304, ' touch':5916, ' with':449, ' others':3885, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, '.':627, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' not':539, ' life':2324, ' itself':5196, '.':13, ' I':358, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' that':430, ' we':584, ' are':527, ' but':719, ' a':264, ' moment':4545, ' in':304 ] +[21168] n_remain: 3 +[21168] eval: [ ' in':304 ] +[21330] n_past = 133 +[21330] last: [ ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, '.':13, ' When':3277, ' we':584, ' are':527, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' anything':4205, ' else':775, '.':13, ' When':3277, ' we':584, ' are':527, ' in':304, ' touch':5916, ' with':449, ' others':3885, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, '.':627, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' not':539, ' life':2324, ' itself':5196, '.':13, ' I':358, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' that':430, ' we':584, ' are':527, ' but':719, ' a':264, ' moment':4545, ' in':304, ' time':892 ] +[21330] n_remain: 2 +[21330] eval: [ ' time':892 ] +[21491] n_past = 134 +[21492] last: [ ' not':539, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, '.':13, ' When':3277, ' we':584, ' are':527, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' anything':4205, ' else':775, '.':13, ' When':3277, ' we':584, ' are':527, ' in':304, ' touch':5916, ' with':449, ' others':3885, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, '.':627, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' not':539, ' life':2324, ' itself':5196, '.':13, ' I':358, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' that':430, ' we':584, ' are':527, ' but':719, ' a':264, ' moment':4545, ' in':304, ' time':892, ' in':304 ] +[21492] n_remain: 1 +[21492] eval: [ ' in':304 ] +[21654] n_past = 135 +[21654] last: [ ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, '.':13, ' When':3277, ' we':584, ' are':527, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' anything':4205, ' else':775, '.':13, ' When':3277, ' we':584, ' are':527, ' in':304, ' touch':5916, ' with':449, ' others':3885, ' we':584, ' are':527, ' not':539, ' in':304, ' touch':5916, ' with':449, ' ourselves':13520, '.':627, 'I':40, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' not':539, ' life':2324, ' itself':5196, '.':13, ' I':358, ' believe':4510, ' the':279, ' meaning':7438, ' of':315, ' life':2324, ' is':374, ' that':430, ' we':584, ' are':527, ' but':719, ' a':264, ' moment':4545, ' in':304, ' time':892, ' in':304, ' a':264 ] +[21654] n_remain: 0 +[21654] +[21654] llama_print_timings: load time = 523324.10 ms +[21654] llama_print_timings: sample time = 1555.63 ms / 128 runs ( 12.15 ms per token, 82.28 tokens per second) +[21654] llama_print_timings: prompt eval time = 466631.26 ms / 8 tokens (58328.91 ms per token, 0.02 tokens per second) +[21654] llama_print_timings: eval time = 20534858.30 ms / 127 runs (161691.80 ms per token, 0.01 tokens per second) +[21654] llama_print_timings: total time = 21024583.82 ms / 135 tokens +[21660] Log end diff --git a/Q2_result_2.jpg b/Q2_result_2.jpg new file mode 100644 index 0000000000000000000000000000000000000000..5ace946e29bd54f28aec70cb00bd6c2d195f6060 GIT binary patch literal 116144 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