Vanilla_VAE_Training.ipynb

{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"name":"Vanilla_VAE_Training.ipynb","provenance":[],"authorship_tag":"ABX9TyOuD6TEmxs3YcZn4nHQ0WRn"},"kernelspec":{"name":"python3","display_name":"Python 3"},"language_info":{"name":"python"}},"cells":[{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"YDWeS40yaDvq","executionInfo":{"status":"ok","timestamp":1622212945275,"user_tz":420,"elapsed":17356,"user":{"displayName":"Rohan Kapre","photoUrl":"","userId":"05196121123433733982"}},"outputId":"6e9d4637-b9ce-4a5c-c463-93b65ec9da95"},"source":["from google.colab import drive\n","drive.mount(\"/content/drive\",force_remount=True)"],"execution_count":null,"outputs":[{"output_type":"stream","text":["Mounted at /content/drive\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"Cdh23M02aKOE","executionInfo":{"status":"ok","timestamp":1622212947506,"user_tz":420,"elapsed":285,"user":{"displayName":"Rohan Kapre","photoUrl":"","userId":"05196121123433733982"}},"outputId":"0b13b3ca-332a-425f-ffe6-cebd0cb6afd7"},"source":["gpu_info = !nvidia-smi\n","gpu_info = '\\n'.join(gpu_info)\n","if gpu_info.find('failed') >= 0:\n","  print('Select the Runtime > \"Change runtime type\" menu to enable a GPU accelerator, ')\n","  print('and then re-execute this cell.')\n","else:\n","  print(gpu_info)"],"execution_count":null,"outputs":[{"output_type":"stream","text":["Fri May 28 14:42:27 2021       \n","+-----------------------------------------------------------------------------+\n","| NVIDIA-SMI 465.19.01    Driver Version: 460.32.03    CUDA Version: 11.2     |\n","|-------------------------------+----------------------+----------------------+\n","| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |\n","| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |\n","|                               |                      |               MIG M. |\n","|===============================+======================+======================|\n","|   0  Tesla P100-PCIE...  Off  | 00000000:00:04.0 Off |                    0 |\n","| N/A   33C    P0    26W / 250W |      0MiB / 16280MiB |      0%      Default |\n","|                               |                      |                  N/A |\n","+-------------------------------+----------------------+----------------------+\n","                                                                               \n","+-----------------------------------------------------------------------------+\n","| Processes:                                                                  |\n","|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |\n","|        ID   ID                                                   Usage      |\n","|=============================================================================|\n","|  No running processes found                                                 |\n","+-----------------------------------------------------------------------------+\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"3Hd3nFUfaL7E"},"source":["import os \n","os.chdir('drive/MyDrive/OASIS_Data')"],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"id":"b-dx-YUXaPIW"},"source":["import copy \n","import time\n","import datetime\n","import numpy as np \n","import pandas as pd \n","import nibabel as nib\n","import sklearn as skl\n","from sklearn.model_selection import train_test_split\n","import matplotlib.pyplot as plt"],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"id":"slhQGpFNaQ4v"},"source":["import torch \n","from torch.utils.data import Dataset, DataLoader\n","from torch import nn \n","from torch import optim"],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"xEetHGTPaSb0","executionInfo":{"status":"ok","timestamp":1622212969473,"user_tz":420,"elapsed":9996,"user":{"displayName":"Rohan Kapre","photoUrl":"","userId":"05196121123433733982"}},"outputId":"6c247586-d4a7-4f5a-8e0d-3b32c4661cd1"},"source":["pip install torchio nilearn"],"execution_count":null,"outputs":[{"output_type":"stream","text":["Collecting torchio\n","\u001b[?25l  Downloading https://files.pythonhosted.org/packages/2f/ab/fe4db746dbc1bd4a1fa37b6c7bb8ab6568cd1cc2b324f8140015c6cb389e/torchio-0.18.39-py2.py3-none-any.whl (143kB)\n","\u001b[K     |████████████████████████████████| 153kB 7.5MB/s \n","\u001b[?25hCollecting nilearn\n","\u001b[?25l  Downloading https://files.pythonhosted.org/packages/4a/bd/2ad86e2c00ecfe33b86f9f1f6d81de8e11724e822cdf1f5b2d0c21b787f1/nilearn-0.7.1-py3-none-any.whl (3.0MB)\n","\u001b[K     |████████████████████████████████| 3.1MB 27.3MB/s \n","\u001b[?25hCollecting Deprecated\n","  Downloading https://files.pythonhosted.org/packages/fb/73/994edfcba74443146c84b91921fcc269374354118d4f452fb0c54c1cbb12/Deprecated-1.2.12-py2.py3-none-any.whl\n","Requirement already satisfied: scipy in /usr/local/lib/python3.7/dist-packages (from torchio) (1.4.1)\n","Requirement already satisfied: tqdm in /usr/local/lib/python3.7/dist-packages (from torchio) (4.41.1)\n","Requirement already satisfied: humanize in /usr/local/lib/python3.7/dist-packages (from torchio) (0.5.1)\n","Collecting SimpleITK<2\n","\u001b[?25l  Downloading https://files.pythonhosted.org/packages/4a/ee/638b6bae2db10e5ef4ca94c95bb29ec25aa37a9d721b47f91077d7e985e0/SimpleITK-1.2.4-cp37-cp37m-manylinux1_x86_64.whl (42.5MB)\n","\u001b[K     |████████████████████████████████| 42.5MB 127kB/s \n","\u001b[?25hRequirement already satisfied: Click in /usr/local/lib/python3.7/dist-packages (from torchio) (7.1.2)\n","Requirement already satisfied: numpy in /usr/local/lib/python3.7/dist-packages (from torchio) (1.19.5)\n","Requirement already satisfied: nibabel in /usr/local/lib/python3.7/dist-packages (from torchio) (3.0.2)\n","Requirement already satisfied: torch>=1.1 in /usr/local/lib/python3.7/dist-packages (from torchio) (1.8.1+cu101)\n","Requirement already satisfied: pandas>=0.18.0 in /usr/local/lib/python3.7/dist-packages (from nilearn) (1.1.5)\n","Requirement already satisfied: requests>=2 in /usr/local/lib/python3.7/dist-packages (from nilearn) (2.23.0)\n","Requirement already satisfied: joblib>=0.12 in /usr/local/lib/python3.7/dist-packages (from nilearn) (1.0.1)\n","Requirement already satisfied: scikit-learn>=0.19 in /usr/local/lib/python3.7/dist-packages (from nilearn) (0.22.2.post1)\n","Requirement already satisfied: wrapt<2,>=1.10 in /usr/local/lib/python3.7/dist-packages (from Deprecated->torchio) (1.12.1)\n","Requirement already satisfied: typing-extensions in /usr/local/lib/python3.7/dist-packages (from torch>=1.1->torchio) (3.7.4.3)\n","Requirement already satisfied: pytz>=2017.2 in /usr/local/lib/python3.7/dist-packages (from pandas>=0.18.0->nilearn) (2018.9)\n","Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.7/dist-packages (from pandas>=0.18.0->nilearn) (2.8.1)\n","Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests>=2->nilearn) (1.24.3)\n","Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from requests>=2->nilearn) (3.0.4)\n","Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests>=2->nilearn) (2.10)\n","Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests>=2->nilearn) (2020.12.5)\n","Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.7/dist-packages (from python-dateutil>=2.7.3->pandas>=0.18.0->nilearn) (1.15.0)\n","Installing collected packages: Deprecated, SimpleITK, torchio, nilearn\n","Successfully installed Deprecated-1.2.12 SimpleITK-1.2.4 nilearn-0.7.1 torchio-0.18.39\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"bQ76B-2-aVpw"},"source":["import torchio as tio "],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"id":"OW6vnpeHaWEB"},"source":["os.chdir(\"MRI_SOMVAE\")\n","from OASISDataset import *\n","from FullModels import *\n","from TrainingTesting import *\n","from ExtraMetrics import *\n","os.chdir(\"..\")"],"execution_count":null,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"yjyKGWN8adqx"},"source":["Load and split training data into usable training and validation sets "]},{"cell_type":"code","metadata":{"id":"dZeheTFMaYSn"},"source":["fulltrainlist = pd.read_csv(\"oasis_ctrl_training.csv\")\n","\n","trainlist,vallist = train_test_split(fulltrainlist, random_state=128, test_size=0.15)\n","\n","folder = \"ctrl_original_resolution\""],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"sL2AFB3dagP5","executionInfo":{"status":"ok","timestamp":1622213160166,"user_tz":420,"elapsed":174928,"user":{"displayName":"Rohan Kapre","photoUrl":"","userId":"05196121123433733982"}},"outputId":"7d6c5a09-e3b5-4643-805e-9e712768bbb6"},"source":["start = time.time()\n","traindataset = OASISDataset_Colab(folder,trainlist)\n","print(time.time()-start)\n","valdataset = OASISDataset_Colab(folder,vallist)\n","print(time.time()-start)"],"execution_count":null,"outputs":[{"output_type":"stream","text":["149.35125541687012\n","174.68431186676025\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"xBmF6BIyaiGl"},"source":["batch_size=32\n","\n","train_dataloader = DataLoader(traindataset,batch_size=batch_size,shuffle=True)\n","val_dataloader = DataLoader(valdataset,batch_size=len(valdataset),shuffle=True)"],"execution_count":null,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"-5f_PqwfaoYb"},"source":["Set up Model Training on VanillaVAE. Using Adam Optimizer with learning rate of 0.005. Encoder dimension is 32. 250 epochs of training. "]},{"cell_type":"code","metadata":{"id":"Lkk_5_6daxyk"},"source":["VAE = VanillaVAE(num_channels = 1,num_filters = 4,embedding_dim = 32)\n","\n","loss_fn = nn.MSELoss(reduction=\"mean\")\n"],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"id":"fR6yz604a-zn"},"source":["optimizer = optim.Adam(VAE.parameters(),lr=0.005)"],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"id":"5w5cq6YFbEex"},"source":["max_epochs = 250\n","\n","train_losses= np.zeros(max_epochs)\n","val_losses = np.zeros(max_epochs)"],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"02SSbT4qbGC9","executionInfo":{"status":"ok","timestamp":1622220283090,"user_tz":420,"elapsed":6988212,"user":{"displayName":"Rohan Kapre","photoUrl":"","userId":"05196121123433733982"}},"outputId":"1f88d389-60cb-4cf4-c8db-2faf84972334"},"source":["for epoch in range(max_epochs):\n","    train_losses[epoch] = train_vae(VAE,optimizer,loss_fn,train_dataloader,epoch)\n","    val_losses[epoch] = test_vae(VAE,loss_fn,val_dataloader)\n"],"execution_count":null,"outputs":[{"output_type":"stream","text":["====> Begin epoch 1\n","\n","\n","====> Epoch: 1 Average loss: 0.0431\tTime elapsed: 0:00:30\n","====> Test set loss: 0.0579\tTime elapsed: 0:00:06\n","\n","====> Begin epoch 2\n","\n","\n","====> Epoch: 2 Average loss: 0.0396\tTime elapsed: 0:00:27\n","====> Test set loss: 0.1417\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 3\n","\n","\n","====> Epoch: 3 Average loss: 0.0544\tTime elapsed: 0:00:27\n","====> Test set loss: 0.0564\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 4\n","\n","\n","====> Epoch: 4 Average loss: 0.0405\tTime elapsed: 0:00:26\n","====> Test set loss: 0.0556\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 5\n","\n","\n","====> Epoch: 5 Average loss: 0.0399\tTime elapsed: 0:00:26\n","====> Test set loss: 0.0553\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 6\n","\n","\n","====> Epoch: 6 Average loss: 0.0398\tTime elapsed: 0:00:25\n","====> Test set loss: 0.0553\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 7\n","\n","\n","====> Epoch: 7 Average loss: 0.0396\tTime elapsed: 0:00:25\n","====> Test set loss: 0.0548\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 8\n","\n","\n","====> Epoch: 8 Average loss: 0.0391\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0540\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 9\n","\n","\n","====> Epoch: 9 Average loss: 0.0385\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0528\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 10\n","\n","\n","====> Epoch: 10 Average loss: 0.0375\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0513\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 11\n","\n","\n","====> Epoch: 11 Average loss: 0.0364\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0500\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 12\n","\n","\n","====> Epoch: 12 Average loss: 0.0357\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0491\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 13\n","\n","\n","====> Epoch: 13 Average loss: 0.0347\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0480\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 14\n","\n","\n","====> Epoch: 14 Average loss: 0.0337\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0470\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 15\n","\n","\n","====> Epoch: 15 Average loss: 0.0328\tTime elapsed: 0:00:25\n","====> Test set loss: 0.0441\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 16\n","\n","\n","====> Epoch: 16 Average loss: 0.0319\tTime elapsed: 0:00:25\n","====> Test set loss: 0.0422\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 17\n","\n","\n","====> Epoch: 17 Average loss: 0.0305\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0411\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 18\n","\n","\n","====> Epoch: 18 Average loss: 0.0293\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0379\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 19\n","\n","\n","====> Epoch: 19 Average loss: 0.0264\tTime elapsed: 0:00:25\n","====> Test set loss: 0.0339\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 20\n","\n","\n","====> Epoch: 20 Average loss: 0.0239\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0316\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 21\n","\n","\n","====> Epoch: 21 Average loss: 0.0224\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0302\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 22\n","\n","\n","====> Epoch: 22 Average loss: 0.0216\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0294\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 23\n","\n","\n","====> Epoch: 23 Average loss: 0.0211\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0288\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 24\n","\n","\n","====> Epoch: 24 Average loss: 0.0207\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0284\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 25\n","\n","\n","====> Epoch: 25 Average loss: 0.0205\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0281\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 26\n","\n","\n","====> Epoch: 26 Average loss: 0.0203\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0278\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 27\n","\n","\n","====> Epoch: 27 Average loss: 0.0201\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0276\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 28\n","\n","\n","====> Epoch: 28 Average loss: 0.0199\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0273\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 29\n","\n","\n","====> Epoch: 29 Average loss: 0.0197\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0271\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 30\n","\n","\n","====> Epoch: 30 Average loss: 0.0196\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0270\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 31\n","\n","\n","====> Epoch: 31 Average loss: 0.0195\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0270\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 32\n","\n","\n","====> Epoch: 32 Average loss: 0.0195\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0269\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 33\n","\n","\n","====> Epoch: 33 Average loss: 0.0194\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0267\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 34\n","\n","\n","====> Epoch: 34 Average loss: 0.0194\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0267\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 35\n","\n","\n","====> Epoch: 35 Average loss: 0.0192\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0264\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 36\n","\n","\n","====> Epoch: 36 Average loss: 0.0191\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0263\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 37\n","\n","\n","====> Epoch: 37 Average loss: 0.0190\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0262\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 38\n","\n","\n","====> Epoch: 38 Average loss: 0.0189\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0262\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 39\n","\n","\n","====> Epoch: 39 Average loss: 0.0189\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0258\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 40\n","\n","\n","====> Epoch: 40 Average loss: 0.0187\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0258\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 41\n","\n","\n","====> Epoch: 41 Average loss: 0.0186\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0257\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 42\n","\n","\n","====> Epoch: 42 Average loss: 0.0186\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0256\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 43\n","\n","\n","====> Epoch: 43 Average loss: 0.0185\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0256\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 44\n","\n","\n","====> Epoch: 44 Average loss: 0.0185\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0254\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 45\n","\n","\n","====> Epoch: 45 Average loss: 0.0184\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0254\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 46\n","\n","\n","====> Epoch: 46 Average loss: 0.0184\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0254\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 47\n","\n","\n","====> Epoch: 47 Average loss: 0.0184\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0254\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 48\n","\n","\n","====> Epoch: 48 Average loss: 0.0183\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0253\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 49\n","\n","\n","====> Epoch: 49 Average loss: 0.0183\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0253\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 50\n","\n","\n","====> Epoch: 50 Average loss: 0.0183\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0252\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 51\n","\n","\n","====> Epoch: 51 Average loss: 0.0182\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0251\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 52\n","\n","\n","====> Epoch: 52 Average loss: 0.0182\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0251\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 53\n","\n","\n","====> Epoch: 53 Average loss: 0.0181\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0251\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 54\n","\n","\n","====> Epoch: 54 Average loss: 0.0181\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0251\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 55\n","\n","\n","====> Epoch: 55 Average loss: 0.0181\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0249\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 56\n","\n","\n","====> Epoch: 56 Average loss: 0.0181\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0249\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 57\n","\n","\n","====> Epoch: 57 Average loss: 0.0180\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0249\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 58\n","\n","\n","====> Epoch: 58 Average loss: 0.0180\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0248\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 59\n","\n","\n","====> Epoch: 59 Average loss: 0.0180\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0249\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 60\n","\n","\n","====> Epoch: 60 Average loss: 0.0179\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0248\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 61\n","\n","\n","====> Epoch: 61 Average loss: 0.0179\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0248\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 62\n","\n","\n","====> Epoch: 62 Average loss: 0.0179\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0248\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 63\n","\n","\n","====> Epoch: 63 Average loss: 0.0179\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0246\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 64\n","\n","\n","====> Epoch: 64 Average loss: 0.0179\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0247\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 65\n","\n","\n","====> Epoch: 65 Average loss: 0.0178\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0245\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 66\n","\n","\n","====> Epoch: 66 Average loss: 0.0178\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0245\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 67\n","\n","\n","====> Epoch: 67 Average loss: 0.0178\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0245\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 68\n","\n","\n","====> Epoch: 68 Average loss: 0.0177\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0244\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 69\n","\n","\n","====> Epoch: 69 Average loss: 0.0177\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0244\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 70\n","\n","\n","====> Epoch: 70 Average loss: 0.0177\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0244\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 71\n","\n","\n","====> Epoch: 71 Average loss: 0.0176\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0244\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 72\n","\n","\n","====> Epoch: 72 Average loss: 0.0176\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0244\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 73\n","\n","\n","====> Epoch: 73 Average loss: 0.0176\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0243\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 74\n","\n","\n","====> Epoch: 74 Average loss: 0.0176\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0243\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 75\n","\n","\n","====> Epoch: 75 Average loss: 0.0175\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0242\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 76\n","\n","\n","====> Epoch: 76 Average loss: 0.0175\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0242\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 77\n","\n","\n","====> Epoch: 77 Average loss: 0.0175\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0242\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 78\n","\n","\n","====> Epoch: 78 Average loss: 0.0175\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0241\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 79\n","\n","\n","====> Epoch: 79 Average loss: 0.0175\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0241\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 80\n","\n","\n","====> Epoch: 80 Average loss: 0.0174\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0241\tTime elapsed: 0:00:04\n","\n","====> Begin epoch 81\n","\n","\n","====> Epoch: 81 Average loss: 0.0174\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0242\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 82\n","\n","\n","====> Epoch: 82 Average loss: 0.0174\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0240\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 83\n","\n","\n","====> Epoch: 83 Average loss: 0.0174\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0240\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 84\n","\n","\n","====> Epoch: 84 Average loss: 0.0173\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0239\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 85\n","\n","\n","====> Epoch: 85 Average loss: 0.0173\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0239\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 86\n","\n","\n","====> Epoch: 86 Average loss: 0.0173\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0239\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 87\n","\n","\n","====> Epoch: 87 Average loss: 0.0173\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0239\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 88\n","\n","\n","====> Epoch: 88 Average loss: 0.0172\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0239\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 89\n","\n","\n","====> Epoch: 89 Average loss: 0.0172\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0239\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 90\n","\n","\n","====> Epoch: 90 Average loss: 0.0172\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0237\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 91\n","\n","\n","====> Epoch: 91 Average loss: 0.0172\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0237\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 92\n","\n","\n","====> Epoch: 92 Average loss: 0.0171\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0238\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 93\n","\n","\n","====> Epoch: 93 Average loss: 0.0171\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0238\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 94\n","\n","\n","====> Epoch: 94 Average loss: 0.0171\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0237\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 95\n","\n","\n","====> Epoch: 95 Average loss: 0.0171\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0238\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 96\n","\n","\n","====> Epoch: 96 Average loss: 0.0171\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0237\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 97\n","\n","\n","====> Epoch: 97 Average loss: 0.0171\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0236\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 98\n","\n","\n","====> Epoch: 98 Average loss: 0.0170\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0236\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 99\n","\n","\n","====> Epoch: 99 Average loss: 0.0170\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0235\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 100\n","\n","\n","====> Epoch: 100 Average loss: 0.0170\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0235\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 101\n","\n","\n","====> Epoch: 101 Average loss: 0.0170\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0235\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 102\n","\n","\n","====> Epoch: 102 Average loss: 0.0169\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0234\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 103\n","\n","\n","====> Epoch: 103 Average loss: 0.0169\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0234\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 104\n","\n","\n","====> Epoch: 104 Average loss: 0.0169\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0234\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 105\n","\n","\n","====> Epoch: 105 Average loss: 0.0169\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0233\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 106\n","\n","\n","====> Epoch: 106 Average loss: 0.0169\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0235\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 107\n","\n","\n","====> Epoch: 107 Average loss: 0.0169\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0233\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 108\n","\n","\n","====> Epoch: 108 Average loss: 0.0168\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0233\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 109\n","\n","\n","====> Epoch: 109 Average loss: 0.0168\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0233\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 110\n","\n","\n","====> Epoch: 110 Average loss: 0.0168\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0232\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 111\n","\n","\n","====> Epoch: 111 Average loss: 0.0168\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0232\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 112\n","\n","\n","====> Epoch: 112 Average loss: 0.0168\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0233\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 113\n","\n","\n","====> Epoch: 113 Average loss: 0.0168\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0232\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 114\n","\n","\n","====> Epoch: 114 Average loss: 0.0167\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0232\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 115\n","\n","\n","====> Epoch: 115 Average loss: 0.0168\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0231\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 116\n","\n","\n","====> Epoch: 116 Average loss: 0.0167\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0231\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 117\n","\n","\n","====> Epoch: 117 Average loss: 0.0167\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0233\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 118\n","\n","\n","====> Epoch: 118 Average loss: 0.0168\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0231\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 119\n","\n","\n","====> Epoch: 119 Average loss: 0.0167\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0231\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 120\n","\n","\n","====> Epoch: 120 Average loss: 0.0167\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0231\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 121\n","\n","\n","====> Epoch: 121 Average loss: 0.0167\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0230\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 122\n","\n","\n","====> Epoch: 122 Average loss: 0.0167\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0232\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 123\n","\n","\n","====> Epoch: 123 Average loss: 0.0167\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0230\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 124\n","\n","\n","====> Epoch: 124 Average loss: 0.0166\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0230\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 125\n","\n","\n","====> Epoch: 125 Average loss: 0.0166\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0230\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 126\n","\n","\n","====> Epoch: 126 Average loss: 0.0166\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0230\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 127\n","\n","\n","====> Epoch: 127 Average loss: 0.0166\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0229\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 128\n","\n","\n","====> Epoch: 128 Average loss: 0.0166\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0229\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 129\n","\n","\n","====> Epoch: 129 Average loss: 0.0167\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0235\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 130\n","\n","\n","====> Epoch: 130 Average loss: 0.0168\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0233\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 131\n","\n","\n","====> Epoch: 131 Average loss: 0.0167\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0232\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 132\n","\n","\n","====> Epoch: 132 Average loss: 0.0167\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0230\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 133\n","\n","\n","====> Epoch: 133 Average loss: 0.0166\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0229\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 134\n","\n","\n","====> Epoch: 134 Average loss: 0.0166\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0229\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 135\n","\n","\n","====> Epoch: 135 Average loss: 0.0166\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0229\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 136\n","\n","\n","====> Epoch: 136 Average loss: 0.0165\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0229\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 137\n","\n","\n","====> Epoch: 137 Average loss: 0.0165\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0229\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 138\n","\n","\n","====> Epoch: 138 Average loss: 0.0165\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0228\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 139\n","\n","\n","====> Epoch: 139 Average loss: 0.0165\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0228\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 140\n","\n","\n","====> Epoch: 140 Average loss: 0.0165\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0227\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 141\n","\n","\n","====> Epoch: 141 Average loss: 0.0165\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0228\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 142\n","\n","\n","====> Epoch: 142 Average loss: 0.0164\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0228\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 143\n","\n","\n","====> Epoch: 143 Average loss: 0.0165\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0228\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 144\n","\n","\n","====> Epoch: 144 Average loss: 0.0165\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0228\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 145\n","\n","\n","====> Epoch: 145 Average loss: 0.0164\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0227\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 146\n","\n","\n","====> Epoch: 146 Average loss: 0.0164\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0227\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 147\n","\n","\n","====> Epoch: 147 Average loss: 0.0164\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0227\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 148\n","\n","\n","====> Epoch: 148 Average loss: 0.0164\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0228\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 149\n","\n","\n","====> Epoch: 149 Average loss: 0.0164\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0226\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 150\n","\n","\n","====> Epoch: 150 Average loss: 0.0163\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0226\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 151\n","\n","\n","====> Epoch: 151 Average loss: 0.0164\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0237\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 152\n","\n","\n","====> Epoch: 152 Average loss: 0.0167\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0230\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 153\n","\n","\n","====> Epoch: 153 Average loss: 0.0165\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0229\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 154\n","\n","\n","====> Epoch: 154 Average loss: 0.0165\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0228\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 155\n","\n","\n","====> Epoch: 155 Average loss: 0.0164\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0227\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 156\n","\n","\n","====> Epoch: 156 Average loss: 0.0164\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0227\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 157\n","\n","\n","====> Epoch: 157 Average loss: 0.0164\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0227\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 158\n","\n","\n","====> Epoch: 158 Average loss: 0.0164\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0226\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 159\n","\n","\n","====> Epoch: 159 Average loss: 0.0163\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0226\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 160\n","\n","\n","====> Epoch: 160 Average loss: 0.0163\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0226\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 161\n","\n","\n","====> Epoch: 161 Average loss: 0.0163\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0225\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 162\n","\n","\n","====> Epoch: 162 Average loss: 0.0163\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0226\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 163\n","\n","\n","====> Epoch: 163 Average loss: 0.0163\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0226\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 164\n","\n","\n","====> Epoch: 164 Average loss: 0.0163\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0225\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 165\n","\n","\n","====> Epoch: 165 Average loss: 0.0163\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0226\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 166\n","\n","\n","====> Epoch: 166 Average loss: 0.0163\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0226\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 167\n","\n","\n","====> Epoch: 167 Average loss: 0.0163\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0225\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 168\n","\n","\n","====> Epoch: 168 Average loss: 0.0162\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0225\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 169\n","\n","\n","====> Epoch: 169 Average loss: 0.0162\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0224\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 170\n","\n","\n","====> Epoch: 170 Average loss: 0.0162\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0227\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 171\n","\n","\n","====> Epoch: 171 Average loss: 0.0164\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0227\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 172\n","\n","\n","====> Epoch: 172 Average loss: 0.0163\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0226\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 173\n","\n","\n","====> Epoch: 173 Average loss: 0.0163\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0225\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 174\n","\n","\n","====> Epoch: 174 Average loss: 0.0162\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0224\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 175\n","\n","\n","====> Epoch: 175 Average loss: 0.0162\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0225\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 176\n","\n","\n","====> Epoch: 176 Average loss: 0.0162\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0227\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 177\n","\n","\n","====> Epoch: 177 Average loss: 0.0163\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0225\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 178\n","\n","\n","====> Epoch: 178 Average loss: 0.0162\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0226\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 179\n","\n","\n","====> Epoch: 179 Average loss: 0.0163\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0224\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 180\n","\n","\n","====> Epoch: 180 Average loss: 0.0162\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0224\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 181\n","\n","\n","====> Epoch: 181 Average loss: 0.0162\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0225\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 182\n","\n","\n","====> Epoch: 182 Average loss: 0.0162\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0224\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 183\n","\n","\n","====> Epoch: 183 Average loss: 0.0162\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0224\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 184\n","\n","\n","====> Epoch: 184 Average loss: 0.0162\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0224\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 185\n","\n","\n","====> Epoch: 185 Average loss: 0.0161\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0225\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 186\n","\n","\n","====> Epoch: 186 Average loss: 0.0162\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0223\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 187\n","\n","\n","====> Epoch: 187 Average loss: 0.0161\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0223\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 188\n","\n","\n","====> Epoch: 188 Average loss: 0.0161\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0223\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 189\n","\n","\n","====> Epoch: 189 Average loss: 0.0162\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0225\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 190\n","\n","\n","====> Epoch: 190 Average loss: 0.0162\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0223\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 191\n","\n","\n","====> Epoch: 191 Average loss: 0.0162\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0224\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 192\n","\n","\n","====> Epoch: 192 Average loss: 0.0161\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0223\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 193\n","\n","\n","====> Epoch: 193 Average loss: 0.0161\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0223\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 194\n","\n","\n","====> Epoch: 194 Average loss: 0.0165\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0225\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 195\n","\n","\n","====> Epoch: 195 Average loss: 0.0164\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0226\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 196\n","\n","\n","====> Epoch: 196 Average loss: 0.0163\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0225\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 197\n","\n","\n","====> Epoch: 197 Average loss: 0.0162\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0225\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 198\n","\n","\n","====> Epoch: 198 Average loss: 0.0162\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0224\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 199\n","\n","\n","====> Epoch: 199 Average loss: 0.0162\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0223\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 200\n","\n","\n","====> Epoch: 200 Average loss: 0.0162\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0224\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 201\n","\n","\n","====> Epoch: 201 Average loss: 0.0161\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0224\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 202\n","\n","\n","====> Epoch: 202 Average loss: 0.0161\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0223\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 203\n","\n","\n","====> Epoch: 203 Average loss: 0.0161\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0224\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 204\n","\n","\n","====> Epoch: 204 Average loss: 0.0162\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0223\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 205\n","\n","\n","====> Epoch: 205 Average loss: 0.0161\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0224\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 206\n","\n","\n","====> Epoch: 206 Average loss: 0.0161\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0223\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 207\n","\n","\n","====> Epoch: 207 Average loss: 0.0161\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0223\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 208\n","\n","\n","====> Epoch: 208 Average loss: 0.0161\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0223\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 209\n","\n","\n","====> Epoch: 209 Average loss: 0.0161\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0222\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 210\n","\n","\n","====> Epoch: 210 Average loss: 0.0161\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0223\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 211\n","\n","\n","====> Epoch: 211 Average loss: 0.0162\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0223\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 212\n","\n","\n","====> Epoch: 212 Average loss: 0.0161\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0224\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 213\n","\n","\n","====> Epoch: 213 Average loss: 0.0161\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0222\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 214\n","\n","\n","====> Epoch: 214 Average loss: 0.0161\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0223\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 215\n","\n","\n","====> Epoch: 215 Average loss: 0.0161\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0222\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 216\n","\n","\n","====> Epoch: 216 Average loss: 0.0160\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0223\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 217\n","\n","\n","====> Epoch: 217 Average loss: 0.0161\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0222\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 218\n","\n","\n","====> Epoch: 218 Average loss: 0.0160\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0222\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 219\n","\n","\n","====> Epoch: 219 Average loss: 0.0161\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0223\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 220\n","\n","\n","====> Epoch: 220 Average loss: 0.0161\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0223\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 221\n","\n","\n","====> Epoch: 221 Average loss: 0.0161\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0222\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 222\n","\n","\n","====> Epoch: 222 Average loss: 0.0161\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0223\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 223\n","\n","\n","====> Epoch: 223 Average loss: 0.0161\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0223\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 224\n","\n","\n","====> Epoch: 224 Average loss: 0.0161\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0222\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 225\n","\n","\n","====> Epoch: 225 Average loss: 0.0160\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0222\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 226\n","\n","\n","====> Epoch: 226 Average loss: 0.0161\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0224\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 227\n","\n","\n","====> Epoch: 227 Average loss: 0.0161\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0222\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 228\n","\n","\n","====> Epoch: 228 Average loss: 0.0161\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0223\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 229\n","\n","\n","====> Epoch: 229 Average loss: 0.0160\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0221\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 230\n","\n","\n","====> Epoch: 230 Average loss: 0.0160\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0221\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 231\n","\n","\n","====> Epoch: 231 Average loss: 0.0160\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0222\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 232\n","\n","\n","====> Epoch: 232 Average loss: 0.0160\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0222\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 233\n","\n","\n","====> Epoch: 233 Average loss: 0.0160\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0222\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 234\n","\n","\n","====> Epoch: 234 Average loss: 0.0160\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0221\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 235\n","\n","\n","====> Epoch: 235 Average loss: 0.0160\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0222\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 236\n","\n","\n","====> Epoch: 236 Average loss: 0.0161\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0222\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 237\n","\n","\n","====> Epoch: 237 Average loss: 0.0160\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0223\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 238\n","\n","\n","====> Epoch: 238 Average loss: 0.0160\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0221\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 239\n","\n","\n","====> Epoch: 239 Average loss: 0.0160\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0221\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 240\n","\n","\n","====> Epoch: 240 Average loss: 0.0160\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0221\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 241\n","\n","\n","====> Epoch: 241 Average loss: 0.0160\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0221\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 242\n","\n","\n","====> Epoch: 242 Average loss: 0.0159\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0220\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 243\n","\n","\n","====> Epoch: 243 Average loss: 0.0159\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0221\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 244\n","\n","\n","====> Epoch: 244 Average loss: 0.0162\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0222\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 245\n","\n","\n","====> Epoch: 245 Average loss: 0.0161\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0223\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 246\n","\n","\n","====> Epoch: 246 Average loss: 0.0161\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0222\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 247\n","\n","\n","====> Epoch: 247 Average loss: 0.0160\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0222\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 248\n","\n","\n","====> Epoch: 248 Average loss: 0.0160\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0221\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 249\n","\n","\n","====> Epoch: 249 Average loss: 0.0160\tTime elapsed: 0:00:24\n","====> Test set loss: 0.0222\tTime elapsed: 0:00:03\n","\n","====> Begin epoch 250\n","\n","\n","====> Epoch: 250 Average loss: 0.0160\tTime elapsed: 0:00:23\n","====> Test set loss: 0.0222\tTime elapsed: 0:00:03\n","\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"u2VvgSRvcoKY"},"source":["torch.save({\"epoch\": epoch,\"model_state_dict\": VAE.state_dict(),\"optimizer_state_dict\": optimizer.state_dict(),\"train_loss\": train_losses,\"val_loss\": val_losses},\n","           \"VanillaVAE32_250epochs.tar\")"],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"id":"kTELXVrI4we-"},"source":["import matplotlib.pyplot as plt\n"],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":265},"id":"f-R_VNSH8k4-","executionInfo":{"status":"ok","timestamp":1622221710727,"user_tz":420,"elapsed":149,"user":{"displayName":"Rohan Kapre","photoUrl":"","userId":"05196121123433733982"}},"outputId":"19a59576-3fa3-42e7-de24-cf41d63703df"},"source":["plt.plot(np.log10(train_losses))\n","plt.plot(np.log10(val_losses))\n","plt.show()"],"execution_count":null,"outputs":[{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"tags":[],"needs_background":"light"}}]}]}