src/torch-mlp-tuned.ipynb

{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"name":"python","version":"3.7.12","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"markdown","source":"# MLP with the Adam optimizer trained on the Fashion-MNIST dataset using PyTorch","metadata":{}},{"cell_type":"code","source":"from torch.optim import Adam\nfrom torch.nn import NLLLoss\nfrom torchvision.datasets import FashionMNIST\nfrom torchvision.transforms import ToTensor\nfrom sklearn.metrics import classification_report\nimport wandb\nfrom pprint import pprint\n\nfrom torch_utils import split_data, create_model, fit, evaluate\nfrom plot_utils import plot_training, show_confusion_matrix","metadata":{"execution":{"iopub.status.busy":"2023-03-11T14:21:39.114042Z","iopub.execute_input":"2023-03-11T14:21:39.114812Z","iopub.status.idle":"2023-03-11T14:21:42.555318Z","shell.execute_reply.started":"2023-03-11T14:21:39.114769Z","shell.execute_reply":"2023-03-11T14:21:42.554017Z"},"trusted":true},"execution_count":1,"outputs":[]},{"cell_type":"markdown","source":"## Login to Wandb","metadata":{}},{"cell_type":"code","source":"wandb.login()","metadata":{"execution":{"iopub.status.busy":"2023-03-11T14:21:42.557775Z","iopub.execute_input":"2023-03-11T14:21:42.558398Z","iopub.status.idle":"2023-03-11T14:21:47.453200Z","shell.execute_reply.started":"2023-03-11T14:21:42.558356Z","shell.execute_reply":"2023-03-11T14:21:47.451996Z"},"trusted":true},"execution_count":2,"outputs":[{"name":"stderr","text":"\u001b[34m\u001b[1mwandb\u001b[0m: Logging into wandb.ai. (Learn how to deploy a W&B server locally: https://wandb.me/wandb-server)\n\u001b[34m\u001b[1mwandb\u001b[0m: You can find your API key in your browser here: https://wandb.ai/authorize\n\u001b[34m\u001b[1mwandb\u001b[0m: Paste an API key from your profile and hit enter, or press ctrl+c to quit:","output_type":"stream"},{"output_type":"stream","name":"stdin","text":"  ········································\n"},{"name":"stderr","text":"\u001b[34m\u001b[1mwandb\u001b[0m: Appending key for api.wandb.ai to your netrc file: /root/.netrc\n","output_type":"stream"},{"execution_count":2,"output_type":"execute_result","data":{"text/plain":"True"},"metadata":{}}]},{"cell_type":"markdown","source":"## Load best hyperparameters from the Tensorflow run","metadata":{}},{"cell_type":"code","source":"api = wandb.Api()\nsweep = api.sweep(\"nsiete23/tf_mlp/sweeps/12a25071\")\n\nbest_config = sweep.best_run().config\npprint(best_config)\n\nwandb.init(config=best_config, project='torch_mlp', name='best-mlp-torch')\nconfig = wandb.config","metadata":{"execution":{"iopub.status.busy":"2023-03-11T14:21:47.455084Z","iopub.execute_input":"2023-03-11T14:21:47.455929Z","iopub.status.idle":"2023-03-11T14:22:18.303291Z","shell.execute_reply.started":"2023-03-11T14:21:47.455878Z","shell.execute_reply":"2023-03-11T14:22:18.302280Z"},"trusted":true},"execution_count":3,"outputs":[{"name":"stderr","text":"\u001b[34m\u001b[1mwandb\u001b[0m: Sorting runs by +summary_metrics.val_loss\n\u001b[34m\u001b[1mwandb\u001b[0m: Currently logged in as: \u001b[33mv-modroczky\u001b[0m (\u001b[33mnsiete23\u001b[0m). Use \u001b[1m`wandb login --relogin`\u001b[0m to force relogin\n","output_type":"stream"},{"name":"stdout","text":"{'batch_size': 128,\n 'beta_1': 0.986435025614692,\n 'beta_2': 0.9904482393527106,\n 'dense_1': 485,\n 'dense_2': 176,\n 'dense_3': 131,\n 'dense_4': 122,\n 'epochs': 19,\n 'learning_rate': 0.00012885226472854095}\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"<IPython.core.display.HTML object>","text/html":"wandb version 0.13.11 is available!  To upgrade, please run:\n $ pip install wandb --upgrade"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"<IPython.core.display.HTML object>","text/html":"Tracking run with wandb version 0.13.10"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"<IPython.core.display.HTML object>","text/html":"Run data is saved locally in <code>/kaggle/working/wandb/run-20230311_142147-qfy6r37f</code>"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"<IPython.core.display.HTML object>","text/html":"Syncing run <strong><a href='https://wandb.ai/nsiete23/torch_mlp/runs/qfy6r37f' target=\"_blank\">best-mlp-torch</a></strong> to <a href='https://wandb.ai/nsiete23/torch_mlp' target=\"_blank\">Weights & Biases</a> (<a href='https://wandb.me/run' target=\"_blank\">docs</a>)<br/>"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"<IPython.core.display.HTML object>","text/html":" View project at <a href='https://wandb.ai/nsiete23/torch_mlp' target=\"_blank\">https://wandb.ai/nsiete23/torch_mlp</a>"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"<IPython.core.display.HTML object>","text/html":" View run at <a href='https://wandb.ai/nsiete23/torch_mlp/runs/qfy6r37f' target=\"_blank\">https://wandb.ai/nsiete23/torch_mlp/runs/qfy6r37f</a>"},"metadata":{}}]},{"cell_type":"markdown","source":"## Load dataset","metadata":{}},{"cell_type":"code","source":"data = FashionMNIST(root='../data', download=True, transform=ToTensor())\ntest = FashionMNIST(root='../data', download=True, train=False, transform=ToTensor())\n\ntrain_loader, val_loader, test_loader = split_data(data, test, batch_size=config.batch_size)\n\nprint(len(train_loader.dataset))\nprint(len(val_loader.dataset))\nprint(len(test_loader.dataset))","metadata":{"execution":{"iopub.status.busy":"2023-03-11T14:22:18.306584Z","iopub.execute_input":"2023-03-11T14:22:18.307250Z","iopub.status.idle":"2023-03-11T14:22:23.651464Z","shell.execute_reply.started":"2023-03-11T14:22:18.307211Z","shell.execute_reply":"2023-03-11T14:22:23.650445Z"},"trusted":true},"execution_count":4,"outputs":[{"name":"stdout","text":"Downloading http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/train-images-idx3-ubyte.gz\nDownloading http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/train-images-idx3-ubyte.gz to ../data/FashionMNIST/raw/train-images-idx3-ubyte.gz\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"  0%|          | 0/26421880 [00:00<?, ?it/s]","application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"1a83dee3336d4d9790a5b14932e76833"}},"metadata":{}},{"name":"stdout","text":"Extracting ../data/FashionMNIST/raw/train-images-idx3-ubyte.gz to ../data/FashionMNIST/raw\n\nDownloading http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/train-labels-idx1-ubyte.gz\nDownloading http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/train-labels-idx1-ubyte.gz to ../data/FashionMNIST/raw/train-labels-idx1-ubyte.gz\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"  0%|          | 0/29515 [00:00<?, ?it/s]","application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"18ed4c3934d643798c8442ad90fd4f31"}},"metadata":{}},{"name":"stdout","text":"Extracting ../data/FashionMNIST/raw/train-labels-idx1-ubyte.gz to ../data/FashionMNIST/raw\n\nDownloading http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/t10k-images-idx3-ubyte.gz\nDownloading http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/t10k-images-idx3-ubyte.gz to ../data/FashionMNIST/raw/t10k-images-idx3-ubyte.gz\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"  0%|          | 0/4422102 [00:00<?, ?it/s]","application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"0a1f6c98b2844fd1823341639e883f6e"}},"metadata":{}},{"name":"stdout","text":"Extracting ../data/FashionMNIST/raw/t10k-images-idx3-ubyte.gz to ../data/FashionMNIST/raw\n\nDownloading http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/t10k-labels-idx1-ubyte.gz\nDownloading http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/t10k-labels-idx1-ubyte.gz to ../data/FashionMNIST/raw/t10k-labels-idx1-ubyte.gz\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"  0%|          | 0/5148 [00:00<?, ?it/s]","application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"91611f5378324345b33275bbf5766c0d"}},"metadata":{}},{"name":"stdout","text":"Extracting ../data/FashionMNIST/raw/t10k-labels-idx1-ubyte.gz to ../data/FashionMNIST/raw\n\n48000\n12000\n10000\n","output_type":"stream"}]},{"cell_type":"markdown","source":"## Create model","metadata":{}},{"cell_type":"code","source":"mlp = create_model(config)\n\nloss = NLLLoss()\noptimizer = Adam(mlp.parameters(), lr=config.learning_rate, betas=(config.beta_1, config.beta_2))","metadata":{"execution":{"iopub.status.busy":"2023-03-11T14:22:23.655781Z","iopub.execute_input":"2023-03-11T14:22:23.658107Z","iopub.status.idle":"2023-03-11T14:22:23.682706Z","shell.execute_reply.started":"2023-03-11T14:22:23.658067Z","shell.execute_reply":"2023-03-11T14:22:23.681784Z"},"trusted":true},"execution_count":5,"outputs":[]},{"cell_type":"markdown","source":"## Train model and finish Wandb run","metadata":{}},{"cell_type":"code","source":"history = fit(mlp, train_loader, val_loader, optimizer, loss, config.epochs, config.batch_size)\nwandb.finish()","metadata":{"execution":{"iopub.status.busy":"2023-03-11T14:22:23.687407Z","iopub.execute_input":"2023-03-11T14:22:23.689906Z","iopub.status.idle":"2023-03-11T14:25:04.261085Z","shell.execute_reply.started":"2023-03-11T14:22:23.689867Z","shell.execute_reply":"2023-03-11T14:25:04.260201Z"},"trusted":true},"execution_count":6,"outputs":[{"name":"stdout","text":"Epoch 1/19: loss 1.1536671412785848, val_loss 0.6919355344772339, accuracy 0.5993333333333334, val_accuracy 0.7325833333333334\nEpoch 2/19: loss 0.634277834335963, val_loss 0.5656527795791626, accuracy 0.766, val_accuracy 0.7965\nEpoch 3/19: loss 0.543801552216212, val_loss 0.5013695669174194, accuracy 0.8078541666666667, val_accuracy 0.8279166666666666\nEpoch 4/19: loss 0.4859077597459157, val_loss 0.4500073585510254, accuracy 0.8293541666666666, val_accuracy 0.84525\nEpoch 5/19: loss 0.45278780682881675, val_loss 0.43975549379984535, accuracy 0.8411458333333334, val_accuracy 0.8484166666666667\nEpoch 6/19: loss 0.4281736028989156, val_loss 0.4188218866984049, accuracy 0.84925, val_accuracy 0.8546666666666667\nEpoch 7/19: loss 0.4104100909233093, val_loss 0.40643049160639444, accuracy 0.8542291666666667, val_accuracy 0.8589166666666667\nEpoch 8/19: loss 0.39190225104490917, val_loss 0.39198314905166626, accuracy 0.860625, val_accuracy 0.8603333333333333\nEpoch 9/19: loss 0.3797987955411275, val_loss 0.3810535699526469, accuracy 0.86525, val_accuracy 0.8645833333333334\nEpoch 10/19: loss 0.37188136529922483, val_loss 0.38444019254048667, accuracy 0.8679583333333334, val_accuracy 0.8638333333333333\nEpoch 11/19: loss 0.36156421740849815, val_loss 0.37480123901367185, accuracy 0.870375, val_accuracy 0.8670833333333333\nEpoch 12/19: loss 0.3479141906897227, val_loss 0.35920013062159223, accuracy 0.8749791666666666, val_accuracy 0.8698333333333333\nEpoch 13/19: loss 0.340242090066274, val_loss 0.3491000649134318, accuracy 0.8777708333333333, val_accuracy 0.8754166666666666\nEpoch 14/19: loss 0.3300188567241033, val_loss 0.3449784639676412, accuracy 0.8810208333333334, val_accuracy 0.8763333333333333\nEpoch 15/19: loss 0.32112990085283916, val_loss 0.3355961194038391, accuracy 0.8837083333333333, val_accuracy 0.8790833333333333\nEpoch 16/19: loss 0.3148400081396103, val_loss 0.3324051121075948, accuracy 0.8860416666666666, val_accuracy 0.8805833333333334\nEpoch 17/19: loss 0.308021884004275, val_loss 0.34296688143412274, accuracy 0.8877708333333333, val_accuracy 0.879\nEpoch 18/19: loss 0.3058671554327011, val_loss 0.3383064940770467, accuracy 0.8889583333333333, val_accuracy 0.87875\nEpoch 19/19: loss 0.29969928435484566, val_loss 0.31973103046417234, accuracy 0.8912916666666667, val_accuracy 0.8858333333333334\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"<IPython.core.display.HTML object>","text/html":"Waiting for W&B process to finish... <strong style=\"color:green\">(success).</strong>"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"VBox(children=(Label(value='0.001 MB of 0.001 MB uploaded (0.000 MB deduped)\\r'), FloatProgress(value=1.0, max…","application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"6753917bc9274d1ba06974649357751d"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"<IPython.core.display.HTML object>","text/html":"<style>\n    table.wandb td:nth-child(1) { padding: 0 10px; text-align: left ; width: auto;} td:nth-child(2) {text-align: left ; width: 100%}\n    .wandb-row { display: flex; flex-direction: row; flex-wrap: wrap; justify-content: flex-start; width: 100% }\n    .wandb-col { display: flex; flex-direction: column; flex-basis: 100%; flex: 1; padding: 10px; }\n    </style>\n<div class=\"wandb-row\"><div class=\"wandb-col\"><h3>Run history:</h3><br/><table class=\"wandb\"><tr><td>accuracy</td><td>▁▅▆▇▇▇▇▇▇▇▇████████</td></tr><tr><td>loss</td><td>█▄▃▃▂▂▂▂▂▂▂▁▁▁▁▁▁▁▁</td></tr><tr><td>val_accuracy</td><td>▁▄▅▆▆▇▇▇▇▇▇▇███████</td></tr><tr><td>val_loss</td><td>█▆▄▃▃▃▃▂▂▂▂▂▂▁▁▁▁▁▁</td></tr></table><br/></div><div class=\"wandb-col\"><h3>Run summary:</h3><br/><table class=\"wandb\"><tr><td>accuracy</td><td>0.89129</td></tr><tr><td>loss</td><td>0.2997</td></tr><tr><td>val_accuracy</td><td>0.88583</td></tr><tr><td>val_loss</td><td>0.31973</td></tr></table><br/></div></div>"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"<IPython.core.display.HTML object>","text/html":" View run <strong style=\"color:#cdcd00\">best-mlp-torch</strong> at: <a href='https://wandb.ai/nsiete23/torch_mlp/runs/qfy6r37f' target=\"_blank\">https://wandb.ai/nsiete23/torch_mlp/runs/qfy6r37f</a><br/>Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"<IPython.core.display.HTML object>","text/html":"Find logs at: <code>./wandb/run-20230311_142147-qfy6r37f/logs</code>"},"metadata":{}}]},{"cell_type":"markdown","source":"## Plot training and validation accuracy and loss","metadata":{}},{"cell_type":"code","source":"plot_training(\n    history['accuracy'],\n    history['val_accuracy'],\n    history['loss'],\n    history['val_loss']\n)","metadata":{"execution":{"iopub.status.busy":"2023-03-11T14:25:04.262838Z","iopub.execute_input":"2023-03-11T14:25:04.263273Z","iopub.status.idle":"2023-03-11T14:25:04.619942Z","shell.execute_reply.started":"2023-03-11T14:25:04.263230Z","shell.execute_reply":"2023-03-11T14:25:04.618973Z"},"trusted":true},"execution_count":7,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 1200x300 with 2 Axes>","image/png":"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\n"},"metadata":{}}]},{"cell_type":"markdown","source":"## Define class names","metadata":{}},{"cell_type":"code","source":"class_names = [\n    'T-shirt/top',\n    'Trouser',\n    'Pullover',\n    'Dress',\n    'Coat',\n    'Sandal',\n    'Shirt',\n    'Sneaker',\n    'Bag',\n    'Ankle boot'\n]","metadata":{"execution":{"iopub.status.busy":"2023-03-11T14:25:04.621438Z","iopub.execute_input":"2023-03-11T14:25:04.622510Z","iopub.status.idle":"2023-03-11T14:25:04.627932Z","shell.execute_reply.started":"2023-03-11T14:25:04.622471Z","shell.execute_reply":"2023-03-11T14:25:04.626673Z"},"trusted":true},"execution_count":8,"outputs":[]},{"cell_type":"markdown","source":"## Run classification evaluation","metadata":{}},{"cell_type":"code","source":"y_test_all, y_pred_all = evaluate(mlp, test_loader)\n\nreport = classification_report(y_test_all, y_pred_all, target_names=class_names, digits=4)\nprint(report)","metadata":{"execution":{"iopub.status.busy":"2023-03-11T14:25:04.629424Z","iopub.execute_input":"2023-03-11T14:25:04.630078Z","iopub.status.idle":"2023-03-11T14:25:05.650847Z","shell.execute_reply.started":"2023-03-11T14:25:04.630023Z","shell.execute_reply":"2023-03-11T14:25:05.649579Z"},"trusted":true},"execution_count":9,"outputs":[{"name":"stdout","text":"              precision    recall  f1-score   support\n\n T-shirt/top     0.8365    0.8340    0.8353      1000\n     Trouser     0.9817    0.9630    0.9722      1000\n    Pullover     0.8281    0.7420    0.7827      1000\n       Dress     0.8961    0.8540    0.8746      1000\n        Coat     0.7712    0.8190    0.7944      1000\n      Sandal     0.9561    0.9590    0.9576      1000\n       Shirt     0.6483    0.7170    0.6809      1000\n     Sneaker     0.9302    0.9590    0.9444      1000\n         Bag     0.9708    0.9640    0.9674      1000\n  Ankle boot     0.9693    0.9480    0.9585      1000\n\n    accuracy                         0.8759     10000\n   macro avg     0.8788    0.8759    0.8768     10000\nweighted avg     0.8788    0.8759    0.8768     10000\n\n","output_type":"stream"}]},{"cell_type":"markdown","source":"## Visualize confusion matrix","metadata":{}},{"cell_type":"code","source":"show_confusion_matrix(y_test_all, y_pred_all, class_names)","metadata":{"execution":{"iopub.status.busy":"2023-03-11T14:25:05.654378Z","iopub.execute_input":"2023-03-11T14:25:05.654737Z","iopub.status.idle":"2023-03-11T14:25:06.337961Z","shell.execute_reply.started":"2023-03-11T14:25:05.654707Z","shell.execute_reply":"2023-03-11T14:25:06.337013Z"},"trusted":true},"execution_count":10,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 640x480 with 2 Axes>","image/png":"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\n"},"metadata":{}}]}]}