From e5422682a9afa8cdda873685b3bf054de27e0fc2 Mon Sep 17 00:00:00 2001 From: Ben Akka Zakariae <zakariae.ben-akka@etu.ec-lyon.fr> Date: Sat, 25 Nov 2023 19:18:47 +0000 Subject: [PATCH] Replace TD2_Deep_Learning.ipynb --- TD2_Deep_Learning.ipynb | 1241 ++++++++++++++++++++++++++++++++------- 1 file changed, 1042 insertions(+), 199 deletions(-) diff --git a/TD2_Deep_Learning.ipynb b/TD2_Deep_Learning.ipynb index 43202c6..efdbe8e 100644 --- a/TD2_Deep_Learning.ipynb +++ b/TD2_Deep_Learning.ipynb @@ -52,7 +52,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 45, "id": "b1950f0a", "metadata": {}, "outputs": [ @@ -60,34 +60,34 @@ "name": "stdout", "output_type": "stream", "text": [ - "tensor([[-5.8924e-01, 2.1220e+00, 1.9458e+00, -1.3186e+00, -9.7570e-02,\n", - " 7.9640e-01, -1.6654e+00, -1.6353e+00, 9.2206e-06, 8.7219e-01],\n", - " [-8.2591e-01, 1.0598e+00, -1.0381e+00, -1.6884e-01, 1.3910e-01,\n", - " 9.4575e-01, -8.9953e-01, -1.4905e-02, -5.1178e-01, -2.7737e-01],\n", - " [-1.1482e+00, 2.9044e-01, -4.7778e-01, 1.1531e-02, -5.0711e-01,\n", - " 8.6026e-02, 9.1611e-01, -1.1916e+00, -1.5993e+00, 6.8025e-01],\n", - " [ 1.8637e+00, 9.3719e-01, 1.9201e-01, 1.7796e-01, 1.2529e-01,\n", - " -1.5584e+00, -4.8589e-01, -1.0694e-01, 1.1896e+00, 1.5170e+00],\n", - " [-5.4430e-01, 8.3538e-01, 3.2014e-01, 1.4140e+00, -1.9518e-02,\n", - " -9.9845e-01, -2.3777e-01, 7.4762e-01, 1.3153e+00, 7.1071e-01],\n", - " [-7.1822e-01, -1.4507e+00, 7.9309e-01, -1.5367e+00, 5.1508e-01,\n", - " -8.9456e-01, -2.3076e+00, 5.5256e-01, -2.9351e+00, -4.5846e-01],\n", - " [-8.8017e-01, -1.5886e+00, -1.0726e+00, -5.1527e-01, -1.0166e+00,\n", - " 1.1196e+00, 2.2907e+00, 4.7045e-01, 6.5176e-02, -3.8003e-01],\n", - " [-1.6367e+00, -6.1370e-01, -1.3276e-01, 1.2225e+00, -4.1115e-01,\n", - " -4.3862e-01, 5.9012e-02, -9.8958e-01, -2.9922e-01, -1.8661e+00],\n", - " [ 6.4152e-01, 4.0064e-01, -1.0230e+00, 5.1555e-01, -1.7135e+00,\n", - " -4.8497e-01, 1.0353e+00, 5.1067e-01, 1.0871e+00, 1.0828e+00],\n", - " [ 2.7377e-01, -7.0140e-01, 4.5986e-01, -6.5572e-01, -1.4944e-01,\n", - " 3.6845e-01, 7.6481e-01, -5.4602e-01, -3.0768e-01, 1.2102e+00],\n", - " [-1.1149e+00, 6.2832e-01, -7.7844e-01, -8.9476e-02, -2.1547e-01,\n", - " 1.3613e-02, -4.6081e-01, 3.9298e-01, -4.2523e-01, 4.6146e-01],\n", - " [-9.5144e-01, -1.5101e+00, 9.3765e-01, 1.4225e-01, 8.7158e-01,\n", - " 1.0917e+00, -9.4545e-01, 2.6401e-01, 4.8634e-01, -6.9427e-01],\n", - " [ 4.8155e-01, -1.0618e+00, 1.4245e+00, -1.2025e+00, -1.3219e-01,\n", - " 3.3985e-01, 3.0212e-01, -4.0114e-01, -5.5227e-01, 2.1337e+00],\n", - " [ 1.0462e+00, -4.0807e-01, -5.7568e-01, -1.4289e+00, 1.0102e+00,\n", - " -1.0233e+00, -2.2472e+00, 1.0844e+00, -7.9381e-01, 5.0162e-01]])\n", + "tensor([[ 1.3823e-01, 1.4371e+00, 5.4047e-01, 1.2822e+00, 1.3424e+00,\n", + " -1.5928e+00, 4.0903e-01, 2.1866e-01, -7.1381e-01, 1.6739e-01],\n", + " [ 7.0293e-02, -9.5987e-01, -6.2845e-01, 1.5115e+00, -1.1146e+00,\n", + " 2.5957e-01, -4.8736e-01, -2.4212e-01, -3.3799e-01, -3.7087e-02],\n", + " [-8.0512e-01, 7.4754e-01, 1.1382e+00, 6.6314e-02, 6.2260e-01,\n", + " -4.6954e-01, -1.8344e+00, -5.6127e-01, 8.3433e-01, -1.2938e+00],\n", + " [ 2.6398e-01, 1.7975e+00, -1.9659e-01, -3.7564e-01, 1.2111e+00,\n", + " -6.4029e-01, -1.1225e+00, 1.9364e+00, -3.7276e-01, 7.2748e-01],\n", + " [ 1.3801e+00, -3.6240e-01, -1.7176e+00, -4.2919e-01, -3.1818e-01,\n", + " 1.0519e+00, -5.2622e-01, -7.5018e-01, 2.6915e-01, 6.1554e-01],\n", + " [-8.6415e-01, 5.6285e-01, 1.5016e+00, 8.2404e-01, -9.8542e-01,\n", + " 1.2048e-01, 6.9681e-02, 6.7965e-01, -1.3491e-02, -3.3971e-01],\n", + " [ 3.6813e-01, -3.5418e-02, -6.7875e-01, -1.5985e+00, -7.3461e-01,\n", + " -1.1518e-01, 6.5060e-02, -1.3577e+00, -2.2329e+00, -9.8384e-02],\n", + " [-3.9290e-02, -7.5967e-01, -1.4911e+00, -1.6983e+00, -3.9907e-01,\n", + " 7.8204e-01, -1.4037e-01, 8.0492e-01, 4.7376e-01, -5.3342e-01],\n", + " [-3.0993e-01, 7.8360e-02, 1.4900e-01, 4.4902e-01, -7.8801e-01,\n", + " -1.1366e-01, -1.1190e+00, -1.0254e+00, 6.8965e-01, -8.8056e-05],\n", + " [ 6.9366e-01, 1.2367e+00, 7.2280e-01, 2.3477e-01, -1.1897e+00,\n", + " -1.2704e+00, 1.2654e-01, 2.3361e-01, -1.1486e+00, 4.1836e-01],\n", + " [ 4.0964e-01, -8.8076e-01, -6.7998e-01, 8.5963e-01, -3.3105e-02,\n", + " 4.1114e-01, 1.5261e+00, -1.5699e+00, 1.1273e+00, 1.7822e+00],\n", + " [-6.6847e-02, -1.0270e+00, -7.9580e-01, -7.9645e-01, 5.4400e-01,\n", + " -1.5260e+00, -1.3404e+00, 5.8349e-01, 1.7359e-01, 6.8507e-01],\n", + " [-8.3327e-01, 4.7356e-01, -6.9084e-01, -5.2129e-01, -5.8944e-01,\n", + " 7.9934e-01, -1.3757e+00, -6.1393e-01, 6.5033e-01, -1.2716e+00],\n", + " [-7.6035e-01, -1.7380e-01, -1.5043e+00, 1.6806e-01, -7.3543e-01,\n", + " 3.8011e-01, 1.6860e+00, 2.2899e+00, -1.6324e-01, -7.1291e-01]])\n", "AlexNet(\n", " (features): Sequential(\n", " (0): Conv2d(3, 64, kernel_size=(11, 11), stride=(4, 4), padding=(2, 2))\n", @@ -120,6 +120,7 @@ ], "source": [ "import torch\n", + "import torchvision\n", "import numpy as np\n", "from torchvision import datasets, transforms\n", "from torch.utils.data.sampler import SubsetRandomSampler\n", @@ -131,6 +132,10 @@ "import torch.quantization\n", "import json\n", "from PIL import Image\n", + "import copy\n", + "import time\n", + "from torch.optim import lr_scheduler\n", + "\n", "N, D = 14, 10\n", "x = torch.randn(N, D).type(torch.FloatTensor)\n", "print(x)\n", @@ -167,7 +172,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 4, "id": "6e18f2fd", "metadata": {}, "outputs": [ @@ -201,7 +206,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 5, "id": "462666a2", "metadata": {}, "outputs": [ @@ -280,7 +285,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 6, "id": "317bf070", "metadata": {}, "outputs": [ @@ -343,7 +348,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 7, "id": "4b53f229", "metadata": {}, "outputs": [ @@ -351,49 +356,50 @@ "name": "stdout", "output_type": "stream", "text": [ - "Epoch: 0 \tTraining Loss: 43.378945 \tValidation Loss: 37.534217\n", - "Validation loss decreased (inf --> 37.534217). Saving model ...\n", - "Epoch: 1 \tTraining Loss: 34.343955 \tValidation Loss: 32.349840\n", - "Validation loss decreased (37.534217 --> 32.349840). Saving model ...\n", - "Epoch: 2 \tTraining Loss: 30.806036 \tValidation Loss: 29.145299\n", - "Validation loss decreased (32.349840 --> 29.145299). Saving model ...\n", - "Epoch: 3 \tTraining Loss: 28.630288 \tValidation Loss: 28.434799\n", - "Validation loss decreased (29.145299 --> 28.434799). Saving model ...\n", - "Epoch: 4 \tTraining Loss: 26.962422 \tValidation Loss: 27.143118\n", - "Validation loss decreased (28.434799 --> 27.143118). Saving model ...\n", - "Epoch: 5 \tTraining Loss: 25.590344 \tValidation Loss: 26.188523\n", - "Validation loss decreased (27.143118 --> 26.188523). Saving model ...\n", - "Epoch: 6 \tTraining Loss: 24.329372 \tValidation Loss: 25.016885\n", - "Validation loss decreased (26.188523 --> 25.016885). Saving model ...\n", - "Epoch: 7 \tTraining Loss: 23.258511 \tValidation Loss: 23.744379\n", - "Validation loss decreased (25.016885 --> 23.744379). Saving model ...\n", - "Epoch: 8 \tTraining Loss: 22.283808 \tValidation Loss: 23.032502\n", - "Validation loss decreased (23.744379 --> 23.032502). Saving model ...\n", - "Epoch: 9 \tTraining Loss: 21.437031 \tValidation Loss: 22.921947\n", - "Validation loss decreased (23.032502 --> 22.921947). Saving model ...\n", - "Epoch: 10 \tTraining Loss: 20.588990 \tValidation Loss: 22.088936\n", - "Validation loss decreased (22.921947 --> 22.088936). Saving model ...\n", - "Epoch: 11 \tTraining Loss: 19.811905 \tValidation Loss: 22.587189\n", - "Epoch: 12 \tTraining Loss: 19.123620 \tValidation Loss: 21.755673\n", - "Validation loss decreased (22.088936 --> 21.755673). Saving model ...\n", - "Epoch: 13 \tTraining Loss: 18.497675 \tValidation Loss: 21.942630\n", - "Epoch: 14 \tTraining Loss: 17.852816 \tValidation Loss: 21.932077\n", - "Epoch: 15 \tTraining Loss: 17.251354 \tValidation Loss: 21.707757\n", - "Validation loss decreased (21.755673 --> 21.707757). Saving model ...\n", - "Epoch: 16 \tTraining Loss: 16.719265 \tValidation Loss: 22.491421\n", - "Epoch: 17 \tTraining Loss: 16.119002 \tValidation Loss: 22.045470\n", - "Epoch: 18 \tTraining Loss: 15.587754 \tValidation Loss: 21.740500\n", - "Epoch: 19 \tTraining Loss: 15.052405 \tValidation Loss: 22.119651\n", - "Epoch: 20 \tTraining Loss: 14.572571 \tValidation Loss: 22.519353\n", - "Epoch: 21 \tTraining Loss: 14.125367 \tValidation Loss: 24.025316\n", - "Epoch: 22 \tTraining Loss: 13.533694 \tValidation Loss: 23.514559\n", - "Epoch: 23 \tTraining Loss: 13.080140 \tValidation Loss: 24.261488\n", - "Epoch: 24 \tTraining Loss: 12.658047 \tValidation Loss: 24.357848\n", - "Epoch: 25 \tTraining Loss: 12.231944 \tValidation Loss: 24.462697\n", - "Epoch: 26 \tTraining Loss: 11.806727 \tValidation Loss: 25.935711\n", - "Epoch: 27 \tTraining Loss: 11.362395 \tValidation Loss: 26.394804\n", - "Epoch: 28 \tTraining Loss: 10.929406 \tValidation Loss: 26.953419\n", - "Epoch: 29 \tTraining Loss: 10.504231 \tValidation Loss: 26.891173\n" + "Epoch: 0 \tTraining Loss: 42.706410 \tValidation Loss: 37.549365\n", + "Validation loss decreased (inf --> 37.549365). Saving model ...\n", + "Epoch: 1 \tTraining Loss: 34.682203 \tValidation Loss: 32.756616\n", + "Validation loss decreased (37.549365 --> 32.756616). Saving model ...\n", + "Epoch: 2 \tTraining Loss: 30.741905 \tValidation Loss: 29.590071\n", + "Validation loss decreased (32.756616 --> 29.590071). Saving model ...\n", + "Epoch: 3 \tTraining Loss: 28.491642 \tValidation Loss: 27.348559\n", + "Validation loss decreased (29.590071 --> 27.348559). Saving model ...\n", + "Epoch: 4 \tTraining Loss: 26.764905 \tValidation Loss: 25.580812\n", + "Validation loss decreased (27.348559 --> 25.580812). Saving model ...\n", + "Epoch: 5 \tTraining Loss: 25.264787 \tValidation Loss: 24.726740\n", + "Validation loss decreased (25.580812 --> 24.726740). Saving model ...\n", + "Epoch: 6 \tTraining Loss: 23.990562 \tValidation Loss: 24.224369\n", + "Validation loss decreased (24.726740 --> 24.224369). Saving model ...\n", + "Epoch: 7 \tTraining Loss: 22.904920 \tValidation Loss: 23.848258\n", + "Validation loss decreased (24.224369 --> 23.848258). Saving model ...\n", + "Epoch: 8 \tTraining Loss: 21.983295 \tValidation Loss: 23.657920\n", + "Validation loss decreased (23.848258 --> 23.657920). Saving model ...\n", + "Epoch: 9 \tTraining Loss: 21.100526 \tValidation Loss: 22.080895\n", + "Validation loss decreased (23.657920 --> 22.080895). Saving model ...\n", + "Epoch: 10 \tTraining Loss: 20.297763 \tValidation Loss: 22.566959\n", + "Epoch: 11 \tTraining Loss: 19.580086 \tValidation Loss: 22.426025\n", + "Epoch: 12 \tTraining Loss: 18.895442 \tValidation Loss: 21.998238\n", + "Validation loss decreased (22.080895 --> 21.998238). Saving model ...\n", + "Epoch: 13 \tTraining Loss: 18.266996 \tValidation Loss: 21.645298\n", + "Validation loss decreased (21.998238 --> 21.645298). Saving model ...\n", + "Epoch: 14 \tTraining Loss: 17.614121 \tValidation Loss: 21.425315\n", + "Validation loss decreased (21.645298 --> 21.425315). Saving model ...\n", + "Epoch: 15 \tTraining Loss: 17.013795 \tValidation Loss: 21.336770\n", + "Validation loss decreased (21.425315 --> 21.336770). Saving model ...\n", + "Epoch: 16 \tTraining Loss: 16.433492 \tValidation Loss: 21.738642\n", + "Epoch: 17 \tTraining Loss: 15.871810 \tValidation Loss: 22.068780\n", + "Epoch: 18 \tTraining Loss: 15.372662 \tValidation Loss: 22.312414\n", + "Epoch: 19 \tTraining Loss: 14.806503 \tValidation Loss: 22.614040\n", + "Epoch: 20 \tTraining Loss: 14.257983 \tValidation Loss: 22.820819\n", + "Epoch: 21 \tTraining Loss: 13.838574 \tValidation Loss: 22.394366\n", + "Epoch: 22 \tTraining Loss: 13.313069 \tValidation Loss: 22.948898\n", + "Epoch: 23 \tTraining Loss: 12.879593 \tValidation Loss: 23.263349\n", + "Epoch: 24 \tTraining Loss: 12.414456 \tValidation Loss: 23.998298\n", + "Epoch: 25 \tTraining Loss: 12.041669 \tValidation Loss: 25.065187\n", + "Epoch: 26 \tTraining Loss: 11.523059 \tValidation Loss: 25.274171\n", + "Epoch: 27 \tTraining Loss: 11.059043 \tValidation Loss: 25.448349\n", + "Epoch: 28 \tTraining Loss: 10.749217 \tValidation Loss: 25.841604\n", + "Epoch: 29 \tTraining Loss: 10.308294 \tValidation Loss: 26.855672\n" ] } ], @@ -479,13 +485,13 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 8, "id": "d39df818", "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", "text/plain": [ "<Figure size 640x480 with 1 Axes>" ] @@ -517,27 +523,27 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 26, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Test Loss: 21.662193\n", + "Test Loss: 21.184199\n", "\n", - "Test Accuracy of airplane: 67% (674/1000)\n", - "Test Accuracy of automobile: 75% (750/1000)\n", - "Test Accuracy of bird: 52% (529/1000)\n", - "Test Accuracy of cat: 47% (470/1000)\n", - "Test Accuracy of deer: 60% (600/1000)\n", - "Test Accuracy of dog: 49% (490/1000)\n", - "Test Accuracy of frog: 68% (683/1000)\n", - "Test Accuracy of horse: 66% (660/1000)\n", - "Test Accuracy of ship: 68% (684/1000)\n", - "Test Accuracy of truck: 74% (747/1000)\n", + "Test Accuracy of airplane: 65% (651/1000)\n", + "Test Accuracy of automobile: 75% (754/1000)\n", + "Test Accuracy of bird: 55% (552/1000)\n", + "Test Accuracy of cat: 39% (394/1000)\n", + "Test Accuracy of deer: 56% (568/1000)\n", + "Test Accuracy of dog: 56% (562/1000)\n", + "Test Accuracy of frog: 69% (695/1000)\n", + "Test Accuracy of horse: 66% (661/1000)\n", + "Test Accuracy of ship: 80% (805/1000)\n", + "Test Accuracy of truck: 71% (718/1000)\n", "\n", - "Test Accuracy of model 1 (Overall): 62% (6287/10000)\n" + "Test Accuracy of model 1 (Overall): 63.600000% (6360.000000/10000.000000)\n" ] } ], @@ -597,7 +603,7 @@ " print(\"Test Accuracy of %5s: N/A (no training examples)\" % (classes[i]))\n", "\n", "print(\n", - " \"\\nTest Accuracy of model 1 (Overall): %2d%% (%2d/%2d)\"\n", + " \"\\nTest Accuracy of model 1 (Overall): %2f%% (%2f/%2f)\"\n", " % (\n", " 100.0 * np.sum(class_correct) / np.sum(class_total),\n", " np.sum(class_correct),\n", @@ -615,7 +621,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 10, "metadata": {}, "outputs": [ { @@ -685,55 +691,54 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 11, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Epoch: 0 \tTraining Loss: 44.557753 \tValidation Loss: 39.817679\n", - "Validation loss decreased (inf --> 39.817679). Saving model ...\n", - "Epoch: 1 \tTraining Loss: 36.209753 \tValidation Loss: 33.034412\n", - "Validation loss decreased (39.817679 --> 33.034412). Saving model ...\n", - "Epoch: 2 \tTraining Loss: 31.099305 \tValidation Loss: 29.910456\n", - "Validation loss decreased (33.034412 --> 29.910456). Saving model ...\n", - "Epoch: 3 \tTraining Loss: 28.188536 \tValidation Loss: 26.678592\n", - "Validation loss decreased (29.910456 --> 26.678592). Saving model ...\n", - "Epoch: 4 \tTraining Loss: 25.639184 \tValidation Loss: 24.843114\n", - "Validation loss decreased (26.678592 --> 24.843114). Saving model ...\n", - "Epoch: 5 \tTraining Loss: 23.317273 \tValidation Loss: 22.223353\n", - "Validation loss decreased (24.843114 --> 22.223353). Saving model ...\n", - "Epoch: 6 \tTraining Loss: 21.301518 \tValidation Loss: 20.623540\n", - "Validation loss decreased (22.223353 --> 20.623540). Saving model ...\n", - "Epoch: 7 \tTraining Loss: 19.542947 \tValidation Loss: 20.162958\n", - "Validation loss decreased (20.623540 --> 20.162958). Saving model ...\n", - "Epoch: 8 \tTraining Loss: 17.999442 \tValidation Loss: 18.675086\n", - "Validation loss decreased (20.162958 --> 18.675086). Saving model ...\n", - "Epoch: 9 \tTraining Loss: 16.535020 \tValidation Loss: 18.128589\n", - "Validation loss decreased (18.675086 --> 18.128589). Saving model ...\n", - "Epoch: 10 \tTraining Loss: 15.174483 \tValidation Loss: 17.162074\n", - "Validation loss decreased (18.128589 --> 17.162074). Saving model ...\n", - "Epoch: 11 \tTraining Loss: 13.864482 \tValidation Loss: 17.209080\n", - "Epoch: 12 \tTraining Loss: 12.617755 \tValidation Loss: 17.270458\n", - "Epoch: 13 \tTraining Loss: 11.389589 \tValidation Loss: 17.112058\n", - "Validation loss decreased (17.162074 --> 17.112058). Saving model ...\n", - "Epoch: 14 \tTraining Loss: 10.064839 \tValidation Loss: 17.678218\n", - "Epoch: 15 \tTraining Loss: 8.780338 \tValidation Loss: 17.519580\n", - "Epoch: 16 \tTraining Loss: 7.626408 \tValidation Loss: 18.112166\n", - "Epoch: 17 \tTraining Loss: 6.316284 \tValidation Loss: 19.413389\n", - "Epoch: 18 \tTraining Loss: 5.235316 \tValidation Loss: 20.455955\n", - "Epoch: 19 \tTraining Loss: 4.317387 \tValidation Loss: 22.437315\n", - "Epoch: 20 \tTraining Loss: 3.492141 \tValidation Loss: 24.581517\n", - "Epoch: 21 \tTraining Loss: 2.814595 \tValidation Loss: 23.857926\n", - "Epoch: 22 \tTraining Loss: 2.292130 \tValidation Loss: 27.540117\n", - "Epoch: 23 \tTraining Loss: 1.958200 \tValidation Loss: 29.974592\n", - "Epoch: 24 \tTraining Loss: 1.703906 \tValidation Loss: 29.493216\n", - "Epoch: 25 \tTraining Loss: 1.515222 \tValidation Loss: 31.318798\n", - "Epoch: 26 \tTraining Loss: 1.304394 \tValidation Loss: 31.898265\n", - "Epoch: 27 \tTraining Loss: 1.135672 \tValidation Loss: 33.532167\n", - "Epoch: 28 \tTraining Loss: 1.063874 \tValidation Loss: 33.580899\n", - "Epoch: 29 \tTraining Loss: 0.910804 \tValidation Loss: 35.744193\n" + "Epoch: 0 \tTraining Loss: 45.198202 \tValidation Loss: 40.966207\n", + "Validation loss decreased (inf --> 40.966207). Saving model ...\n", + "Epoch: 1 \tTraining Loss: 37.330688 \tValidation Loss: 33.521531\n", + "Validation loss decreased (40.966207 --> 33.521531). Saving model ...\n", + "Epoch: 2 \tTraining Loss: 31.562392 \tValidation Loss: 29.229370\n", + "Validation loss decreased (33.521531 --> 29.229370). Saving model ...\n", + "Epoch: 3 \tTraining Loss: 28.058459 \tValidation Loss: 26.177679\n", + "Validation loss decreased (29.229370 --> 26.177679). Saving model ...\n", + "Epoch: 4 \tTraining Loss: 25.456967 \tValidation Loss: 23.716301\n", + "Validation loss decreased (26.177679 --> 23.716301). Saving model ...\n", + "Epoch: 5 \tTraining Loss: 23.113733 \tValidation Loss: 22.240193\n", + "Validation loss decreased (23.716301 --> 22.240193). Saving model ...\n", + "Epoch: 6 \tTraining Loss: 21.204408 \tValidation Loss: 20.603154\n", + "Validation loss decreased (22.240193 --> 20.603154). Saving model ...\n", + "Epoch: 7 \tTraining Loss: 19.409736 \tValidation Loss: 19.268198\n", + "Validation loss decreased (20.603154 --> 19.268198). Saving model ...\n", + "Epoch: 8 \tTraining Loss: 17.837116 \tValidation Loss: 18.357212\n", + "Validation loss decreased (19.268198 --> 18.357212). Saving model ...\n", + "Epoch: 9 \tTraining Loss: 16.416749 \tValidation Loss: 18.906651\n", + "Epoch: 10 \tTraining Loss: 15.053826 \tValidation Loss: 17.337641\n", + "Validation loss decreased (18.357212 --> 17.337641). Saving model ...\n", + "Epoch: 11 \tTraining Loss: 13.805687 \tValidation Loss: 16.633078\n", + "Validation loss decreased (17.337641 --> 16.633078). Saving model ...\n", + "Epoch: 12 \tTraining Loss: 12.541472 \tValidation Loss: 17.184920\n", + "Epoch: 13 \tTraining Loss: 11.335604 \tValidation Loss: 17.543164\n", + "Epoch: 14 \tTraining Loss: 10.047115 \tValidation Loss: 17.556785\n", + "Epoch: 15 \tTraining Loss: 8.794780 \tValidation Loss: 17.938292\n", + "Epoch: 16 \tTraining Loss: 7.607265 \tValidation Loss: 19.072760\n", + "Epoch: 17 \tTraining Loss: 6.449549 \tValidation Loss: 19.529105\n", + "Epoch: 18 \tTraining Loss: 5.425620 \tValidation Loss: 21.515781\n", + "Epoch: 19 \tTraining Loss: 4.283669 \tValidation Loss: 22.043078\n", + "Epoch: 20 \tTraining Loss: 3.533014 \tValidation Loss: 24.846188\n", + "Epoch: 21 \tTraining Loss: 2.861788 \tValidation Loss: 25.897939\n", + "Epoch: 22 \tTraining Loss: 2.286396 \tValidation Loss: 27.009543\n", + "Epoch: 23 \tTraining Loss: 2.219529 \tValidation Loss: 29.655110\n", + "Epoch: 24 \tTraining Loss: 1.721309 \tValidation Loss: 30.484672\n", + "Epoch: 25 \tTraining Loss: 1.391777 \tValidation Loss: 32.229886\n", + "Epoch: 26 \tTraining Loss: 1.279259 \tValidation Loss: 33.819620\n", + "Epoch: 27 \tTraining Loss: 1.252377 \tValidation Loss: 32.575949\n", + "Epoch: 28 \tTraining Loss: 1.323867 \tValidation Loss: 34.618063\n", + "Epoch: 29 \tTraining Loss: 1.130607 \tValidation Loss: 35.113301\n" ] } ], @@ -815,12 +820,12 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 12, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", "text/plain": [ "<Figure size 640x480 with 1 Axes>" ] @@ -852,25 +857,25 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 27, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Test Accuracy of airplane: 71% (711/1000)\n", - "Test Accuracy of automobile: 74% (745/1000)\n", - "Test Accuracy of bird: 57% (578/1000)\n", - "Test Accuracy of cat: 65% (656/1000)\n", - "Test Accuracy of deer: 57% (578/1000)\n", - "Test Accuracy of dog: 57% (574/1000)\n", - "Test Accuracy of frog: 79% (793/1000)\n", - "Test Accuracy of horse: 74% (742/1000)\n", - "Test Accuracy of ship: 84% (846/1000)\n", - "Test Accuracy of truck: 81% (819/1000)\n", + "Test Accuracy of airplane: 74% (743/1000)\n", + "Test Accuracy of automobile: 83% (839/1000)\n", + "Test Accuracy of bird: 62% (624/1000)\n", + "Test Accuracy of cat: 45% (453/1000)\n", + "Test Accuracy of deer: 58% (586/1000)\n", + "Test Accuracy of dog: 70% (704/1000)\n", + "Test Accuracy of frog: 76% (768/1000)\n", + "Test Accuracy of horse: 71% (719/1000)\n", + "Test Accuracy of ship: 79% (798/1000)\n", + "Test Accuracy of truck: 79% (795/1000)\n", "\n", - "Test Accuracy (Overall): 70% (7042/10000)\n" + "Test Accuracy (Overall): 70.290000% (7029.000000/10000.000000)\n" ] } ], @@ -922,7 +927,7 @@ " print(\"Test Accuracy of %5s: N/A (no training examples)\" % (classes[i]))\n", "\n", "print(\n", - " \"\\nTest Accuracy (Overall): %2d%% (%2d/%2d)\"\n", + " \"\\nTest Accuracy (Overall): %2f%% (%2f/%2f)\"\n", " % (\n", " 100.0 * np.sum(class_correct2) / np.sum(class_total2),\n", " np.sum(class_correct2),\n", @@ -967,7 +972,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 14, "metadata": {}, "outputs": [ { @@ -983,7 +988,7 @@ "251278" ] }, - "execution_count": 15, + "execution_count": 14, "metadata": {}, "output_type": "execute_result" } @@ -1012,7 +1017,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 15, "metadata": {}, "outputs": [ { @@ -1028,7 +1033,7 @@ "76522" ] }, - "execution_count": 16, + "execution_count": 15, "metadata": {}, "output_type": "execute_result" } @@ -1050,7 +1055,7 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 16, "metadata": {}, "outputs": [ { @@ -1067,7 +1072,7 @@ "659806" ] }, - "execution_count": 25, + "execution_count": 16, "metadata": {}, "output_type": "execute_result" } @@ -1087,25 +1092,25 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 25, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Test Accuracy of airplane: 67% (679/1000)\n", - "Test Accuracy of automobile: 75% (751/1000)\n", - "Test Accuracy of bird: 53% (532/1000)\n", - "Test Accuracy of cat: 46% (464/1000)\n", - "Test Accuracy of deer: 59% (598/1000)\n", - "Test Accuracy of dog: 49% (491/1000)\n", - "Test Accuracy of frog: 68% (682/1000)\n", - "Test Accuracy of horse: 65% (658/1000)\n", - "Test Accuracy of ship: 67% (679/1000)\n", - "Test Accuracy of truck: 74% (746/1000)\n", + "Test Accuracy of airplane: 64% (647/1000)\n", + "Test Accuracy of automobile: 75% (755/1000)\n", + "Test Accuracy of bird: 55% (551/1000)\n", + "Test Accuracy of cat: 38% (384/1000)\n", + "Test Accuracy of deer: 58% (581/1000)\n", + "Test Accuracy of dog: 55% (558/1000)\n", + "Test Accuracy of frog: 69% (696/1000)\n", + "Test Accuracy of horse: 66% (662/1000)\n", + "Test Accuracy of ship: 80% (806/1000)\n", + "Test Accuracy of truck: 72% (721/1000)\n", "\n", - "Test Accuracy of quantized model 1 (Overall): 62% (6280/10000)\n" + "Test Accuracy of quantized model 1 (Overall): 63.610000% (6361.000000/10000.000000)\n" ] } ], @@ -1158,7 +1163,7 @@ " print(\"Test Accuracy of quantized model 1 %5s: N/A (no training examples)\" % (classes[i]))\n", "\n", "print(\n", - " \"\\nTest Accuracy of quantized model 1 (Overall): %2d%% (%2d/%2d)\"\n", + " \"\\nTest Accuracy of quantized model 1 (Overall): %2f%% (%2f/%2f)\"\n", " % (\n", " 100.0 * np.sum(class_correct) / np.sum(class_total),\n", " np.sum(class_correct),\n", @@ -1176,25 +1181,25 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 28, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Test Accuracy of airplane: 70% (703/1000)\n", - "Test Accuracy of automobile: 74% (743/1000)\n", - "Test Accuracy of bird: 58% (582/1000)\n", - "Test Accuracy of cat: 65% (652/1000)\n", - "Test Accuracy of deer: 57% (579/1000)\n", - "Test Accuracy of dog: 57% (579/1000)\n", - "Test Accuracy of frog: 79% (795/1000)\n", - "Test Accuracy of horse: 73% (736/1000)\n", - "Test Accuracy of ship: 84% (845/1000)\n", - "Test Accuracy of truck: 81% (819/1000)\n", + "Test Accuracy of airplane: 74% (746/1000)\n", + "Test Accuracy of automobile: 83% (839/1000)\n", + "Test Accuracy of bird: 61% (617/1000)\n", + "Test Accuracy of cat: 45% (455/1000)\n", + "Test Accuracy of deer: 58% (588/1000)\n", + "Test Accuracy of dog: 70% (704/1000)\n", + "Test Accuracy of frog: 76% (768/1000)\n", + "Test Accuracy of horse: 72% (720/1000)\n", + "Test Accuracy of ship: 79% (791/1000)\n", + "Test Accuracy of truck: 79% (791/1000)\n", "\n", - "Test Accuracy of quantized model 2 (Overall): 70% (7033/10000)\n" + "Test Accuracy of quantized model 2 (Overall): 70.190000% (7019.000000/10000.000000)\n" ] } ], @@ -1247,7 +1252,7 @@ " print(\"Test Accuracy of quantized model 2 %5s: N/A (no training examples)\" % (classes[i]))\n", "\n", "print(\n", - " \"\\nTest Accuracy of quantized model 2 (Overall): %2d%% (%2d/%2d)\"\n", + " \"\\nTest Accuracy of quantized model 2 (Overall): %2f%% (%2f/%2f)\"\n", " % (\n", " 100.0 * np.sum(class_correct) / np.sum(class_total),\n", " np.sum(class_correct),\n", @@ -1265,12 +1270,12 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 32, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", + "image/png": 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", "text/plain": [ "<Figure size 640x480 with 1 Axes>" ] @@ -1282,11 +1287,12 @@ "source": [ "fig_4, ax_4 = plt.subplots()\n", "w = 0.4\n", - "x = [\"airplane\", \"automobile\", \"bird\", \"car\", \"deer\", \"dog\", \"frog\", \"horse\", \"ship\", \"truck\"]\n", + "x = [\"airpl.\", \"auto.\", \"bird\", \"car\", \"deer\", \"dog\", \"frog\", \"horse\", \"ship\", \"truck\"]\n", "bar1 = np.arange(len(x))\n", "bar2 = [i+w for i in bar1]\n", "ax_4.bar(bar1,accuracy_per_class_m1,w,label=\"Original model\")\n", "ax_4.bar(bar2,accuracy_per_class_q1,w,label=\"quantized model\")\n", + "ax_4.set_xticks(bar1+w/2,x)\n", "ax_4.legend()\n", "plt.xlabel(\"Class\")\n", "plt.ylabel(\"Accuracy\")\n", @@ -1302,12 +1308,12 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 36, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", + "image/png": 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", "text/plain": [ "<Figure size 640x480 with 1 Axes>" ] @@ -1319,11 +1325,12 @@ "source": [ "fig_5, ax_5 = plt.subplots()\n", "w = 0.4\n", - "x = [\"airplane\", \"automobile\", \"bird\", \"car\", \"deer\", \"dog\", \"frog\", \"horse\", \"ship\", \"truck\"]\n", + "x = [\"airpl.\", \"autom.\", \"bird\", \"car\", \"deer\", \"dog\", \"frog\", \"horse\", \"ship\", \"truck\"]\n", "bar1 = np.arange(len(x))\n", "bar2 = [i+w for i in bar1]\n", "ax_5.bar(bar1,accuracy_per_class_m2,w,label=\"Original model\")\n", "ax_5.bar(bar2,accuracy_per_class_q2,w,label=\"Quantized_model\")\n", + "ax_5.set_xticks(bar1+w/2,x)\n", "ax_5.legend()\n", "plt.xlabel(\"Class\")\n", "plt.ylabel(\"Accuracy\")\n", @@ -1346,14 +1353,218 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 40, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\LENOVO\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\torchvision\\models\\_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.\n", + " warnings.warn(\n", + "C:\\Users\\LENOVO\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\torchvision\\models\\_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=ResNet50_Weights.IMAGENET1K_V1`. You can also use `weights=ResNet50_Weights.DEFAULT` to get the most up-to-date weights.\n", + " warnings.warn(msg)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "ResNet(\n", + " (conv1): Conv2d(3, 64, kernel_size=(7, 7), stride=(2, 2), padding=(3, 3), bias=False)\n", + " (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=True)\n", + " (maxpool): MaxPool2d(kernel_size=3, stride=2, padding=1, dilation=1, ceil_mode=False)\n", + " (layer1): Sequential(\n", + " (0): Bottleneck(\n", + " (conv1): Conv2d(64, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " (bn2): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv3): Conv2d(64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn3): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=True)\n", + " (downsample): Sequential(\n", + " (0): Conv2d(64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " )\n", + " )\n", + " (1): Bottleneck(\n", + " (conv1): Conv2d(256, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " (bn2): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv3): Conv2d(64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn3): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=True)\n", + " )\n", + " (2): Bottleneck(\n", + " (conv1): Conv2d(256, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " (bn2): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv3): Conv2d(64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn3): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=True)\n", + " )\n", + " )\n", + " (layer2): Sequential(\n", + " (0): Bottleneck(\n", + " (conv1): Conv2d(256, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)\n", + " (bn2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv3): Conv2d(128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn3): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=True)\n", + " (downsample): Sequential(\n", + " (0): Conv2d(256, 512, kernel_size=(1, 1), stride=(2, 2), bias=False)\n", + " (1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " )\n", + " )\n", + " (1): Bottleneck(\n", + " (conv1): Conv2d(512, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " (bn2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv3): Conv2d(128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn3): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=True)\n", + " )\n", + " (2): Bottleneck(\n", + " (conv1): Conv2d(512, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " (bn2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv3): Conv2d(128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn3): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=True)\n", + " )\n", + " (3): Bottleneck(\n", + " (conv1): Conv2d(512, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " (bn2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv3): Conv2d(128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn3): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=True)\n", + " )\n", + " )\n", + " (layer3): Sequential(\n", + " (0): Bottleneck(\n", + " (conv1): Conv2d(512, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)\n", + " (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn3): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=True)\n", + " (downsample): Sequential(\n", + " (0): Conv2d(512, 1024, kernel_size=(1, 1), stride=(2, 2), bias=False)\n", + " (1): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " )\n", + " )\n", + " (1): Bottleneck(\n", + " (conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn3): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=True)\n", + " )\n", + " (2): Bottleneck(\n", + " (conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn3): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=True)\n", + " )\n", + " (3): Bottleneck(\n", + " (conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn3): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=True)\n", + " )\n", + " (4): Bottleneck(\n", + " (conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn3): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=True)\n", + " )\n", + " (5): Bottleneck(\n", + " (conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn3): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=True)\n", + " )\n", + " )\n", + " (layer4): Sequential(\n", + " (0): Bottleneck(\n", + " (conv1): Conv2d(1024, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)\n", + " (bn2): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv3): Conv2d(512, 2048, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn3): BatchNorm2d(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=True)\n", + " (downsample): Sequential(\n", + " (0): Conv2d(1024, 2048, kernel_size=(1, 1), stride=(2, 2), bias=False)\n", + " (1): BatchNorm2d(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " )\n", + " )\n", + " (1): Bottleneck(\n", + " (conv1): Conv2d(2048, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " (bn2): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv3): Conv2d(512, 2048, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn3): BatchNorm2d(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=True)\n", + " )\n", + " (2): Bottleneck(\n", + " (conv1): Conv2d(2048, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " (bn2): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv3): Conv2d(512, 2048, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn3): BatchNorm2d(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=True)\n", + " )\n", + " )\n", + " (avgpool): AdaptiveAvgPool2d(output_size=(1, 1))\n", + " (fc): Linear(in_features=2048, out_features=1000, bias=True)\n", + ")\n", + "Predicted class is: German Shepherd Dog\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "<Figure size 640x480 with 1 Axes>" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "\n", "\n", "# Choose an image to pass through the model\n", - "test_image = \"dog.png\"\n", + "test_image = \"dog2.JPEG\"\n", "\n", "# Configure matplotlib for pretty inline plots\n", "#%matplotlib inline\n", @@ -1403,9 +1614,27 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 22, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "model: fp32 \t Size (KB): 102523.238\n" + ] + }, + { + "data": { + "text/plain": [ + "102523238" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "print_size_of_model(model_3, \"fp32\")" ] @@ -1419,9 +1648,27 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 23, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "model: int8 \t Size (KB): 96379.996\n" + ] + }, + { + "data": { + "text/plain": [ + "96379996" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "quantized_model_3 = torch.quantization.quantize_dynamic(model_3, dtype=torch.qint8)\n", "print_size_of_model(quantized_model_3, \"int8\")" @@ -1436,15 +1683,209 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 41, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "ResNet(\n", + " (conv1): Conv2d(3, 64, kernel_size=(7, 7), stride=(2, 2), padding=(3, 3), bias=False)\n", + " (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=True)\n", + " (maxpool): MaxPool2d(kernel_size=3, stride=2, padding=1, dilation=1, ceil_mode=False)\n", + " (layer1): Sequential(\n", + " (0): Bottleneck(\n", + " (conv1): Conv2d(64, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " (bn2): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv3): Conv2d(64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn3): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=True)\n", + " (downsample): Sequential(\n", + " (0): Conv2d(64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " )\n", + " )\n", + " (1): Bottleneck(\n", + " (conv1): Conv2d(256, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " (bn2): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv3): Conv2d(64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn3): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=True)\n", + " )\n", + " (2): Bottleneck(\n", + " (conv1): Conv2d(256, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " (bn2): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv3): Conv2d(64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn3): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=True)\n", + " )\n", + " )\n", + " (layer2): Sequential(\n", + " (0): Bottleneck(\n", + " (conv1): Conv2d(256, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)\n", + " (bn2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv3): Conv2d(128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn3): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=True)\n", + " (downsample): Sequential(\n", + " (0): Conv2d(256, 512, kernel_size=(1, 1), stride=(2, 2), bias=False)\n", + " (1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " )\n", + " )\n", + " (1): Bottleneck(\n", + " (conv1): Conv2d(512, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " (bn2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv3): Conv2d(128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn3): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=True)\n", + " )\n", + " (2): Bottleneck(\n", + " (conv1): Conv2d(512, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " (bn2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv3): Conv2d(128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn3): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=True)\n", + " )\n", + " (3): Bottleneck(\n", + " (conv1): Conv2d(512, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " (bn2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv3): Conv2d(128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn3): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=True)\n", + " )\n", + " )\n", + " (layer3): Sequential(\n", + " (0): Bottleneck(\n", + " (conv1): Conv2d(512, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)\n", + " (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn3): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=True)\n", + " (downsample): Sequential(\n", + " (0): Conv2d(512, 1024, kernel_size=(1, 1), stride=(2, 2), bias=False)\n", + " (1): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " )\n", + " )\n", + " (1): Bottleneck(\n", + " (conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn3): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=True)\n", + " )\n", + " (2): Bottleneck(\n", + " (conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn3): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=True)\n", + " )\n", + " (3): Bottleneck(\n", + " (conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn3): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=True)\n", + " )\n", + " (4): Bottleneck(\n", + " (conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn3): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=True)\n", + " )\n", + " (5): Bottleneck(\n", + " (conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn3): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=True)\n", + " )\n", + " )\n", + " (layer4): Sequential(\n", + " (0): Bottleneck(\n", + " (conv1): Conv2d(1024, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)\n", + " (bn2): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv3): Conv2d(512, 2048, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn3): BatchNorm2d(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=True)\n", + " (downsample): Sequential(\n", + " (0): Conv2d(1024, 2048, kernel_size=(1, 1), stride=(2, 2), bias=False)\n", + " (1): BatchNorm2d(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " )\n", + " )\n", + " (1): Bottleneck(\n", + " (conv1): Conv2d(2048, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " (bn2): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv3): Conv2d(512, 2048, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn3): BatchNorm2d(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=True)\n", + " )\n", + " (2): Bottleneck(\n", + " (conv1): Conv2d(2048, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " (bn2): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (conv3): Conv2d(512, 2048, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (bn3): BatchNorm2d(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=True)\n", + " )\n", + " )\n", + " (avgpool): AdaptiveAvgPool2d(output_size=(1, 1))\n", + " (fc): Linear(in_features=2048, out_features=1000, bias=True)\n", + ")\n", + "Predicted class is: German Shepherd Dog\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "<Figure size 640x480 with 1 Axes>" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "import json\n", "from PIL import Image\n", "\n", "# Choose an image to pass through the model\n", - "test_image = \"dog.png\"\n", + "test_image = \"dog2.JPEG\"\n", "\n", "# Configure matplotlib for pretty inline plots\n", "#%matplotlib inline\n", @@ -1491,6 +1932,408 @@ "source": [ " Experiments:Study the code and the results obtained. Possibly add other images downloaded from the internet.What is the size of the model? Quantize it and then check if the model is still able to correctly classify the other images.Experiment with other pre-trained CNN models." ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Exercise 4: Transfer Learning" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "For this work, we will use a pre-trained model (ResNet18) as a descriptor extractor and will refine the classification by training only the last fully connected layer of the network. Thus, the output layer of the pre-trained network will be replaced by a layer adapted to the new classes to be recognized which will be in our case ants and bees.\n", + "Download and unzip in your working directory the dataset available at the address :https://download.pytorch.org/tutorial/hymenoptera_data.zipExecute the following code in order to display some images of the dataset." + ] + }, + { + "cell_type": "code", + "execution_count": 101, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "<Figure size 640x480 with 1 Axes>" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "\n", + "\n", + "# Data augmentation and normalization for training\n", + "# Just normalization for validation\n", + "data_transforms = {\n", + " \"train\": transforms.Compose(\n", + " [\n", + " transforms.RandomResizedCrop(\n", + " 224\n", + " ), # ImageNet models were trained on 224x224 images\n", + " transforms.RandomHorizontalFlip(), # flip horizontally 50% of the time - increases train set variability\n", + " transforms.ToTensor(), # convert it to a PyTorch tensor\n", + " transforms.Normalize(\n", + " [0.485, 0.456, 0.406], [0.229, 0.224, 0.225]\n", + " ), # ImageNet models expect this norm\n", + " ]\n", + " ),\n", + " \"val\": transforms.Compose(\n", + " [\n", + " transforms.Resize(256),\n", + " transforms.CenterCrop(224),\n", + " transforms.ToTensor(),\n", + " transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225]),\n", + " ]\n", + " \n", + " ),\n", + " \"test\": transforms.Compose(\n", + " [\n", + " transforms.Resize(256),\n", + " transforms.CenterCrop(224),\n", + " transforms.ToTensor(),\n", + " transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225]),\n", + " ]\n", + " \n", + " ),\n", + "}\n", + "\n", + "data_dir = \"hymenoptera_data\"\n", + "# Create train and validation datasets and loaders\n", + "image_datasets = {\n", + " x: datasets.ImageFolder(os.path.join(data_dir, x), data_transforms[x])\n", + " for x in [\"train\", \"val\", \"test\"]\n", + "}\n", + "dataloaders = {\n", + " x: torch.utils.data.DataLoader(\n", + " image_datasets[x], batch_size=4, shuffle=True, num_workers=0\n", + " )\n", + " for x in [\"train\", \"val\", \"test\"]\n", + "}\n", + "dataset_sizes = {x: len(image_datasets[x]) for x in [\"train\", \"val\", \"test\"]}\n", + "class_names = image_datasets[\"train\"].classes\n", + "device = torch.device(\"cuda:0\" if torch.cuda.is_available() else \"cpu\")\n", + "\n", + "# Helper function for displaying images\n", + "def imshow(inp, title=None):\n", + " \"\"\"Imshow for Tensor.\"\"\"\n", + " inp = inp.numpy().transpose((1, 2, 0))\n", + " mean = np.array([0.485, 0.456, 0.406])\n", + " std = np.array([0.229, 0.224, 0.225])\n", + "\n", + " # Un-normalize the images\n", + " inp = std * inp + mean\n", + " # Clip just in case\n", + " inp = np.clip(inp, 0, 1)\n", + " plt.imshow(inp)\n", + " if title is not None:\n", + " plt.title(title)\n", + " plt.pause(0.001) # pause a bit so that plots are updated\n", + " plt.show()\n", + "\n", + "\n", + "# Get a batch of training data\n", + "inputs, classes = next(iter(dataloaders[\"train\"]))\n", + "\n", + "# Make a grid from batch\n", + "out = torchvision.utils.make_grid(inputs)\n", + "\n", + "imshow(out, title=[class_names[x] for x in classes])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + " Now, execute the following code which uses a pre-trained model ResNet18 having replaced the output layer for the ants/bees classification and performs the model training by only changing the weights of this output layer." + ] + }, + { + "cell_type": "code", + "execution_count": 112, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\LENOVO\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\torchvision\\models\\_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.\n", + " warnings.warn(\n", + "C:\\Users\\LENOVO\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\torchvision\\models\\_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=ResNet18_Weights.IMAGENET1K_V1`. You can also use `weights=ResNet18_Weights.DEFAULT` to get the most up-to-date weights.\n", + " warnings.warn(msg)\n", + "C:\\Users\\LENOVO\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\torch\\optim\\lr_scheduler.py:136: UserWarning: Detected call of `lr_scheduler.step()` before `optimizer.step()`. In PyTorch 1.1.0 and later, you should call them in the opposite order: `optimizer.step()` before `lr_scheduler.step()`. Failure to do this will result in PyTorch skipping the first value of the learning rate schedule. See more details at https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate\n", + " warnings.warn(\"Detected call of `lr_scheduler.step()` before `optimizer.step()`. \"\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch 1/10\n", + "----------\n", + "train Loss: 0.7194 Acc: 0.6311\n", + "val Loss: 0.2315 Acc: 0.9281\n", + "\n", + "Epoch 2/10\n", + "----------\n", + "train Loss: 0.4209 Acc: 0.8402\n", + "val Loss: 0.3087 Acc: 0.8693\n", + "\n", + "Epoch 3/10\n", + "----------\n", + "train Loss: 0.4580 Acc: 0.7910\n", + "val Loss: 0.2286 Acc: 0.9216\n", + "\n", + "Epoch 4/10\n", + "----------\n", + "train Loss: 0.5098 Acc: 0.7500\n", + "val Loss: 0.2053 Acc: 0.9477\n", + "\n", + "Epoch 5/10\n", + "----------\n", + "train Loss: 0.4581 Acc: 0.7951\n", + "val Loss: 0.1972 Acc: 0.9281\n", + "\n", + "Epoch 6/10\n", + "----------\n", + "train Loss: 0.4872 Acc: 0.7910\n", + "val Loss: 0.2144 Acc: 0.9412\n", + "\n", + "Epoch 7/10\n", + "----------\n", + "train Loss: 0.3793 Acc: 0.8074\n", + "val Loss: 0.2013 Acc: 0.9477\n", + "\n", + "Epoch 8/10\n", + "----------\n", + "train Loss: 0.3204 Acc: 0.8525\n", + "val Loss: 0.1868 Acc: 0.9477\n", + "\n", + "Epoch 9/10\n", + "----------\n", + "train Loss: 0.3025 Acc: 0.8607\n", + "val Loss: 0.2040 Acc: 0.9542\n", + "\n", + "Epoch 10/10\n", + "----------\n", + "train Loss: 0.3443 Acc: 0.8648\n", + "val Loss: 0.1886 Acc: 0.9477\n", + "\n", + "Training complete in 2m 1s\n", + "Best val Acc: 0.954248\n", + "test loss is 0.177460 and test accuracy is 0.850000\n" + ] + } + ], + "source": [ + "# Get a batch of training data\n", + "# inputs, classes = next(iter(dataloaders['train']))\n", + "\n", + "# Make a grid from batch\n", + "# out = torchvision.utils.make_grid(inputs)\n", + "\n", + "# imshow(out, title=[class_names[x] for x in classes])\n", + "# training\n", + "train_loss_list = []\n", + "valid_loss_list = []\n", + "train_accuracy_list = []\n", + "valid_accuracy_list = []\n", + "test_loss_list = []\n", + "test_accuracy_list = []\n", + "\n", + "num_epochs = 10\n", + "\n", + "def train_model(model, criterion, optimizer, scheduler, num_epochs=25):\n", + " since = time.time()\n", + "\n", + " best_model_wts = copy.deepcopy(model.state_dict())\n", + " best_acc = 0.0\n", + "\n", + " epoch_time = [] # we'll keep track of the time needed for each epoch\n", + " \n", + " \n", + "\n", + " for epoch in range(num_epochs):\n", + " epoch_start = time.time()\n", + " print(\"Epoch {}/{}\".format(epoch + 1, num_epochs))\n", + " print(\"-\" * 10)\n", + "\n", + " # Each epoch has a training and validation phase\n", + " for phase in [\"train\", \"val\"]:\n", + " if phase == \"train\":\n", + " scheduler.step()\n", + " model.train() # Set model to training mode\n", + " else:\n", + " model.eval() # Set model to evaluate mode\n", + "\n", + " running_loss = 0.0\n", + " running_corrects = 0\n", + "\n", + " # Iterate over data.\n", + " for inputs, labels in dataloaders[phase]:\n", + " inputs = inputs.to(device)\n", + " labels = labels.to(device)\n", + "\n", + " # zero the parameter gradients\n", + " optimizer.zero_grad()\n", + "\n", + " # Forward\n", + " # Track history if only in training phase\n", + " with torch.set_grad_enabled(phase == \"train\"):\n", + " outputs = model(inputs)\n", + " _, preds = torch.max(outputs, 1)\n", + " loss = criterion(outputs, labels)\n", + "\n", + " # backward + optimize only if in training phase\n", + " if phase == \"train\":\n", + " loss.backward()\n", + " optimizer.step()\n", + "\n", + " # Statistics\n", + " running_loss += loss.item() * inputs.size(0)\n", + " running_corrects += torch.sum(preds == labels.data)\n", + "\n", + " epoch_loss = running_loss / dataset_sizes[phase]\n", + " \n", + " epoch_acc = running_corrects.double() / dataset_sizes[phase]\n", + " \n", + "\n", + " if phase == \"train\" :\n", + " train_loss_list.append(epoch_loss)\n", + " train_accuracy_list.append(epoch_acc)\n", + " elif phase == \"val\":\n", + " valid_loss_list.append(epoch_loss)\n", + " valid_accuracy_list.append(epoch_acc\n", + " )\n", + "\n", + " print(\"{} Loss: {:.4f} Acc: {:.4f}\".format(phase, epoch_loss, epoch_acc))\n", + "\n", + " # Deep copy the model\n", + " if phase == \"val\" and epoch_acc > best_acc:\n", + " best_acc = epoch_acc\n", + " best_model_wts = copy.deepcopy(model.state_dict())\n", + "\n", + " # Add the epoch time\n", + " t_epoch = time.time() - epoch_start\n", + " epoch_time.append(t_epoch)\n", + " print()\n", + "\n", + " time_elapsed = time.time() - since\n", + " print(\n", + " \"Training complete in {:.0f}m {:.0f}s\".format(\n", + " time_elapsed // 60, time_elapsed % 60\n", + " )\n", + " )\n", + " print(\"Best val Acc: {:4f}\".format(best_acc))\n", + "\n", + " # Load best model weights\n", + " model.load_state_dict(best_model_wts)\n", + " return model, epoch_time\n", + "\n", + "\n", + "def test_model (model, criterion):\n", + " since = time.time()\n", + "\n", + " running_loss = 0.0\n", + " running_corrects = 0\n", + " model.eval()\n", + " for inputs, labels in dataloaders[\"test\"] :\n", + " inputs = inputs.to(device)\n", + " labels = labels.to(device)\n", + "\n", + " outputs = model(inputs)\n", + " _, preds = torch.max(outputs, 1)\n", + " loss = criterion(outputs, labels)\n", + " \n", + " running_loss += loss.item() * inputs.size(0)\n", + " running_corrects += torch.sum(preds == labels.data)\n", + " \n", + " test_loss = running_loss/dataset_sizes[\"test\"]\n", + " test_accuracy = running_corrects.double()/dataset_sizes[\"test\"]\n", + "\n", + " print(\"test loss is %2f and test accuracy is %2f\" %(test_loss, test_accuracy ))\n", + "\n", + " return test_loss, test_accuracy\n", + " \n", + "\n", + "\n", + "# Download a pre-trained ResNet18 model and freeze its weights\n", + "model = torchvision.models.resnet18(pretrained=True)\n", + "for param in model.parameters():\n", + " param.requires_grad = False\n", + "\n", + "# Replace the final fully connected layer\n", + "# Parameters of newly constructed modules have requires_grad=True by default\n", + "\n", + "num_ftrs = model.fc.in_features\n", + "model.fc = nn.Linear(num_ftrs, 2)\n", + "\n", + "# Send the model to the GPU\n", + "model = model.to(device)\n", + "# Set the loss function\n", + "criterion = nn.CrossEntropyLoss()\n", + "\n", + "# Observe that only the parameters of the final layer are being optimized\n", + "optimizer_conv = optim.SGD(model.fc.parameters(), lr=0.001, momentum=0.9)\n", + "exp_lr_scheduler = lr_scheduler.StepLR(optimizer_conv, step_size=7, gamma=0.1)\n", + "model, epoch_time = train_model(\n", + " model, criterion, optimizer_conv, exp_lr_scheduler, num_epochs )\n", + "\n", + "test_loss, test_accuracy = test_model(model, criterion)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Performance of resnet18 model" + ] + }, + { + "cell_type": "code", + "execution_count": 100, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "<Figure size 1000x400 with 2 Axes>" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "\n", + "\n", + "fig_6 = plt.figure() \n", + "fig_6.set_size_inches(10, 4)\n", + "plt.subplots_adjust(wspace=0.2, hspace=0.35)\n", + "ax_6_1 = plt.subplot(1,2,1) \n", + "ax_6_2 = plt.subplot(1,2,2)\n", + "ax_6_1.plot(range(num_epochs), train_loss_list, label = 'train_loss')\n", + "ax_6_1.legend()\n", + "ax_6_1.plot(range(num_epochs), valid_loss_list, label = 'valid_loss')\n", + "ax_6_1.legend()\n", + "ax_6_1.set_xlabel(\"Epoch\")\n", + "ax_6_1.set_ylabel(\"Loss\")\n", + "ax_6_1.set_title(\"Performance of resnet18 model\")\n", + "ax_6_2.plot(range(num_epochs), train_accuracy_list, label = 'train_acc')\n", + "ax_6_2.legend()\n", + "ax_6_2.plot(range(num_epochs), valid_accuracy_list, label = 'valid_acc')\n", + "ax_6_2.legend()\n", + "ax_6_2.set_xlabel(\"Epoch\")\n", + "ax_6_2.set_ylabel(\"accuracy\")\n", + "ax_6_2.set_title(\"Performance of resnet18 model\")\n", + "plt.show()\n", + "\n" + ] } ], "metadata": { -- GitLab