diff --git a/TD2 Deep Learning.ipynb b/TD2 Deep Learning.ipynb index 8bd1351cbc4cb1d496b9a2c5f575d7de53eed44c..1902bccf1198c01335b12f83c8e0136f99cee4ee 100644 --- a/TD2 Deep Learning.ipynb +++ b/TD2 Deep Learning.ipynb @@ -1716,10 +1716,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "id": "be2d31f5", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "<Figure size 640x480 with 1 Axes>" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "import os\n", "\n", @@ -1808,10 +1819,81 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "id": "572d824c", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\anton\\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\\anton\\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\\anton\\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: 0.6258 Acc: 0.6844\n", + "val Loss: 0.3001 Acc: 0.8627\n", + "\n", + "Epoch 2/10\n", + "----------\n", + "train Loss: 0.5831 Acc: 0.7254\n", + "val Loss: 0.3236 Acc: 0.8693\n", + "\n", + "Epoch 3/10\n", + "----------\n", + "train Loss: 0.7128 Acc: 0.6803\n", + "val Loss: 0.1519 Acc: 0.9608\n", + "\n", + "Epoch 4/10\n", + "----------\n", + "train Loss: 0.4125 Acc: 0.8484\n", + "val Loss: 0.2064 Acc: 0.9346\n", + "\n", + "Epoch 5/10\n", + "----------\n", + "train Loss: 0.4823 Acc: 0.8074\n", + "val Loss: 0.2963 Acc: 0.8824\n", + "\n", + "Epoch 6/10\n", + "----------\n", + "train Loss: 0.4049 Acc: 0.8320\n", + "val Loss: 0.1720 Acc: 0.9542\n", + "\n", + "Epoch 7/10\n", + "----------\n", + "train Loss: 0.4392 Acc: 0.8033\n", + "val Loss: 0.1718 Acc: 0.9477\n", + "\n", + "Epoch 8/10\n", + "----------\n", + "train Loss: 0.4233 Acc: 0.8074\n", + "val Loss: 0.1682 Acc: 0.9542\n", + "\n", + "Epoch 9/10\n", + "----------\n", + "train Loss: 0.3947 Acc: 0.8197\n", + "val Loss: 0.1653 Acc: 0.9542\n", + "\n", + "Epoch 10/10\n", + "----------\n", + "train Loss: 0.3435 Acc: 0.8525\n", + "val Loss: 0.1849 Acc: 0.9542\n", + "\n", + "Training complete in 1m 43s\n", + "Best val Acc: 0.960784\n" + ] + } + ], "source": [ "import copy\n", "import os\n", @@ -2008,6 +2090,373 @@ "\n", "Apply ther quantization (post and quantization aware) and evaluate impact on model size and accuracy." ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Test Loss: 0.1519 Acc: 0.9608\n" + ] + } + ], + "source": [ + "def eval_model(model, dataloader):\n", + " model.eval() # Set model to evaluate mode\n", + " running_loss = 0.0\n", + " running_corrects = 0\n", + "\n", + " # Iterate over data.\n", + " for inputs, labels in dataloader:\n", + " inputs = inputs.to(device)\n", + " labels = labels.to(device)\n", + " # Forward\n", + " with torch.no_grad():\n", + " outputs = model(inputs)\n", + " _, preds = torch.max(outputs, 1)\n", + " loss = criterion(outputs, labels)\n", + "\n", + "\n", + "\n", + " # Statistics\n", + " running_loss += loss.item() * inputs.size(0)\n", + " running_corrects += torch.sum(preds == labels.data)\n", + "\n", + " test_loss = running_loss / len(dataloader.dataset)\n", + " test_acc = running_corrects.double() / len(dataloader.dataset)\n", + "\n", + " print(\"Test Loss: {:.4f} Acc: {:.4f}\".format(test_loss, test_acc))\n", + "\n", + "\n", + "#Remplacer par un test set ?\n", + "eval_model(model, dataloaders[\"val\"])" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\anton\\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\\anton\\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\\anton\\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: 0.6410 Acc: 0.6189\n", + "val Loss: 0.4122 Acc: 0.8431\n", + "\n", + "Epoch 2/10\n", + "----------\n", + "train Loss: 0.4754 Acc: 0.7910\n", + "val Loss: 0.2508 Acc: 0.9281\n", + "\n", + "Epoch 3/10\n", + "----------\n", + "train Loss: 0.4369 Acc: 0.7910\n", + "val Loss: 0.4421 Acc: 0.7778\n", + "\n", + "Epoch 4/10\n", + "----------\n", + "train Loss: 0.5607 Acc: 0.7254\n", + "val Loss: 0.2220 Acc: 0.9216\n", + "\n", + "Epoch 5/10\n", + "----------\n", + "train Loss: 0.4189 Acc: 0.8074\n", + "val Loss: 0.2442 Acc: 0.9150\n", + "\n", + "Epoch 6/10\n", + "----------\n", + "train Loss: 0.5837 Acc: 0.7131\n", + "val Loss: 0.2100 Acc: 0.9673\n", + "\n", + "Epoch 7/10\n", + "----------\n", + "train Loss: 0.3441 Acc: 0.8566\n", + "val Loss: 0.2237 Acc: 0.9346\n", + "\n", + "Epoch 8/10\n", + "----------\n", + "train Loss: 0.3663 Acc: 0.8279\n", + "val Loss: 0.2004 Acc: 0.9608\n", + "\n", + "Epoch 9/10\n", + "----------\n", + "train Loss: 0.4002 Acc: 0.8033\n", + "val Loss: 0.1947 Acc: 0.9673\n", + "\n", + "Epoch 10/10\n", + "----------\n", + "train Loss: 0.4264 Acc: 0.7992\n", + "val Loss: 0.2019 Acc: 0.9477\n", + "\n", + "Training complete in 1m 42s\n", + "Best val Acc: 0.967320\n" + ] + } + ], + "source": [ + "model = torchvision.models.resnet18(pretrained=True)\n", + "for param in model.parameters():\n", + " param.requires_grad = False\n", + "\n", + "num_ftrs = model.fc.in_features\n", + "model.fc = nn.Sequential(\n", + " nn.Linear(num_ftrs, 256), \n", + " nn.ReLU(), \n", + " nn.Dropout(0.5), \n", + " nn.Linear(256, 2) \n", + ")\n", + "\n", + "# Set the loss function\n", + "criterion = nn.CrossEntropyLoss()\n", + "\n", + "optimizer_conv = optim.SGD(model.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=10 #Nb d'itérations\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Test Loss: 0.2100 Acc: 0.9673\n", + "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): BasicBlock(\n", + " (conv1): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=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", + " )\n", + " (1): BasicBlock(\n", + " (conv1): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=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", + " )\n", + " )\n", + " (layer2): Sequential(\n", + " (0): BasicBlock(\n", + " (conv1): Conv2d(64, 128, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)\n", + " (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=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", + " (downsample): Sequential(\n", + " (0): Conv2d(64, 128, kernel_size=(1, 1), stride=(2, 2), bias=False)\n", + " (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " )\n", + " )\n", + " (1): BasicBlock(\n", + " (conv1): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=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", + " )\n", + " )\n", + " (layer3): Sequential(\n", + " (0): BasicBlock(\n", + " (conv1): Conv2d(128, 256, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)\n", + " (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=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", + " (downsample): Sequential(\n", + " (0): Conv2d(128, 256, kernel_size=(1, 1), stride=(2, 2), bias=False)\n", + " (1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " )\n", + " )\n", + " (1): BasicBlock(\n", + " (conv1): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=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", + " )\n", + " )\n", + " (layer4): Sequential(\n", + " (0): BasicBlock(\n", + " (conv1): Conv2d(256, 512, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)\n", + " (bn1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=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", + " (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): BasicBlock(\n", + " (conv1): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " (bn1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=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", + " )\n", + " )\n", + " (avgpool): AdaptiveAvgPool2d(output_size=(1, 1))\n", + " (fc): Sequential(\n", + " (0): Linear(in_features=512, out_features=256, bias=True)\n", + " (1): ReLU()\n", + " (2): Dropout(p=0.5, inplace=False)\n", + " (3): Linear(in_features=256, out_features=2, bias=True)\n", + " )\n", + ")\n" + ] + } + ], + "source": [ + "#Remplacer par un test set ?\n", + "eval_model(model, dataloaders[\"val\"])\n", + "print(model)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Quantization" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Test Loss: 0.2095 Acc: 0.9673\n", + "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): BasicBlock(\n", + " (conv1): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=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", + " )\n", + " (1): BasicBlock(\n", + " (conv1): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=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", + " )\n", + " )\n", + " (layer2): Sequential(\n", + " (0): BasicBlock(\n", + " (conv1): Conv2d(64, 128, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)\n", + " (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=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", + " (downsample): Sequential(\n", + " (0): Conv2d(64, 128, kernel_size=(1, 1), stride=(2, 2), bias=False)\n", + " (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " )\n", + " )\n", + " (1): BasicBlock(\n", + " (conv1): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=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", + " )\n", + " )\n", + " (layer3): Sequential(\n", + " (0): BasicBlock(\n", + " (conv1): Conv2d(128, 256, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)\n", + " (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=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", + " (downsample): Sequential(\n", + " (0): Conv2d(128, 256, kernel_size=(1, 1), stride=(2, 2), bias=False)\n", + " (1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " )\n", + " )\n", + " (1): BasicBlock(\n", + " (conv1): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=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", + " )\n", + " )\n", + " (layer4): Sequential(\n", + " (0): BasicBlock(\n", + " (conv1): Conv2d(256, 512, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)\n", + " (bn1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=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", + " (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): BasicBlock(\n", + " (conv1): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " (bn1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=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", + " )\n", + " )\n", + " (avgpool): AdaptiveAvgPool2d(output_size=(1, 1))\n", + " (fc): Sequential(\n", + " (0): DynamicQuantizedLinear(in_features=512, out_features=256, dtype=torch.qint8, qscheme=torch.per_tensor_affine)\n", + " (1): ReLU()\n", + " (2): Dropout(p=0.5, inplace=False)\n", + " (3): DynamicQuantizedLinear(in_features=256, out_features=2, dtype=torch.qint8, qscheme=torch.per_tensor_affine)\n", + " )\n", + ")\n" + ] + } + ], + "source": [ + "quantized_model = torch.quantization.quantize_dynamic(model, dtype=torch.qint8)\n", + "eval_model(quantized_model, dataloaders[\"val\"])\n", + "print(quantized_model)" + ] } ], "metadata": {