diff --git a/TD2 Deep Learning.ipynb b/TD2 Deep Learning.ipynb
index 780cc6f59bcac17f63cd9a03502f250b2ca6e700..650d72834cd3477a3b902e34a8bc9b5b9020e84a 100644
--- a/TD2 Deep Learning.ipynb	
+++ b/TD2 Deep Learning.ipynb	
@@ -215,7 +215,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 47,
    "id": "462666a2",
    "metadata": {},
    "outputs": [
@@ -296,7 +296,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 48,
    "id": "317bf070",
    "metadata": {},
    "outputs": [
@@ -360,7 +360,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 49,
    "id": "4b53f229",
    "metadata": {},
    "outputs": [
@@ -368,16 +368,34 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Epoch: 0 \tTraining Loss: 12.224831 \tValidation Loss: 19.767630\n",
-      "Validation loss decreased (inf --> 19.767630).  Saving model ...\n",
-      "Epoch: 1 \tTraining Loss: 11.779677 \tValidation Loss: 19.502304\n",
-      "Validation loss decreased (19.767630 --> 19.502304).  Saving model ...\n",
-      "Epoch: 2 \tTraining Loss: 11.402885 \tValidation Loss: 19.299951\n",
-      "Validation loss decreased (19.502304 --> 19.299951).  Saving model ...\n",
-      "Epoch: 3 \tTraining Loss: 10.922978 \tValidation Loss: 20.018273\n",
-      "Epoch: 4 \tTraining Loss: 10.535478 \tValidation Loss: 20.801044\n",
-      "Epoch: 5 \tTraining Loss: 10.175075 \tValidation Loss: 20.377939\n",
-      "Early stopping after 5 epochss.\n"
+      "Epoch: 0 \tTraining Loss: 43.971403 \tValidation Loss: 38.781364\n",
+      "Validation loss decreased (inf --> 38.781364).  Saving model ...\n",
+      "Epoch: 1 \tTraining Loss: 34.860234 \tValidation Loss: 32.887555\n",
+      "Validation loss decreased (38.781364 --> 32.887555).  Saving model ...\n",
+      "Epoch: 2 \tTraining Loss: 30.713754 \tValidation Loss: 30.105906\n",
+      "Validation loss decreased (32.887555 --> 30.105906).  Saving model ...\n",
+      "Epoch: 3 \tTraining Loss: 28.186929 \tValidation Loss: 28.076022\n",
+      "Validation loss decreased (30.105906 --> 28.076022).  Saving model ...\n",
+      "Epoch: 4 \tTraining Loss: 26.351580 \tValidation Loss: 26.367747\n",
+      "Validation loss decreased (28.076022 --> 26.367747).  Saving model ...\n",
+      "Epoch: 5 \tTraining Loss: 24.947239 \tValidation Loss: 26.368494\n",
+      "Epoch: 6 \tTraining Loss: 23.778135 \tValidation Loss: 24.579198\n",
+      "Validation loss decreased (26.367747 --> 24.579198).  Saving model ...\n",
+      "Epoch: 7 \tTraining Loss: 22.707515 \tValidation Loss: 24.203169\n",
+      "Validation loss decreased (24.579198 --> 24.203169).  Saving model ...\n",
+      "Epoch: 8 \tTraining Loss: 21.805590 \tValidation Loss: 23.090124\n",
+      "Validation loss decreased (24.203169 --> 23.090124).  Saving model ...\n",
+      "Epoch: 9 \tTraining Loss: 21.043298 \tValidation Loss: 22.905686\n",
+      "Validation loss decreased (23.090124 --> 22.905686).  Saving model ...\n",
+      "Epoch: 10 \tTraining Loss: 20.250996 \tValidation Loss: 23.170775\n",
+      "Epoch: 11 \tTraining Loss: 19.621161 \tValidation Loss: 22.586260\n",
+      "Validation loss decreased (22.905686 --> 22.586260).  Saving model ...\n",
+      "Epoch: 12 \tTraining Loss: 18.967947 \tValidation Loss: 22.084914\n",
+      "Validation loss decreased (22.586260 --> 22.084914).  Saving model ...\n",
+      "Epoch: 13 \tTraining Loss: 18.294242 \tValidation Loss: 22.170993\n",
+      "Epoch: 14 \tTraining Loss: 17.742965 \tValidation Loss: 22.235334\n",
+      "Epoch: 15 \tTraining Loss: 17.191995 \tValidation Loss: 22.188067\n",
+      "Early stopping after 15 epochss.\n"
      ]
     }
    ],
@@ -473,13 +491,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 50,
    "id": "d39df818",
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -510,7 +528,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 51,
    "id": "e93efdfc",
    "metadata": {},
    "outputs": [
@@ -518,20 +536,20 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Test Loss: 21.403010\n",
+      "Test Loss: 21.919417\n",
       "\n",
-      "Test Accuracy of airplane: 68% (681/1000)\n",
-      "Test Accuracy of automobile: 74% (744/1000)\n",
-      "Test Accuracy of  bird: 50% (508/1000)\n",
-      "Test Accuracy of   cat: 37% (371/1000)\n",
-      "Test Accuracy of  deer: 56% (566/1000)\n",
-      "Test Accuracy of   dog: 48% (480/1000)\n",
-      "Test Accuracy of  frog: 78% (780/1000)\n",
-      "Test Accuracy of horse: 72% (724/1000)\n",
-      "Test Accuracy of  ship: 74% (748/1000)\n",
-      "Test Accuracy of truck: 72% (724/1000)\n",
+      "Test Accuracy of airplane: 67% (679/1000)\n",
+      "Test Accuracy of automobile: 78% (782/1000)\n",
+      "Test Accuracy of  bird: 59% (596/1000)\n",
+      "Test Accuracy of   cat: 39% (398/1000)\n",
+      "Test Accuracy of  deer: 55% (554/1000)\n",
+      "Test Accuracy of   dog: 48% (482/1000)\n",
+      "Test Accuracy of  frog: 67% (678/1000)\n",
+      "Test Accuracy of horse: 60% (605/1000)\n",
+      "Test Accuracy of  ship: 71% (713/1000)\n",
+      "Test Accuracy of truck: 68% (687/1000)\n",
       "\n",
-      "Test Accuracy (Overall): 63% (6326/10000)\n"
+      "Test Accuracy (Overall): 61% (6174/10000)\n"
      ]
     }
    ],
@@ -948,21 +966,21 @@
   },
   {
    "cell_type": "markdown",
-   "id": "efb5df69",
+   "id": "189a6a2b",
    "metadata": {},
    "source": [
-    "We compare the results obtained with this new network to those obtained previously. Our new model is better than the first model on almost all classes. We get XX% of accuracy on average over all the classes."
+    "We compare the results obtained with this new network to those obtained previously. Our new model is better than the first model on almost all classes. We get 69% of accuracy on average over all the classes compare to 61% with the initial model."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
-   "id": "86f7cf40",
+   "execution_count": 52,
+   "id": "09fdf14a",
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -1008,10 +1026,28 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 39,
    "id": "ef623c26",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "model:  fp32  \t Size (KB): 2330.519\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "2330519"
+      ]
+     },
+     "execution_count": 39,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "import os\n",
     "\n",
@@ -1037,10 +1073,28 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 40,
    "id": "c4c65d4b",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "model:  int8  \t Size (KB): 659.379\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "659379"
+      ]
+     },
+     "execution_count": 40,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "import torch.quantization\n",
     "\n",
@@ -1057,6 +1111,143 @@
     "For each class, compare the classification test accuracy of the initial model and the quantized model. Also give the overall test accuracy for both models."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "id": "0d85231c",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Test Loss: 18.854834\n",
+      "\n",
+      "Test Accuracy of airplane: 78% (786/1000)\n",
+      "Test Accuracy of automobile: 83% (831/1000)\n",
+      "Test Accuracy of  bird: 60% (605/1000)\n",
+      "Test Accuracy of   cat: 44% (443/1000)\n",
+      "Test Accuracy of  deer: 64% (641/1000)\n",
+      "Test Accuracy of   dog: 56% (567/1000)\n",
+      "Test Accuracy of  frog: 82% (824/1000)\n",
+      "Test Accuracy of horse: 71% (711/1000)\n",
+      "Test Accuracy of  ship: 78% (785/1000)\n",
+      "Test Accuracy of truck: 73% (731/1000)\n",
+      "\n",
+      "Test Accuracy (Overall): 69% (6924/10000)\n"
+     ]
+    }
+   ],
+   "source": [
+    "model.load_state_dict(torch.load(\"./model_cifar_exo1.pt\"))\n",
+    "quantized_model = torch.quantization.quantize_dynamic(model, dtype=torch.qint8)\n",
+    "torch.save(quantized_model.state_dict(), \"model_cifar_exo2_quantized.pt\")\n",
+    "\n",
+    "# track test loss\n",
+    "test_loss = 0.0\n",
+    "class_correct_quant = list(0.0 for i in range(10))\n",
+    "class_total_quant = list(0.0 for i in range(10))\n",
+    "\n",
+    "quantized_model.eval()\n",
+    "# iterate over test data\n",
+    "for data, target in test_loader:\n",
+    "    # move tensors to GPU if CUDA is available\n",
+    "    if train_on_gpu:\n",
+    "        data, target = data.cuda(), target.cuda()\n",
+    "    # forward pass: compute predicted outputs by passing inputs to the model\n",
+    "    output = quantized_model(data)\n",
+    "    # calculate the batch loss\n",
+    "    loss = criterion(output, target)\n",
+    "    # update test loss\n",
+    "    test_loss += loss.item() * data.size(0)\n",
+    "    # convert output probabilities to predicted class\n",
+    "    _, pred = torch.max(output, 1)\n",
+    "    # compare predictions to true label\n",
+    "    correct_tensor = pred.eq(target.data.view_as(pred))\n",
+    "    correct = (\n",
+    "        np.squeeze(correct_tensor.numpy())\n",
+    "        if not train_on_gpu\n",
+    "        else np.squeeze(correct_tensor.cpu().numpy())\n",
+    "    )\n",
+    "    # calculate test accuracy for each object class\n",
+    "    for i in range(batch_size):\n",
+    "        label = target.data[i]\n",
+    "        class_correct_quant[label] += correct[i].item()\n",
+    "        class_total_quant[label] += 1\n",
+    "\n",
+    "# average test loss\n",
+    "test_loss = test_loss / len(test_loader)\n",
+    "print(\"Test Loss: {:.6f}\\n\".format(test_loss))\n",
+    "\n",
+    "for i in range(10):\n",
+    "    if class_total2[i] > 0:\n",
+    "        print(\n",
+    "            \"Test Accuracy of %5s: %2d%% (%2d/%2d)\"\n",
+    "            % (\n",
+    "                classes[i],\n",
+    "                100 * class_correct_quant[i] / class_total_quant[i],\n",
+    "                np.sum(class_correct_quant[i]),\n",
+    "                np.sum(class_total_quant[i]),\n",
+    "            )\n",
+    "        )\n",
+    "    else:\n",
+    "        print(\"Test Accuracy of %5s: N/A (no training examples)\" % (classes[i]))\n",
+    "\n",
+    "print(\n",
+    "    \"\\nTest Accuracy (Overall): %2d%% (%2d/%2d)\"\n",
+    "    % (\n",
+    "        100.0 * np.sum(class_correct_quant) / np.sum(class_total_quant),\n",
+    "        np.sum(class_correct_quant),\n",
+    "        np.sum(class_total_quant),\n",
+    "    )\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "id": "906262db",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "accuracy_initial = [correct / total for correct, total in zip(class_correct2, class_total2)]\n",
+    "accuracy_quant = [correct / total for correct, total in zip(class_correct_quant, class_total_quant)]\n",
+    "\n",
+    "x = np.arange(len(classes))\n",
+    "width = .35\n",
+    "\n",
+    "fig, ax = plt.subplots()\n",
+    "r1 = ax.bar(x - width/2, accuracy_initial, width, label=\"Initial Model\")\n",
+    "r2 = ax.bar(x + width/2, accuracy_quant, width, label=\"New Model\")\n",
+    "\n",
+    "ax.set_xlabel('Classes')\n",
+    "ax.set_ylabel('Accuracy')\n",
+    "ax.set_title('Accuracy comparison by class')\n",
+    "ax.set_xticks(x)\n",
+    "ax.set_xticklabels(classes)\n",
+    "ax.legend()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "899fd729",
+   "metadata": {},
+   "source": [
+    "We compare the results obtained with this quantized network to the initial model. Our new quantized model is as good as the initial model on all classes. We get 69% of accuracy on average over all the classes on both the initial model and the quantized model. We can therefore store our model in a smaller format."
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "a0a34b90",