fix normalization of loss calculations

Author: cezannec

convolutional-neural-networks/mnist-mlp/mnist_mlp_exercise.ipynb

@@ -260,7 +260,7 @@
     "        \n",
     "    # print training statistics \n",
     "    # calculate average loss over an epoch\n",
-    "    train_loss = train_loss/len(train_loader.dataset)\n",
+    "    train_loss = train_loss/len(train_loader.sampler)\n",
     "\n",
     "    print('Epoch: {} \\tTraining Loss: {:.6f}'.format(\n",
     "        epoch+1, \n",
@@ -315,7 +315,7 @@
     "        class_total[label] += 1\n",
     "\n",
     "# calculate and print avg test loss\n",
-    "test_loss = test_loss/len(test_loader.dataset)\n",
+    "test_loss = test_loss/len(test_loader.sampler)\n",
     "print('Test Loss: {:.6f}\\n'.format(test_loss))\n",
     "\n",
     "for i in range(10):\n",

convolutional-neural-networks/mnist-mlp/mnist_mlp_solution.ipynb

@@ -360,7 +360,7 @@
     "             \n",
     "    # print training statistics \n",
     "    # calculate average loss over an epoch\n",
-    "    train_loss = train_loss/len(train_loader.dataset)\n",
+    "    train_loss = train_loss/len(train_loader.sampler)\n",
     "\n",
     "    print('Epoch: {} \\tTraining Loss: {:.6f}'.format(\n",
     "        epoch+1, \n",
@@ -430,7 +430,7 @@
     "        class_total[label] += 1\n",
     "\n",
     "# calculate and print avg test loss\n",
-    "test_loss = test_loss/len(test_loader.dataset)\n",
+    "test_loss = test_loss/len(test_loader.sampler)\n",
     "print('Test Loss: {:.6f}\\n'.format(test_loss))\n",
     "\n",
     "for i in range(10):\n",

convolutional-neural-networks/mnist-mlp/mnist_mlp_solution_with_validation.ipynb

@@ -417,8 +417,8 @@
     "        \n",
     "    # print training/validation statistics \n",
     "    # calculate average loss over an epoch\n",
-    "    train_loss = train_loss/len(train_loader.dataset)\n",
-    "    valid_loss = valid_loss/len(valid_loader.dataset)\n",
+    "    train_loss = train_loss/len(train_loader.sampler)\n",
+    "    valid_loss = valid_loss/len(valid_loader.sampler)\n",
     "    \n",
     "    print('Epoch: {} \\tTraining Loss: {:.6f} \\tValidation Loss: {:.6f}'.format(\n",
     "        epoch+1, \n",
@@ -515,7 +515,7 @@
     "        class_total[label] += 1\n",
     "\n",
     "# calculate and print avg test loss\n",
-    "test_loss = test_loss/len(test_loader.dataset)\n",
+    "test_loss = test_loss/len(test_loader.sampler)\n",
     "print('Test Loss: {:.6f}\\n'.format(test_loss))\n",
     "\n",
     "for i in range(10):\n",