Make sure we're loading MNIST from the same spot in Parts 2 and 3.

Author: mcleonard

intro-to-pytorch/Part 2 - Neural Networks in PyTorch (Exercises).ipynb

@@ -58,7 +58,7 @@
     "                              ])\n",
     "\n",
     "# Download and load the training data\n",
-    "trainset = datasets.MNIST('MNIST_data/', download=True, train=True, transform=transform)\n",
+    "trainset = datasets.MNIST('~/.pytorch/MNIST_data/', download=True, train=True, transform=transform)\n",
     "trainloader = torch.utils.data.DataLoader(trainset, batch_size=64, shuffle=True)"
    ]
   },

intro-to-pytorch/Part 2 - Neural Networks in PyTorch (Solution).ipynb

@@ -57,7 +57,7 @@
     "                              transforms.Normalize((0.5,), (0.5,)),\n",
     "                              ])\n",
     "# Download and load the training data\n",
-    "trainset = datasets.MNIST('MNIST_data/', download=True, train=True, transform=transform)\n",
+    "trainset = datasets.MNIST('~/.pytorch/MNIST_data/', download=True, train=True, transform=transform)\n",
     "trainloader = torch.utils.data.DataLoader(trainset, batch_size=64, shuffle=True)"
    ]
   },

intro-to-pytorch/Part 3 - Training Neural Networks (Exercises).ipynb

@@ -93,6 +93,14 @@
     "trainloader = torch.utils.data.DataLoader(trainset, batch_size=64, shuffle=True)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Note\n",
+    "If you haven't seen `nn.Sequential` yet, please finish the end of the Part 2 notebook."
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,