Merge branch 'master' of https://github.com/udacity/deep-learning-v2-pytorch

update local copy

Author: cezannec

intro-to-pytorch/Part 1 - Tensors in PyTorch (Exercises).ipynb

@@ -249,7 +249,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "If you did this correctly, you should see the output `tensor([[ 0.4813]])`.\n",
+    "If you did this correctly, you should see the output `tensor([[ 0.3171]])`.\n",
     "\n",
     "The number of hidden units a parameter of the network, often called a **hyperparameter** to differentiate it from the weights and biases parameters. As you'll see later when we discuss training a neural network, the more hidden units a network has, and the more layers, the better able it is to learn from data and make accurate predictions."
    ]

intro-to-pytorch/Part 1 - Tensors in PyTorch (Solution).ipynb

@@ -70,7 +70,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -86,7 +86,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 49,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -119,7 +119,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 50,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -167,7 +167,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 51,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -211,7 +211,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 52,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -245,30 +245,30 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 55,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "tensor([[ 0.4813]])\n"
+      "tensor([[ 0.3171]])\n"
      ]
     }
    ],
    "source": [
     "### Solution\n",
     "\n",
-    "h = activation(torch.mm(features, W1)) + B1\n",
-    "output = activation(torch.mm(h, W2)) + B2\n",
+    "h = activation(torch.mm(features, W1) + B1)\n",
+    "output = activation(torch.mm(h, W2) + B2)\n",
     "print(output)"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "If you did this correctly, you should see the output `tensor([[ 0.4813]])`.\n",
+    "If you did this correctly, you should see the output `tensor([[ 0.3171]])`.\n",
     "\n",
     "The number of hidden units a parameter of the network, often called a **hyperparameter** to differentiate it from the weights and biases parameters. As you'll see later when we discuss training a neural network, the more hidden units a network has, and the more layers, the better able it is to learn from data and make accurate predictions."
    ]

intro-to-pytorch/Part 7 - Loading Image Data (Exercises).ipynb

@@ -135,7 +135,7 @@
     "\n",
     "```python\n",
     "train_transforms = transforms.Compose([transforms.RandomRotation(30),\n",
-    "                                       transforms.RandomResizedCrop(100),\n",
+    "                                       transforms.RandomResizedCrop(224),\n",
     "                                       transforms.RandomHorizontalFlip(),\n",
     "                                       transforms.ToTensor(),\n",
     "                                       transforms.Normalize([0.5, 0.5, 0.5], \n",