Good practice for next(iter(data))

Author: Abdullah-Jannadi

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

@@ -118,7 +118,10 @@
     "criterion = nn.CrossEntropyLoss()\n",
     "\n",
     "# Get our data\n",
-    "images, labels = next(iter(trainloader))\n",
+    "dataiter = iter(trainloader)\n",
+    "\n",
+    "images, labels = next(dataiter)\n",
+    "\n",
     "# Flatten images\n",
     "images = images.view(images.shape[0], -1)\n",
     "\n",
@@ -153,7 +156,10 @@
     "\n",
     "### Run this to check your work\n",
     "# Get our data\n",
-    "images, labels = next(iter(trainloader))\n",
+    "dataiter = iter(trainloader)\n",
+    "\n",
+    "images, labels = next(dataiter)\n",
+    "\n",
     "# Flatten images\n",
     "images = images.view(images.shape[0], -1)\n",
     "\n",
@@ -310,7 +316,8 @@
     "                      nn.LogSoftmax(dim=1))\n",
     "\n",
     "criterion = nn.NLLLoss()\n",
-    "images, labels = next(iter(trainloader))\n",
+    "dataiter = iter(trainloader)\n",
+    "images, labels = next(dataiter)\n",
     "images = images.view(images.shape[0], -1)\n",
     "\n",
     "logits = model(images)\n",
@@ -373,7 +380,8 @@
    "source": [
     "print('Initial weights - ', model[0].weight)\n",
     "\n",
-    "images, labels = next(iter(trainloader))\n",
+    "dataiter = iter(trainloader)\n",
+    "images, labels = next(dataiter)\n",
     "images.resize_(64, 784)\n",
     "\n",
     "# Clear the gradients, do this because gradients are accumulated\n",
@@ -458,7 +466,8 @@
     "%matplotlib inline\n",
     "import helper\n",
     "\n",
-    "images, labels = next(iter(trainloader))\n",
+    "dataiter = iter(trainloader)\n",
+    "images, labels = next(dataiter)\n",
     "\n",
     "img = images[0].view(1, 784)\n",
     "# Turn off gradients to speed up this part\n",
@@ -494,7 +503,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.7"
+   "version": "3.8.5"
   }
  },
  "nbformat": 4,