From a4c034557bd9f5411b136e3ec7a824edc36e182c Mon Sep 17 00:00:00 2001
From: Soumik Rakshit <19soumik.rakshit96@gmail.com>
Date: Tue, 15 Aug 2023 07:00:21 +0000
Subject: [PATCH] fix: pointnet example

---
 .../pyg/pointnet-classification/02_pointnet_plus_plus.ipynb | 6 ++++--
 colabs/pyg/pointnet-classification/03_sweep.ipynb           | 6 ++++--
 2 files changed, 8 insertions(+), 4 deletions(-)

diff --git a/colabs/pyg/pointnet-classification/02_pointnet_plus_plus.ipynb b/colabs/pyg/pointnet-classification/02_pointnet_plus_plus.ipynb
index 26b36c74..12eee4b8 100644
--- a/colabs/pyg/pointnet-classification/02_pointnet_plus_plus.ipynb
+++ b/colabs/pyg/pointnet-classification/02_pointnet_plus_plus.ipynb
@@ -363,8 +363,9 @@
     "        range(num_train_examples),\n",
     "        desc=f\"Training Epoch {epoch}/{config.epochs}\"\n",
     "    )\n",
+    "    data_iter = iter(train_loader)\n",
     "    for batch_idx in progress_bar:\n",
-    "        data = next(iter(train_loader)).to(device)\n",
+    "        data = next(data_iter).to(device)\n",
     "        \n",
     "        optimizer.zero_grad()\n",
     "        prediction = model(data)\n",
@@ -394,8 +395,9 @@
     "        range(num_val_examples),\n",
     "        desc=f\"Validation Epoch {epoch}/{config.epochs}\"\n",
     "    )\n",
+    "    data_iter = iter(val_loader)\n",
     "    for batch_idx in progress_bar:\n",
-    "        data = next(iter(val_loader)).to(device)\n",
+    "        data = next(data_iter).to(device)\n",
     "        \n",
     "        with torch.no_grad():\n",
     "            prediction = model(data)\n",
diff --git a/colabs/pyg/pointnet-classification/03_sweep.ipynb b/colabs/pyg/pointnet-classification/03_sweep.ipynb
index 09845a97..d029f42d 100644
--- a/colabs/pyg/pointnet-classification/03_sweep.ipynb
+++ b/colabs/pyg/pointnet-classification/03_sweep.ipynb
@@ -285,8 +285,9 @@
     "            range(num_train_examples),\n",
     "            desc=f\"Training Epoch {epoch}/{config.epochs}\"\n",
     "        )\n",
+    "        data_iter = iter(train_loader)\n",
     "        for batch_idx in progress_bar:\n",
-    "            data = next(iter(train_loader)).to(device)\n",
+    "            data = next(data_iter).to(device)\n",
     "\n",
     "            optimizer.zero_grad()\n",
     "            prediction = model(data)\n",
@@ -314,8 +315,9 @@
     "            range(num_val_examples),\n",
     "            desc=f\"Validation Epoch {epoch}/{config.epochs}\"\n",
     "        )\n",
+    "        data_iter = iter(val_loader)\n",
     "        for batch_idx in progress_bar:\n",
-    "            data = next(iter(val_loader)).to(device)\n",
+    "            data = next(data_iter).to(device)\n",
     "\n",
     "            with torch.no_grad():\n",
     "                prediction = model(data)\n",