Fix training notebook bug related to larger batch size

fogg-lab · Jan 27, 2024 · 6195f5d · 6195f5d
1 parent 2fc347e
commit 6195f5d
Showing 1 changed file with 22 additions and 22 deletions.
diff --git a/notebooks/microvessels_segmentation_training/train_binary_segmentation.ipynb b/notebooks/microvessels_segmentation_training/train_binary_segmentation.ipynb
@@ -3,8 +3,8 @@
     {
       "cell_type": "markdown",
       "metadata": {
-        "colab_type": "text",
-        "id": "view-in-github"
+        "id": "view-in-github",
+        "colab_type": "text"
       },
       "source": [
         "<a href=\"https://colab.research.google.com/github/fogg-lab/tissue-model-analysis-tools/blob/main/notebooks/microvessels_segmentation_training/train_binary_segmentation.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
@@ -39,7 +39,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 1,
+      "execution_count": null,
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/",
@@ -487,7 +487,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 2,
+      "execution_count": null,
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/"
@@ -554,7 +554,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 3,
+      "execution_count": null,
       "metadata": {
         "id": "ZsraYg1EH0iN"
       },
@@ -586,7 +586,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 4,
+      "execution_count": null,
       "metadata": {
         "id": "3hZ4rclKIItR"
       },
@@ -608,7 +608,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 5,
+      "execution_count": null,
       "metadata": {
         "id": "KBnYCIlVZDo3"
       },
@@ -636,7 +636,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 6,
+      "execution_count": null,
       "metadata": {
         "id": "LHtbr58qGY_u"
       },
@@ -667,7 +667,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 7,
+      "execution_count": null,
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/"
@@ -722,7 +722,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 8,
+      "execution_count": null,
       "metadata": {
         "id": "Fo6FQg9XMeUJ"
       },
@@ -757,7 +757,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 9,
+      "execution_count": null,
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/"
@@ -790,7 +790,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 10,
+      "execution_count": null,
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/"
@@ -831,7 +831,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 11,
+      "execution_count": null,
       "metadata": {
         "id": "fAZ_UNB2JbRr"
       },
@@ -857,7 +857,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 12,
+      "execution_count": null,
       "metadata": {
         "id": "qqr7yKMlMWfg"
       },
@@ -904,7 +904,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 13,
+      "execution_count": null,
       "metadata": {
         "id": "4XL-75mJMWmG"
       },
@@ -935,7 +935,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 14,
+      "execution_count": null,
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/",
@@ -1046,7 +1046,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 15,
+      "execution_count": null,
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/",
@@ -1139,7 +1139,7 @@
       ],
       "source": [
         "X, y, _ = val_gen[1]\n",
-        "for i in range(batch_size):\n",
+        "for i in range(min(batch_size, len(X))):\n",
         "    fig, ax = plt.subplots(1, 2, figsize=(10, 5))\n",
         "    ax[0].imshow(X[i][:,:,0], cmap='gray')\n",
         "    ax[1].imshow(y[i][:,:,0], cmap='gray')\n",
@@ -1180,7 +1180,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 16,
+      "execution_count": null,
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/"
@@ -1496,8 +1496,8 @@
     "accelerator": "GPU",
     "colab": {
       "gpuClass": "premium",
-      "include_colab_link": true,
-      "provenance": []
+      "provenance": [],
+      "include_colab_link": true
     },
     "gpuClass": "premium",
     "kernelspec": {
@@ -1519,4 +1519,4 @@
   },
   "nbformat": 4,
   "nbformat_minor": 0
-}
+}