docs: train only for 4 epochs to speed up execution

The result is not great with 32 epochs, either.
Safe-DS · Nov 26, 2024 · 1dfa9f1 · 1dfa9f1
1 parent fbf3973
commit 1dfa9f1
Showing 1 changed file with 102 additions and 33 deletions.
diff --git a/docs/tutorials/convolutional_neural_network_for_image_classification.ipynb b/docs/tutorials/convolutional_neural_network_for_image_classification.ipynb
@@ -47,17 +47,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "initial_id",
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "ExecuteTime": {
+     "end_time": "2024-11-26T15:45:45.603033Z",
+     "start_time": "2024-11-26T15:45:45.458288Z"
+    }
    },
    "source": [
     "from safeds.data.image.containers import ImageList\n",
     "\n",
     "images, filepaths = ImageList.from_files(\"data/shapes\", return_filenames=True)"
    ],
-   "outputs": []
+   "outputs": [],
+   "execution_count": 41
   },
   {
    "cell_type": "markdown",
@@ -81,11 +85,15 @@
     ")"
    ],
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "ExecuteTime": {
+     "end_time": "2024-11-26T15:45:45.611268Z",
+     "start_time": "2024-11-26T15:45:45.607362Z"
+    }
    },
    "id": "66dcf95a3fa51f23",
-   "execution_count": null,
-   "outputs": []
+   "outputs": [],
+   "execution_count": 42
   },
   {
    "cell_type": "markdown",
@@ -105,11 +113,15 @@
     "dataset = ImageDataset[Column](images, labels, shuffle=True)"
    ],
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "ExecuteTime": {
+     "end_time": "2024-11-26T15:45:45.623054Z",
+     "start_time": "2024-11-26T15:45:45.617103Z"
+    }
    },
    "id": "32056ddf5396e070",
-   "execution_count": null,
-   "outputs": []
+   "outputs": [],
+   "execution_count": 43
   },
   {
    "cell_type": "markdown",
@@ -146,11 +158,15 @@
     "]"
    ],
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "ExecuteTime": {
+     "end_time": "2024-11-26T15:45:45.655060Z",
+     "start_time": "2024-11-26T15:45:45.650789Z"
+    }
    },
    "id": "806a8091249d533a",
-   "execution_count": null,
-   "outputs": []
+   "outputs": [],
+   "execution_count": 44
   },
   {
    "cell_type": "markdown",
@@ -172,11 +188,15 @@
     ")"
    ],
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "ExecuteTime": {
+     "end_time": "2024-11-26T15:45:45.677800Z",
+     "start_time": "2024-11-26T15:45:45.673254Z"
+    }
    },
    "id": "af68cc0d32655d32",
-   "execution_count": null,
-   "outputs": []
+   "outputs": [],
+   "execution_count": 45
   },
   {
    "cell_type": "markdown",
@@ -198,15 +218,17 @@
   },
   {
    "cell_type": "code",
-   "source": [
-    "cnn_fitted = cnn.fit(dataset, epoch_size=32, batch_size=16)"
-   ],
+   "source": "cnn_fitted = cnn.fit(dataset, epoch_size=4, batch_size=16)",
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "ExecuteTime": {
+     "end_time": "2024-11-26T15:45:47.968603Z",
+     "start_time": "2024-11-26T15:45:45.698565Z"
+    }
    },
    "id": "381627a94d500675",
-   "execution_count": null,
-   "outputs": []
+   "outputs": [],
+   "execution_count": 46
   },
   {
    "cell_type": "markdown",
@@ -224,11 +246,15 @@
     "prediction = cnn_fitted.predict(dataset.get_input())"
    ],
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "ExecuteTime": {
+     "end_time": "2024-11-26T15:45:48.153080Z",
+     "start_time": "2024-11-26T15:45:47.977476Z"
+    }
    },
    "id": "62f63dd68362c8b7",
-   "execution_count": null,
-   "outputs": []
+   "outputs": [],
+   "execution_count": 47
   },
   {
    "cell_type": "markdown",
@@ -246,11 +272,15 @@
     "shuffled_prediction = prediction.shuffle()"
    ],
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "ExecuteTime": {
+     "end_time": "2024-11-26T15:45:48.164044Z",
+     "start_time": "2024-11-26T15:45:48.159184Z"
+    }
    },
    "id": "779277d73e30554d",
-   "execution_count": null,
-   "outputs": []
+   "outputs": [],
+   "execution_count": 48
   },
   {
    "cell_type": "markdown",
@@ -268,11 +298,27 @@
     "shuffled_prediction.get_input().remove_image_by_index(list(range(9, len(prediction))))"
    ],
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "ExecuteTime": {
+     "end_time": "2024-11-26T15:45:48.191309Z",
+     "start_time": "2024-11-26T15:45:48.180506Z"
+    }
    },
    "id": "a5ddbbfba41aa7f",
-   "execution_count": null,
-   "outputs": []
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<safeds.data.image.containers._single_size_image_list._SingleSizeImageList at 0x1a0e4b11dc0>"
+      ],
+      "image/png": "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"
+     },
+     "execution_count": 49,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "execution_count": 49
   },
   {
    "cell_type": "markdown",
@@ -290,11 +336,34 @@
     "shuffled_prediction.get_output().to_list()[0:9]"
    ],
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "ExecuteTime": {
+     "end_time": "2024-11-26T15:45:48.204453Z",
+     "start_time": "2024-11-26T15:45:48.199228Z"
+    }
    },
    "id": "7081595d7100fb42",
-   "execution_count": null,
-   "outputs": []
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['circles',\n",
+       " 'circles',\n",
+       " 'circles',\n",
+       " 'circles',\n",
+       " 'circles',\n",
+       " 'circles',\n",
+       " 'circles',\n",
+       " 'circles',\n",
+       " 'circles']"
+      ]
+     },
+     "execution_count": 50,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "execution_count": 50
   }
  ],
  "metadata": {