worked_examples/non-geospatial/classification_mnist/Pipeline.ipynb

{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Classification mnist\n",
    "\n",
    "This is an example to show how you can use MapReader on non-patchified datasets."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Load\n",
    "https://mapreader.readthedocs.io/en/latest/User-guide/Load.html"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load images"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will load our mnist images as patches so MapReader knows we are going to be using these as our unit of analysis."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "5a79a0015f42459783d21f901ace80e3",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "0it [00:00, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "53acbe89bbfd47b9a1b003e55dde59a9",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/200 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from mapreader import load_patches\n",
    "\n",
    "path2images = \"./small_mnist/*.png\"\n",
    "my_files = load_patches(path2images)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of images: 200\n"
     ]
    }
   ],
   "source": [
    "# len() shows the total number of images currently read (or sliced, see below)\n",
    "print(f\"Number of images: {len(my_files)}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "#images: 200\n",
      "\n",
      "#parents: 0\n",
      "\n",
      "#patches: 200\n",
      "49081.png\n",
      "51816.png\n",
      "39566.png\n",
      "24251.png\n",
      "20989.png\n",
      "29013.png\n",
      "10692.png\n",
      "58832.png\n",
      "30556.png\n",
      "10686.png\n",
      "9294.png\n",
      "...\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(my_files)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x600 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "my_files.show_sample(num_samples=3, tree_level=\"patch\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] Add shape, tree level: patch\n"
     ]
    }
   ],
   "source": [
    "my_files.add_shape(tree_level=\"patch\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "parent_df, patch_df = my_files.convert_images()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
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       "      <th>image_path</th>\n",
       "      <th>pixel_bounds</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>49081.png</th>\n",
       "      <td>None</td>\n",
       "      <td>/Users/rwood/LwM/mapreader/MapReader/worked_ex...</td>\n",
       "      <td>(0, 0, 28, 28)</td>\n",
       "      <td>(28, 28, 1)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51816.png</th>\n",
       "      <td>None</td>\n",
       "      <td>/Users/rwood/LwM/mapreader/MapReader/worked_ex...</td>\n",
       "      <td>(0, 0, 28, 28)</td>\n",
       "      <td>(28, 28, 1)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39566.png</th>\n",
       "      <td>None</td>\n",
       "      <td>/Users/rwood/LwM/mapreader/MapReader/worked_ex...</td>\n",
       "      <td>(0, 0, 28, 28)</td>\n",
       "      <td>(28, 28, 1)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24251.png</th>\n",
       "      <td>None</td>\n",
       "      <td>/Users/rwood/LwM/mapreader/MapReader/worked_ex...</td>\n",
       "      <td>(0, 0, 28, 28)</td>\n",
       "      <td>(28, 28, 1)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20989.png</th>\n",
       "      <td>None</td>\n",
       "      <td>/Users/rwood/LwM/mapreader/MapReader/worked_ex...</td>\n",
       "      <td>(0, 0, 28, 28)</td>\n",
       "      <td>(28, 28, 1)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          parent_id                                         image_path  \\\n",
       "image_id                                                                 \n",
       "49081.png      None  /Users/rwood/LwM/mapreader/MapReader/worked_ex...   \n",
       "51816.png      None  /Users/rwood/LwM/mapreader/MapReader/worked_ex...   \n",
       "39566.png      None  /Users/rwood/LwM/mapreader/MapReader/worked_ex...   \n",
       "24251.png      None  /Users/rwood/LwM/mapreader/MapReader/worked_ex...   \n",
       "20989.png      None  /Users/rwood/LwM/mapreader/MapReader/worked_ex...   \n",
       "\n",
       "             pixel_bounds        shape  \n",
       "image_id                                \n",
       "49081.png  (0, 0, 28, 28)  (28, 28, 1)  \n",
       "51816.png  (0, 0, 28, 28)  (28, 28, 1)  \n",
       "39566.png  (0, 0, 28, 28)  (28, 28, 1)  \n",
       "24251.png  (0, 0, 28, 28)  (28, 28, 1)  \n",
       "20989.png  (0, 0, 28, 28)  (28, 28, 1)  "
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "patch_df[\"pixel_bounds\"] = patch_df[\"shape\"].apply(lambda x: (0, 0, x[1], x[0]))\n",
    "patch_df.head()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Annotate\n",
    "https://mapreader.readthedocs.io/en/latest/User-guide/Annotate.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "from mapreader import Annotator"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "annotator = Annotator(\n",
    "    patch_df=patch_df,\n",
    "    parent_df=parent_df,\n",
    "    labels=[\"1\", \"3\"],\n",
    "    annotations_dir=\"./annotations_mnist\",\n",
    "    username=\"kasra\",\n",
    "    task_name=\"mnist\",\n",
    "    show_context=False,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d0ab192abbcb423b8ac5982f7f4e21fc",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(Button(button_style='info', description='1', layout=Layout(flex='1 1 0%', width='auto'), style=…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "0736670cf1ef40a8b358b16411f8d3e7",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "VBox(children=(HBox(children=(Button(description='« previous', layout=Layout(flex='1 1 0%', width='auto'), sty…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "fbb91c7b0ded45c4a1f9dcc731229010",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output(layout=Layout(align_items='center', display='flex', flex_flow='column'))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "annotator.annotate(resize_to=400)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Classify - Train\n",
    "\n",
    "https://mapreader.readthedocs.io/en/latest/User-guide/Classify.html"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Read annotations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from mapreader import AnnotationsLoader"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] Reading \"./annotations_mnist/mnist_#kasra#.csv\"\n",
      "[INFO] Number of annotations:   164\n",
      "\n",
      "[INFO] Number of instances of each label (from column \"label\"):\n",
      "    - 2:  87\n",
      "    - 1:  77\n",
      "\n"
     ]
    }
   ],
   "source": [
    "annotated_images = AnnotationsLoader()\n",
    "\n",
    "annotated_images.load(\"./annotations_mnist/mnist_#kasra#.csv\", images_dir=\"./small_mnist/\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 800x600 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# show sample images for one label (label_to_show)\n",
    "annotated_images.show_sample(label_to_show=\"1\", num_samples=6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# show an image based on its index\n",
    "annotated_images.show_patch(patch_id=\"20989.png\")"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Prepare datasets and dataloaders"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] Number of annotations in each set:\n",
      "    - train:   114\n",
      "    - val:   33\n",
      "    - test:   17\n"
     ]
    }
   ],
   "source": [
    "annotated_images.create_datasets(frac_train=0.7, frac_val=0.2, frac_test=0.1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] Using default sampler.\n"
     ]
    }
   ],
   "source": [
    "dataloaders = annotated_images.create_dataloaders(batch_size=8, sampler=\"default\")"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Set up `ClassifierContainer`"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Load a (pretrained) PyTorch model and combine with dataloaders"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "from mapreader import ClassifierContainer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] Device is set to cpu\n",
      "[INFO] Initializing model.\n",
      "[INFO] Loaded \"train\" with 114 items.\n",
      "[INFO] Loaded \"val\" with 33 items.\n",
      "[INFO] Loaded \"test\" with 17 items.\n"
     ]
    }
   ],
   "source": [
    "my_classifier = ClassifierContainer(model=\"resnet18\", \n",
    "                                    labels_map={0: \"3\", 1: \"1\"},\n",
    "                                    dataloaders=dataloaders\n",
    "                                    )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "===================================================================================================================\n",
      "Layer (type:depth-idx)                   Output Shape              Output Shape              Param #\n",
      "===================================================================================================================\n",
      "ResNet                                   [8, 2]                    [8, 2]                    --\n",
      "├─Conv2d: 1-1                            [8, 64, 112, 112]         [8, 64, 112, 112]         9,408\n",
      "├─BatchNorm2d: 1-2                       [8, 64, 112, 112]         [8, 64, 112, 112]         128\n",
      "├─ReLU: 1-3                              [8, 64, 112, 112]         [8, 64, 112, 112]         --\n",
      "├─MaxPool2d: 1-4                         [8, 64, 56, 56]           [8, 64, 56, 56]           --\n",
      "├─Sequential: 1-5                        [8, 64, 56, 56]           [8, 64, 56, 56]           --\n",
      "│    └─BasicBlock: 2-1                   [8, 64, 56, 56]           [8, 64, 56, 56]           --\n",
      "│    │    └─Conv2d: 3-1                  [8, 64, 56, 56]           [8, 64, 56, 56]           36,864\n",
      "│    │    └─BatchNorm2d: 3-2             [8, 64, 56, 56]           [8, 64, 56, 56]           128\n",
      "│    │    └─ReLU: 3-3                    [8, 64, 56, 56]           [8, 64, 56, 56]           --\n",
      "│    │    └─Conv2d: 3-4                  [8, 64, 56, 56]           [8, 64, 56, 56]           36,864\n",
      "│    │    └─BatchNorm2d: 3-5             [8, 64, 56, 56]           [8, 64, 56, 56]           128\n",
      "│    │    └─ReLU: 3-6                    [8, 64, 56, 56]           [8, 64, 56, 56]           --\n",
      "│    └─BasicBlock: 2-2                   [8, 64, 56, 56]           [8, 64, 56, 56]           --\n",
      "│    │    └─Conv2d: 3-7                  [8, 64, 56, 56]           [8, 64, 56, 56]           36,864\n",
      "│    │    └─BatchNorm2d: 3-8             [8, 64, 56, 56]           [8, 64, 56, 56]           128\n",
      "│    │    └─ReLU: 3-9                    [8, 64, 56, 56]           [8, 64, 56, 56]           --\n",
      "│    │    └─Conv2d: 3-10                 [8, 64, 56, 56]           [8, 64, 56, 56]           36,864\n",
      "│    │    └─BatchNorm2d: 3-11            [8, 64, 56, 56]           [8, 64, 56, 56]           128\n",
      "│    │    └─ReLU: 3-12                   [8, 64, 56, 56]           [8, 64, 56, 56]           --\n",
      "├─Sequential: 1-6                        [8, 128, 28, 28]          [8, 128, 28, 28]          --\n",
      "│    └─BasicBlock: 2-3                   [8, 128, 28, 28]          [8, 128, 28, 28]          --\n",
      "│    │    └─Conv2d: 3-13                 [8, 128, 28, 28]          [8, 128, 28, 28]          73,728\n",
      "│    │    └─BatchNorm2d: 3-14            [8, 128, 28, 28]          [8, 128, 28, 28]          256\n",
      "│    │    └─ReLU: 3-15                   [8, 128, 28, 28]          [8, 128, 28, 28]          --\n",
      "│    │    └─Conv2d: 3-16                 [8, 128, 28, 28]          [8, 128, 28, 28]          147,456\n",
      "│    │    └─BatchNorm2d: 3-17            [8, 128, 28, 28]          [8, 128, 28, 28]          256\n",
      "│    │    └─Sequential: 3-18             [8, 128, 28, 28]          [8, 128, 28, 28]          8,448\n",
      "│    │    └─ReLU: 3-19                   [8, 128, 28, 28]          [8, 128, 28, 28]          --\n",
      "│    └─BasicBlock: 2-4                   [8, 128, 28, 28]          [8, 128, 28, 28]          --\n",
      "│    │    └─Conv2d: 3-20                 [8, 128, 28, 28]          [8, 128, 28, 28]          147,456\n",
      "│    │    └─BatchNorm2d: 3-21            [8, 128, 28, 28]          [8, 128, 28, 28]          256\n",
      "│    │    └─ReLU: 3-22                   [8, 128, 28, 28]          [8, 128, 28, 28]          --\n",
      "│    │    └─Conv2d: 3-23                 [8, 128, 28, 28]          [8, 128, 28, 28]          147,456\n",
      "│    │    └─BatchNorm2d: 3-24            [8, 128, 28, 28]          [8, 128, 28, 28]          256\n",
      "│    │    └─ReLU: 3-25                   [8, 128, 28, 28]          [8, 128, 28, 28]          --\n",
      "├─Sequential: 1-7                        [8, 256, 14, 14]          [8, 256, 14, 14]          --\n",
      "│    └─BasicBlock: 2-5                   [8, 256, 14, 14]          [8, 256, 14, 14]          --\n",
      "│    │    └─Conv2d: 3-26                 [8, 256, 14, 14]          [8, 256, 14, 14]          294,912\n",
      "│    │    └─BatchNorm2d: 3-27            [8, 256, 14, 14]          [8, 256, 14, 14]          512\n",
      "│    │    └─ReLU: 3-28                   [8, 256, 14, 14]          [8, 256, 14, 14]          --\n",
      "│    │    └─Conv2d: 3-29                 [8, 256, 14, 14]          [8, 256, 14, 14]          589,824\n",
      "│    │    └─BatchNorm2d: 3-30            [8, 256, 14, 14]          [8, 256, 14, 14]          512\n",
      "│    │    └─Sequential: 3-31             [8, 256, 14, 14]          [8, 256, 14, 14]          33,280\n",
      "│    │    └─ReLU: 3-32                   [8, 256, 14, 14]          [8, 256, 14, 14]          --\n",
      "│    └─BasicBlock: 2-6                   [8, 256, 14, 14]          [8, 256, 14, 14]          --\n",
      "│    │    └─Conv2d: 3-33                 [8, 256, 14, 14]          [8, 256, 14, 14]          589,824\n",
      "│    │    └─BatchNorm2d: 3-34            [8, 256, 14, 14]          [8, 256, 14, 14]          512\n",
      "│    │    └─ReLU: 3-35                   [8, 256, 14, 14]          [8, 256, 14, 14]          --\n",
      "│    │    └─Conv2d: 3-36                 [8, 256, 14, 14]          [8, 256, 14, 14]          589,824\n",
      "│    │    └─BatchNorm2d: 3-37            [8, 256, 14, 14]          [8, 256, 14, 14]          512\n",
      "│    │    └─ReLU: 3-38                   [8, 256, 14, 14]          [8, 256, 14, 14]          --\n",
      "├─Sequential: 1-8                        [8, 512, 7, 7]            [8, 512, 7, 7]            --\n",
      "│    └─BasicBlock: 2-7                   [8, 512, 7, 7]            [8, 512, 7, 7]            --\n",
      "│    │    └─Conv2d: 3-39                 [8, 512, 7, 7]            [8, 512, 7, 7]            1,179,648\n",
      "│    │    └─BatchNorm2d: 3-40            [8, 512, 7, 7]            [8, 512, 7, 7]            1,024\n",
      "│    │    └─ReLU: 3-41                   [8, 512, 7, 7]            [8, 512, 7, 7]            --\n",
      "│    │    └─Conv2d: 3-42                 [8, 512, 7, 7]            [8, 512, 7, 7]            2,359,296\n",
      "│    │    └─BatchNorm2d: 3-43            [8, 512, 7, 7]            [8, 512, 7, 7]            1,024\n",
      "│    │    └─Sequential: 3-44             [8, 512, 7, 7]            [8, 512, 7, 7]            132,096\n",
      "│    │    └─ReLU: 3-45                   [8, 512, 7, 7]            [8, 512, 7, 7]            --\n",
      "│    └─BasicBlock: 2-8                   [8, 512, 7, 7]            [8, 512, 7, 7]            --\n",
      "│    │    └─Conv2d: 3-46                 [8, 512, 7, 7]            [8, 512, 7, 7]            2,359,296\n",
      "│    │    └─BatchNorm2d: 3-47            [8, 512, 7, 7]            [8, 512, 7, 7]            1,024\n",
      "│    │    └─ReLU: 3-48                   [8, 512, 7, 7]            [8, 512, 7, 7]            --\n",
      "│    │    └─Conv2d: 3-49                 [8, 512, 7, 7]            [8, 512, 7, 7]            2,359,296\n",
      "│    │    └─BatchNorm2d: 3-50            [8, 512, 7, 7]            [8, 512, 7, 7]            1,024\n",
      "│    │    └─ReLU: 3-51                   [8, 512, 7, 7]            [8, 512, 7, 7]            --\n",
      "├─AdaptiveAvgPool2d: 1-9                 [8, 512, 1, 1]            [8, 512, 1, 1]            --\n",
      "├─Linear: 1-10                           [8, 2]                    [8, 2]                    1,026\n",
      "===================================================================================================================\n",
      "Total params: 11,177,538\n",
      "Trainable params: 11,177,538\n",
      "Non-trainable params: 0\n",
      "Total mult-adds (G): 14.51\n",
      "===================================================================================================================\n",
      "Input size (MB): 4.82\n",
      "Forward/backward pass size (MB): 317.92\n",
      "Params size (MB): 44.71\n",
      "Estimated Total Size (MB): 367.44\n",
      "===================================================================================================================\n"
     ]
    }
   ],
   "source": [
    "my_classifier.model_summary()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Set up criterion, optimizer and scheduler"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] Using \"CrossEntropyLoss()\" as criterion.\n"
     ]
    }
   ],
   "source": [
    "my_classifier.add_criterion(\"cross-entropy\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "params_to_optimize = my_classifier.generate_layerwise_lrs(\n",
    "    min_lr=1e-4, max_lr=1e-3, spacing=\"geomspace\"\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "my_classifier.initialize_optimizer(params2optimize=params_to_optimize)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "my_classifier.initialize_scheduler()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Train/fine-tune a model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] Each step will pass: ['train', 'val'].\n",
      "\u001b[92m2024-02-22 09:51:10\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 1/15 --      8/114 (  7.0% ) -- Loss: 0.846\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[92m2024-02-22 09:51:12\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 1/15 --     48/114 ( 42.1% ) -- Loss: 0.055\u001b[0m\n",
      "\u001b[92m2024-02-22 09:51:14\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 1/15 --     88/114 ( 77.2% ) -- Loss: 0.007\u001b[0m\n",
      "\u001b[92m2024-02-22 09:51:15\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 1/15 -- Loss: 0.277; F_macro: 92.06; R_macro: 92.30\u001b[0m\n",
      "\u001b[92m2024-02-22 09:51:15\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;31mval      -- 1/15 --       8/33 ( 24.2% ) -- Loss: 3.853\u001b[0m\n",
      "\u001b[92m2024-02-22 09:51:15\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;31mval      -- 1/15 -- Loss: 3.657; F_macro: 35.29; R_macro: 50.00\n",
      "\u001b[0m\n",
      "\u001b[92m2024-02-22 09:51:16\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 2/15 --      8/114 (  7.0% ) -- Loss: 0.002\u001b[0m\n",
      "\u001b[92m2024-02-22 09:51:18\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 2/15 --     48/114 ( 42.1% ) -- Loss: 0.906\u001b[0m\n",
      "\u001b[92m2024-02-22 09:51:19\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 2/15 --     88/114 ( 77.2% ) -- Loss: 0.014\u001b[0m\n",
      "\u001b[92m2024-02-22 09:51:21\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 2/15 -- Loss: 0.128; F_macro: 97.37; R_macro: 97.37\u001b[0m\n",
      "\u001b[92m2024-02-22 09:51:21\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;31mval      -- 2/15 --       8/33 ( 24.2% ) -- Loss: 0.141\u001b[0m\n",
      "\u001b[92m2024-02-22 09:51:21\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;31mval      -- 2/15 -- Loss: 0.060; F_macro: 96.92; R_macro: 96.67\n",
      "\u001b[0m\n",
      "\u001b[1;90m[INFO] Checkpoint file saved to \"./tmp_checkpoints/tmp_7467067119_checkpoint.pkl\".\u001b[0m\n",
      "\u001b[92m2024-02-22 09:51:22\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 3/15 --      8/114 (  7.0% ) -- Loss: 0.368\u001b[0m\n",
      "\u001b[92m2024-02-22 09:51:24\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 3/15 --     48/114 ( 42.1% ) -- Loss: 0.020\u001b[0m\n",
      "\u001b[92m2024-02-22 09:51:26\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 3/15 --     88/114 ( 77.2% ) -- Loss: 0.004\u001b[0m\n",
      "\u001b[92m2024-02-22 09:51:27\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 3/15 -- Loss: 0.490; F_macro: 85.95; R_macro: 86.14\u001b[0m\n",
      "\u001b[92m2024-02-22 09:51:27\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;31mval      -- 3/15 --       8/33 ( 24.2% ) -- Loss: 0.000\u001b[0m\n",
      "\u001b[92m2024-02-22 09:51:28\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;31mval      -- 3/15 -- Loss: 0.000; F_macro: 100.00; R_macro: 100.00\n",
      "\u001b[0m\n",
      "\u001b[92m2024-02-22 09:51:28\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 4/15 --      8/114 (  7.0% ) -- Loss: 0.257\u001b[0m\n",
      "\u001b[92m2024-02-22 09:51:30\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 4/15 --     48/114 ( 42.1% ) -- Loss: 0.102\u001b[0m\n",
      "\u001b[92m2024-02-22 09:51:32\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 4/15 --     88/114 ( 77.2% ) -- Loss: 0.039\u001b[0m\n",
      "\u001b[92m2024-02-22 09:51:33\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 4/15 -- Loss: 0.155; F_macro: 98.24; R_macro: 98.36\u001b[0m\n",
      "\u001b[92m2024-02-22 09:51:33\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;31mval      -- 4/15 --       8/33 ( 24.2% ) -- Loss: 0.000\u001b[0m\n",
      "\u001b[92m2024-02-22 09:51:34\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;31mval      -- 4/15 -- Loss: 0.002; F_macro: 100.00; R_macro: 100.00\n",
      "\u001b[0m\n",
      "\u001b[1;90m[INFO] Checkpoint file saved to \"./tmp_checkpoints/tmp_7467067119_checkpoint.pkl\".\u001b[0m\n",
      "\u001b[92m2024-02-22 09:51:34\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 5/15 --      8/114 (  7.0% ) -- Loss: 0.023\u001b[0m\n",
      "\u001b[92m2024-02-22 09:51:36\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 5/15 --     48/114 ( 42.1% ) -- Loss: 0.068\u001b[0m\n",
      "\u001b[92m2024-02-22 09:51:38\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 5/15 --     88/114 ( 77.2% ) -- Loss: 0.162\u001b[0m\n",
      "\u001b[92m2024-02-22 09:51:40\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 5/15 -- Loss: 0.101; F_macro: 96.45; R_macro: 96.23\u001b[0m\n",
      "\u001b[92m2024-02-22 09:51:40\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;31mval      -- 5/15 --       8/33 ( 24.2% ) -- Loss: 0.020\u001b[0m\n",
      "\u001b[92m2024-02-22 09:51:40\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;31mval      -- 5/15 -- Loss: 0.009; F_macro: 100.00; R_macro: 100.00\n",
      "\u001b[0m\n",
      "\u001b[92m2024-02-22 09:51:41\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 6/15 --      8/114 (  7.0% ) -- Loss: 0.004\u001b[0m\n",
      "\u001b[92m2024-02-22 09:51:42\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 6/15 --     48/114 ( 42.1% ) -- Loss: 0.051\u001b[0m\n",
      "\u001b[92m2024-02-22 09:51:44\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 6/15 --     88/114 ( 77.2% ) -- Loss: 0.007\u001b[0m\n",
      "\u001b[92m2024-02-22 09:51:46\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 6/15 -- Loss: 0.054; F_macro: 98.23; R_macro: 98.23\u001b[0m\n",
      "\u001b[92m2024-02-22 09:51:46\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;31mval      -- 6/15 --       8/33 ( 24.2% ) -- Loss: 0.001\u001b[0m\n",
      "\u001b[92m2024-02-22 09:51:46\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;31mval      -- 6/15 -- Loss: 0.001; F_macro: 100.00; R_macro: 100.00\n",
      "\u001b[0m\n",
      "\u001b[1;90m[INFO] Checkpoint file saved to \"./tmp_checkpoints/tmp_7467067119_checkpoint.pkl\".\u001b[0m\n",
      "\u001b[92m2024-02-22 09:51:47\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 7/15 --      8/114 (  7.0% ) -- Loss: 0.052\u001b[0m\n",
      "\u001b[92m2024-02-22 09:51:48\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 7/15 --     48/114 ( 42.1% ) -- Loss: 0.008\u001b[0m\n",
      "\u001b[92m2024-02-22 09:51:50\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 7/15 --     88/114 ( 77.2% ) -- Loss: 0.003\u001b[0m\n",
      "\u001b[92m2024-02-22 09:51:52\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 7/15 -- Loss: 0.020; F_macro: 100.00; R_macro: 100.00\u001b[0m\n",
      "\u001b[92m2024-02-22 09:51:52\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;31mval      -- 7/15 --       8/33 ( 24.2% ) -- Loss: 0.000\u001b[0m\n",
      "\u001b[92m2024-02-22 09:51:52\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;31mval      -- 7/15 -- Loss: 0.001; F_macro: 100.00; R_macro: 100.00\n",
      "\u001b[0m\n",
      "\u001b[92m2024-02-22 09:51:53\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 8/15 --      8/114 (  7.0% ) -- Loss: 0.004\u001b[0m\n",
      "\u001b[92m2024-02-22 09:51:54\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 8/15 --     48/114 ( 42.1% ) -- Loss: 1.239\u001b[0m\n",
      "\u001b[92m2024-02-22 09:51:56\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 8/15 --     88/114 ( 77.2% ) -- Loss: 0.021\u001b[0m\n",
      "\u001b[92m2024-02-22 09:51:58\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 8/15 -- Loss: 0.106; F_macro: 95.46; R_macro: 96.43\u001b[0m\n",
      "\u001b[92m2024-02-22 09:51:58\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;31mval      -- 8/15 --       8/33 ( 24.2% ) -- Loss: 0.064\u001b[0m\n",
      "\u001b[92m2024-02-22 09:51:58\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;31mval      -- 8/15 -- Loss: 0.099; F_macro: 93.80; R_macro: 93.33\n",
      "\u001b[0m\n",
      "\u001b[1;90m[INFO] Checkpoint file saved to \"./tmp_checkpoints/tmp_7467067119_checkpoint.pkl\".\u001b[0m\n",
      "\u001b[92m2024-02-22 09:51:59\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 9/15 --      8/114 (  7.0% ) -- Loss: 0.007\u001b[0m\n",
      "\u001b[92m2024-02-22 09:52:01\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 9/15 --     48/114 ( 42.1% ) -- Loss: 0.017\u001b[0m\n",
      "\u001b[92m2024-02-22 09:52:03\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 9/15 --     88/114 ( 77.2% ) -- Loss: 0.043\u001b[0m\n",
      "\u001b[92m2024-02-22 09:52:04\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 9/15 -- Loss: 0.037; F_macro: 99.12; R_macro: 99.11\u001b[0m\n",
      "\u001b[92m2024-02-22 09:52:04\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;31mval      -- 9/15 --       8/33 ( 24.2% ) -- Loss: 0.003\u001b[0m\n",
      "\u001b[92m2024-02-22 09:52:05\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;31mval      -- 9/15 -- Loss: 0.007; F_macro: 100.00; R_macro: 100.00\n",
      "\u001b[0m\n",
      "\u001b[92m2024-02-22 09:52:05\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 10/15 --      8/114 (  7.0% ) -- Loss: 0.001\u001b[0m\n",
      "\u001b[92m2024-02-22 09:52:07\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 10/15 --     48/114 ( 42.1% ) -- Loss: 0.011\u001b[0m\n",
      "\u001b[92m2024-02-22 09:52:09\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 10/15 --     88/114 ( 77.2% ) -- Loss: 0.248\u001b[0m\n",
      "\u001b[92m2024-02-22 09:52:10\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 10/15 -- Loss: 0.069; F_macro: 98.23; R_macro: 98.23\u001b[0m\n",
      "\u001b[92m2024-02-22 09:52:10\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;31mval      -- 10/15 --       8/33 ( 24.2% ) -- Loss: 0.001\u001b[0m\n",
      "\u001b[92m2024-02-22 09:52:11\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;31mval      -- 10/15 -- Loss: 0.002; F_macro: 100.00; R_macro: 100.00\n",
      "\u001b[0m\n",
      "\u001b[1;90m[INFO] Checkpoint file saved to \"./tmp_checkpoints/tmp_7467067119_checkpoint.pkl\".\u001b[0m\n",
      "\u001b[92m2024-02-22 09:52:11\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 11/15 --      8/114 (  7.0% ) -- Loss: 0.011\u001b[0m\n",
      "\u001b[92m2024-02-22 09:52:14\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 11/15 --     48/114 ( 42.1% ) -- Loss: 0.005\u001b[0m\n",
      "\u001b[92m2024-02-22 09:52:15\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 11/15 --     88/114 ( 77.2% ) -- Loss: 0.002\u001b[0m\n",
      "\u001b[92m2024-02-22 09:52:17\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 11/15 -- Loss: 0.142; F_macro: 95.61; R_macro: 95.58\u001b[0m\n",
      "\u001b[92m2024-02-22 09:52:17\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;31mval      -- 11/15 --       8/33 ( 24.2% ) -- Loss: 0.000\u001b[0m\n",
      "\u001b[92m2024-02-22 09:52:17\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;31mval      -- 11/15 -- Loss: 0.001; F_macro: 100.00; R_macro: 100.00\n",
      "\u001b[0m\n",
      "\u001b[92m2024-02-22 09:52:18\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 12/15 --      8/114 (  7.0% ) -- Loss: 0.003\u001b[0m\n",
      "\u001b[92m2024-02-22 09:52:20\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 12/15 --     48/114 ( 42.1% ) -- Loss: 0.002\u001b[0m\n",
      "\u001b[92m2024-02-22 09:52:21\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 12/15 --     88/114 ( 77.2% ) -- Loss: 0.038\u001b[0m\n",
      "\u001b[92m2024-02-22 09:52:23\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 12/15 -- Loss: 0.015; F_macro: 100.00; R_macro: 100.00\u001b[0m\n",
      "\u001b[92m2024-02-22 09:52:23\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;31mval      -- 12/15 --       8/33 ( 24.2% ) -- Loss: 0.001\u001b[0m\n",
      "\u001b[92m2024-02-22 09:52:24\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;31mval      -- 12/15 -- Loss: 0.003; F_macro: 100.00; R_macro: 100.00\n",
      "\u001b[0m\n",
      "\u001b[1;90m[INFO] Checkpoint file saved to \"./tmp_checkpoints/tmp_7467067119_checkpoint.pkl\".\u001b[0m\n",
      "\u001b[92m2024-02-22 09:52:24\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 13/15 --      8/114 (  7.0% ) -- Loss: 0.009\u001b[0m\n",
      "\u001b[92m2024-02-22 09:52:26\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 13/15 --     48/114 ( 42.1% ) -- Loss: 0.007\u001b[0m\n",
      "\u001b[92m2024-02-22 09:52:28\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 13/15 --     88/114 ( 77.2% ) -- Loss: 0.069\u001b[0m\n",
      "\u001b[92m2024-02-22 09:52:30\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 13/15 -- Loss: 0.036; F_macro: 98.24; R_macro: 98.24\u001b[0m\n",
      "\u001b[92m2024-02-22 09:52:30\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;31mval      -- 13/15 --       8/33 ( 24.2% ) -- Loss: 0.001\u001b[0m\n",
      "\u001b[92m2024-02-22 09:52:30\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;31mval      -- 13/15 -- Loss: 0.002; F_macro: 100.00; R_macro: 100.00\n",
      "\u001b[0m\n",
      "\u001b[92m2024-02-22 09:52:31\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 14/15 --      8/114 (  7.0% ) -- Loss: 0.010\u001b[0m\n",
      "\u001b[92m2024-02-22 09:52:33\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 14/15 --     48/114 ( 42.1% ) -- Loss: 0.002\u001b[0m\n",
      "\u001b[92m2024-02-22 09:52:35\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 14/15 --     88/114 ( 77.2% ) -- Loss: 0.022\u001b[0m\n",
      "\u001b[92m2024-02-22 09:52:36\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 14/15 -- Loss: 0.027; F_macro: 99.12; R_macro: 99.12\u001b[0m\n",
      "\u001b[92m2024-02-22 09:52:36\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;31mval      -- 14/15 --       8/33 ( 24.2% ) -- Loss: 0.001\u001b[0m\n",
      "\u001b[92m2024-02-22 09:52:37\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;31mval      -- 14/15 -- Loss: 0.007; F_macro: 100.00; R_macro: 100.00\n",
      "\u001b[0m\n",
      "\u001b[1;90m[INFO] Checkpoint file saved to \"./tmp_checkpoints/tmp_7467067119_checkpoint.pkl\".\u001b[0m\n",
      "\u001b[92m2024-02-22 09:52:37\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 15/15 --      8/114 (  7.0% ) -- Loss: 0.001\u001b[0m\n",
      "\u001b[92m2024-02-22 09:52:39\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 15/15 --     48/114 ( 42.1% ) -- Loss: 0.027\u001b[0m\n",
      "\u001b[92m2024-02-22 09:52:41\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 15/15 --     88/114 ( 77.2% ) -- Loss: 0.020\u001b[0m\n",
      "\u001b[92m2024-02-22 09:52:42\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mtrain    -- 15/15 -- Loss: 0.065; F_macro: 98.24; R_macro: 98.24\u001b[0m\n",
      "\u001b[92m2024-02-22 09:52:42\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;31mval      -- 15/15 --       8/33 ( 24.2% ) -- Loss: 0.001\u001b[0m\n",
      "\u001b[92m2024-02-22 09:52:43\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;31mval      -- 15/15 -- Loss: 0.001; F_macro: 100.00; R_macro: 100.00\n",
      "\u001b[0m\n",
      "[INFO] Total time: 1m 34s\n",
      "[INFO] Model at epoch 3 has least valid loss (0.0001) so will be saved.\n",
      "[INFO] Path: /Users/rwood/LwM/mapreader/MapReader/worked_examples/non-geospatial/classification_mnist/models_mnist/checkpoint_3.pkl\n"
     ]
    }
   ],
   "source": [
    "my_classifier.train(\n",
    "    num_epochs=15,\n",
    "    save_model_dir=\"./models_mnist\",\n",
    "    tensorboard_path=\"tboard_mnist\",\n",
    "    tmp_file_save_freq=2,\n",
    "    remove_after_load=False,\n",
    "    print_info_batch_freq=5,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['epoch_loss_train',\n",
       " 'epoch_prec_micro_train',\n",
       " 'epoch_recall_micro_train',\n",
       " 'epoch_fscore_micro_train',\n",
       " 'epoch_supp_micro_train',\n",
       " 'epoch_rocauc_micro_train',\n",
       " 'epoch_prec_macro_train',\n",
       " 'epoch_recall_macro_train',\n",
       " 'epoch_fscore_macro_train',\n",
       " 'epoch_supp_macro_train',\n",
       " 'epoch_rocauc_macro_train',\n",
       " 'epoch_prec_weighted_train',\n",
       " 'epoch_recall_weighted_train',\n",
       " 'epoch_fscore_weighted_train',\n",
       " 'epoch_supp_weighted_train',\n",
       " 'epoch_rocauc_weighted_train',\n",
       " 'epoch_prec_0_train',\n",
       " 'epoch_recall_0_train',\n",
       " 'epoch_fscore_0_train',\n",
       " 'epoch_supp_0_train',\n",
       " 'epoch_prec_1_train',\n",
       " 'epoch_recall_1_train',\n",
       " 'epoch_fscore_1_train',\n",
       " 'epoch_supp_1_train',\n",
       " 'epoch_loss_val',\n",
       " 'epoch_prec_micro_val',\n",
       " 'epoch_recall_micro_val',\n",
       " 'epoch_fscore_micro_val',\n",
       " 'epoch_supp_micro_val',\n",
       " 'epoch_rocauc_micro_val',\n",
       " 'epoch_prec_macro_val',\n",
       " 'epoch_recall_macro_val',\n",
       " 'epoch_fscore_macro_val',\n",
       " 'epoch_supp_macro_val',\n",
       " 'epoch_rocauc_macro_val',\n",
       " 'epoch_prec_weighted_val',\n",
       " 'epoch_recall_weighted_val',\n",
       " 'epoch_fscore_weighted_val',\n",
       " 'epoch_supp_weighted_val',\n",
       " 'epoch_rocauc_weighted_val',\n",
       " 'epoch_prec_0_val',\n",
       " 'epoch_recall_0_val',\n",
       " 'epoch_fscore_0_val',\n",
       " 'epoch_supp_0_val',\n",
       " 'epoch_prec_1_val',\n",
       " 'epoch_recall_1_val',\n",
       " 'epoch_fscore_1_val',\n",
       " 'epoch_supp_1_val']"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(my_classifier.metrics.keys())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "my_classifier.plot_metric(\n",
    "    y_axis=[\"epoch_loss_train\", \"epoch_loss_val\"],\n",
    "    y_label=\"Loss\",\n",
    "    legends=[\"Train\", \"Valid\"],\n",
    "    colors=[\"k\", \"tab:red\"],\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "my_classifier.plot_metric(\n",
    "    y_axis=[\"epoch_rocauc_macro_train\", \"epoch_rocauc_macro_val\"],\n",
    "    y_label=\"ROC AUC\",\n",
    "    legends=[\"Train\", \"Valid\"],\n",
    "    colors=[\"k\", \"tab:red\"],\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "my_classifier.plot_metric(\n",
    "    y_axis=[\n",
    "        \"epoch_fscore_macro_train\",\n",
    "        \"epoch_fscore_macro_val\",\n",
    "        \"epoch_fscore_0_val\",\n",
    "        \"epoch_fscore_1_val\",\n",
    "    ],\n",
    "    y_label=\"F-score\",\n",
    "    legends=[\n",
    "        \"Train\",\n",
    "        \"Valid\",\n",
    "        \"Valid (label: 0)\",\n",
    "        \"Valid (label: 1)\",\n",
    "    ],\n",
    "    colors=[\"k\", \"tab:red\", \"tab:red\", \"tab:red\"],\n",
    "    styles=[\"-\", \"-\", \"--\", \":\"],\n",
    "    markers=[\"o\", \"o\", \"\", \"\"],\n",
    "    plt_yrange=[0, 100],\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "my_classifier.plot_metric(\n",
    "    y_axis=[\n",
    "        \"epoch_recall_macro_train\",\n",
    "        \"epoch_recall_macro_val\",\n",
    "        \"epoch_recall_0_val\",\n",
    "        \"epoch_recall_1_val\",\n",
    "    ],\n",
    "    y_label=\"Recall\",\n",
    "    legends=[\n",
    "        \"Train\",\n",
    "        \"Valid\",\n",
    "        \"Valid (label: 0)\",\n",
    "        \"Valid (label: 1)\",\n",
    "    ],\n",
    "    colors=[\"k\", \"tab:red\", \"tab:red\", \"tab:red\"],\n",
    "    styles=[\"-\", \"-\", \"--\", \":\"],\n",
    "    markers=[\"o\", \"o\", \"\", \"\"],\n",
    "    plt_yrange=[0, 100],\n",
    ")"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Classify - Infer\n",
    "\n",
    "https://mapreader.readthedocs.io/en/latest/User-guide/Classify.html"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create dataset with all mnist data and add to ``ClassifierContainer``"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "from mapreader import PatchDataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = PatchDataset(patch_df, transform=\"val\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "my_classifier.load_dataset(data, set_name=\"all_mnist\")"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Infer labels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] Each step will pass: ['all_mnist'].\n",
      "\u001b[92m2024-02-22 09:56:58\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mall_mnist -- 16/16 --     16/200 (  8.0% ) -- \u001b[0m\n",
      "\u001b[92m2024-02-22 09:57:02\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mall_mnist -- 16/16 --     96/200 ( 48.0% ) -- \u001b[0m\n",
      "\u001b[92m2024-02-22 09:57:07\u001b[0m \u001b[95m599-JY5FK6\u001b[0m \u001b[1m\u001b[90m[INFO]\u001b[0m \u001b[2;32mall_mnist -- 16/16 --    176/200 ( 88.0% ) -- \u001b[0m\n",
      "[INFO] Total time: 0m 11s\n"
     ]
    }
   ],
   "source": [
    "my_classifier.inference(\"all_mnist\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x1500 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "my_classifier.show_inference_sample_results(\n",
    "    label=\"3\", set_name=\"all_mnist\", min_conf=99\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "mr_dev",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
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