model_explanation_shape.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "id": "1a91b813",
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    },
    "ExecuteTime": {
     "end_time": "2024-04-16T01:49:19.988676Z",
     "start_time": "2024-04-16T01:49:19.975921Z"
    }
   },
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2"
   ],
   "outputs": [],
   "execution_count": 1
  },
  {
   "cell_type": "code",
   "id": "c7f4188d",
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    },
    "ExecuteTime": {
     "end_time": "2024-04-16T01:49:36.963873Z",
     "start_time": "2024-04-16T01:49:21.659071Z"
    }
   },
   "source": [
    "from gnninterpreter import *"
   ],
   "outputs": [],
   "execution_count": 2
  },
  {
   "cell_type": "code",
   "id": "2ab76fb3",
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    },
    "ExecuteTime": {
     "end_time": "2024-04-16T01:49:36.986147Z",
     "start_time": "2024-04-16T01:49:36.965160Z"
    }
   },
   "source": "import torch",
   "outputs": [],
   "execution_count": 3
  },
  {
   "cell_type": "markdown",
   "id": "395a07f1",
   "metadata": {},
   "source": [
    "# Shape"
   ]
  },
  {
   "cell_type": "code",
   "id": "52747602",
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    },
    "ExecuteTime": {
     "end_time": "2024-04-16T01:49:37.688334Z",
     "start_time": "2024-04-16T01:49:36.986879Z"
    }
   },
   "source": [
    "dataset = ShapeDataset(seed=12345)"
   ],
   "outputs": [],
   "execution_count": 4
  },
  {
   "cell_type": "code",
   "id": "4c1617a4-666d-43de-8f0e-c5301b74375f",
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    },
    "ExecuteTime": {
     "end_time": "2024-04-16T01:49:38.947478Z",
     "start_time": "2024-04-16T01:49:38.905330Z"
    }
   },
   "source": [
    "model = GCNClassifier(node_features=len(dataset.NODE_CLS),\n",
    "                      num_classes=len(dataset.GRAPH_CLS),\n",
    "                      hidden_channels=64,\n",
    "                      num_layers=4)\n",
    "model.load_state_dict(torch.load('ckpts/shape.pt'))"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<All keys matched successfully>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 6
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-04-16T01:50:03.530005Z",
     "start_time": "2024-04-16T01:50:01.625041Z"
    }
   },
   "cell_type": "code",
   "source": [
    "dataset_list_gt = dataset.split_by_class()\n",
    "dataset_list_pred = dataset.split_by_pred(model)"
   ],
   "id": "a1958000e3fa2221",
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/homebrew/Caskroom/mambaforge/base/envs/gnninterpreter/lib/python3.10/site-packages/torch_geometric/data/in_memory_dataset.py:300: UserWarning: It is not recommended to directly access the internal storage format `data` of an 'InMemoryDataset'. If you are absolutely certain what you are doing, access the internal storage via `InMemoryDataset._data` instead to suppress this warning. Alternatively, you can access stacked individual attributes of every graph via `dataset.{attr_name}`.\n",
      "  warnings.warn(msg)\n",
      "/opt/homebrew/Caskroom/mambaforge/base/envs/gnninterpreter/lib/python3.10/site-packages/torch_geometric/deprecation.py:26: UserWarning: 'data.DataLoader' is deprecated, use 'loader.DataLoader' instead\n",
      "  warnings.warn(out)\n"
     ]
    }
   ],
   "execution_count": 7
  },
  {
   "cell_type": "code",
   "id": "6645ce41-8d77-4945-a474-561843ee8109",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-04-16T01:50:17.207536Z",
     "start_time": "2024-04-16T01:50:13.396947Z"
    }
   },
   "source": [
    "evaluation = dataset.model_evaluate(model)\n",
    "evaluation"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'acc': 0.9909999966621399,\n",
       " 'cm': array([[1568,    7,    1,   20,    0],\n",
       "        [   8, 1611,    0,    7,    0],\n",
       "        [   1,    0, 1584,   21,    0],\n",
       "        [   3,    4,    0, 1616,    0],\n",
       "        [   0,    0,    0,    0, 1549]]),\n",
       " 'f1': {'random': 0.98740553855896,\n",
       "  'lollipop': 0.991995096206665,\n",
       "  'wheel': 0.9927922487258911,\n",
       "  'grid': 0.9832674264907837,\n",
       "  'star': 1.0}}"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 8
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-04-16T01:50:27.283368Z",
     "start_time": "2024-04-16T01:50:27.107347Z"
    }
   },
   "cell_type": "code",
   "source": "draw_matrix(evaluation['cm'], dataset.GRAPH_CLS.values(), fmt='d')",
   "id": "158328baa53a6ef7",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 9
  },
  {
   "cell_type": "code",
   "id": "d4a27bdf-0586-4652-9989-53b8257bb2e9",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-04-16T01:50:39.166757Z",
     "start_time": "2024-04-16T01:50:37.531554Z"
    }
   },
   "source": "mean_embeds = [d.model_transform(model, key=\"embeds\").mean(dim=0) for d in dataset_list_gt]",
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/homebrew/Caskroom/mambaforge/base/envs/gnninterpreter/lib/python3.10/site-packages/torch_geometric/deprecation.py:26: UserWarning: 'data.DataLoader' is deprecated, use 'loader.DataLoader' instead\n",
      "  warnings.warn(out)\n"
     ]
    }
   ],
   "execution_count": 10
  },
  {
   "cell_type": "code",
   "id": "2c966c81e3166b9e",
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-04-16T01:50:39.575955Z",
     "start_time": "2024-04-16T01:50:39.554265Z"
    }
   },
   "source": [
    "trainer = {}\n",
    "sampler = {}"
   ],
   "outputs": [],
   "execution_count": 11
  },
  {
   "cell_type": "markdown",
   "id": "383c9c7a23eb249f",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "# Lollipop"
   ]
  },
  {
   "cell_type": "code",
   "id": "bc959668d833b3b6",
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-04-16T01:53:41.081569Z",
     "start_time": "2024-04-16T01:53:41.058201Z"
    }
   },
   "source": [
    "cls_idx = 1\n",
    "trainer[cls_idx] = Trainer(\n",
    "    sampler=(s := GraphSampler(\n",
    "        max_nodes=25,\n",
    "        temperature=0.15,\n",
    "        learn_node_feat=False\n",
    "    )),\n",
    "    discriminator=model,\n",
    "    criterion=WeightedCriterion([\n",
    "        dict(key=\"logits\", criterion=ClassScoreCriterion(class_idx=cls_idx, mode='maximize'), weight=5),\n",
    "        dict(key=\"embeds\", criterion=EmbeddingCriterion(target_embedding=mean_embeds[cls_idx]), weight=5),\n",
    "        dict(key=\"logits\", criterion=MeanPenalty(), weight=1),\n",
    "        dict(key=\"omega\", criterion=NormPenalty(order=1), weight=1),\n",
    "        dict(key=\"omega\", criterion=NormPenalty(order=2), weight=1),\n",
    "        # dict(key=\"xi\", criterion=NormPenalty(order=1), weight=0),\n",
    "        # dict(key=\"xi\", criterion=NormPenalty(order=2), weight=0),\n",
    "        # dict(key=\"eta\", criterion=NormPenalty(order=1), weight=0),\n",
    "        # dict(key=\"eta\", criterion=NormPenalty(order=2), weight=0),\n",
    "        dict(key=\"theta_pairs\", criterion=KLDivergencePenalty(binary=True), weight=20),\n",
    "    ]),\n",
    "    optimizer=(o := torch.optim.SGD(s.parameters(), lr=1)),\n",
    "    scheduler=torch.optim.lr_scheduler.ExponentialLR(o, gamma=1),\n",
    "    dataset=dataset,\n",
    "    budget_penalty=BudgetPenalty(budget=10, order=2, beta=1),\n",
    ")"
   ],
   "outputs": [],
   "execution_count": 25
  },
  {
   "cell_type": "code",
   "id": "4c0bd9796d611c52",
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-04-16T01:53:45.175329Z",
     "start_time": "2024-04-16T01:53:41.536141Z"
    }
   },
   "source": [
    "cls_idx = 1\n",
    "trainer[cls_idx].train(\n",
    "    iterations=2000,\n",
    "    target_probs={cls_idx: (0.9, 1.0)},\n",
    "    target_size=40,\n",
    "    w_budget_init=1,\n",
    "    w_budget_inc=1.1,\n",
    "    w_budget_dec=0.95,\n",
    "    k_samples=16\n",
    ")"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "  0%|          | 0/2000 [00:00<?, ?it/s]"
      ],
      "application/vnd.jupyter.widget-view+json": {
       "version_major": 2,
       "version_minor": 0,
       "model_id": "33e0ffbef1b74f4ab180d022a93241fc"
      }
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 26
  },
  {
   "cell_type": "code",
   "source": [
    "trainer[1].evaluate(threshold=0.5, show=True)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-04-16T01:53:45.952328Z",
     "start_time": "2024-04-16T01:53:45.880684Z"
    }
   },
   "id": "fd3d495b831e49c2",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "n=16 m=34\n",
      "logits=[-2.5123493671417236, 2.1324427127838135, -16.832082748413086, -15.12959098815918, -73.9304428100586]\n",
      "probs=[0.009520025923848152, 0.9904800057411194, 5.749857034942352e-09, 3.1552939816492653e-08, 9.165426798987303e-34]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 600x600 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<networkx.classes.graph.Graph at 0x33e9e3cd0>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 27
  },
  {
   "cell_type": "markdown",
   "id": "4f4d3ddd-9bb6-456c-9a68-5a3edd019e6e",
   "metadata": {},
   "source": [
    "# Wheel"
   ]
  },
  {
   "cell_type": "code",
   "id": "cee8d978ff9fc2ee",
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-04-16T03:26:22.325428Z",
     "start_time": "2024-04-16T03:26:22.301970Z"
    }
   },
   "source": [
    "cls_idx = 2\n",
    "trainer[cls_idx] = Trainer(\n",
    "    sampler=(s := GraphSampler(\n",
    "        max_nodes=25,\n",
    "        temperature=0.15,\n",
    "        learn_node_feat=False\n",
    "    )),\n",
    "    discriminator=model,\n",
    "    criterion=WeightedCriterion([\n",
    "        dict(key=\"logits\", criterion=ClassScoreCriterion(class_idx=cls_idx, mode='maximize'), weight=2),\n",
    "        dict(key=\"embeds\", criterion=EmbeddingCriterion(target_embedding=mean_embeds[cls_idx]), weight=5),\n",
    "        dict(key=\"logits\", criterion=MeanPenalty(), weight=1),\n",
    "        dict(key=\"omega\", criterion=NormPenalty(order=1), weight=1),\n",
    "        dict(key=\"omega\", criterion=NormPenalty(order=2), weight=1),\n",
    "        # dict(key=\"xi\", criterion=NormPenalty(order=1), weight=0),\n",
    "        # dict(key=\"xi\", criterion=NormPenalty(order=2), weight=0),\n",
    "        # dict(key=\"eta\", criterion=NormPenalty(order=1), weight=0),\n",
    "        # dict(key=\"eta\", criterion=NormPenalty(order=2), weight=0),\n",
    "        dict(key=\"theta_pairs\", criterion=KLDivergencePenalty(binary=True), weight=2),\n",
    "    ]),\n",
    "    optimizer=(o := torch.optim.SGD(s.parameters(), lr=1)),\n",
    "    scheduler=torch.optim.lr_scheduler.ExponentialLR(o, gamma=1),\n",
    "    dataset=dataset,\n",
    "    budget_penalty=BudgetPenalty(budget=25, order=2, beta=1),\n",
    ")"
   ],
   "outputs": [],
   "execution_count": 87
  },
  {
   "cell_type": "code",
   "id": "dcc3278f-a073-42e2-b446-0115025e391f",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-04-16T03:26:23.795280Z",
     "start_time": "2024-04-16T03:26:22.632115Z"
    }
   },
   "source": [
    "cls_idx = 2\n",
    "trainer[cls_idx].train(\n",
    "    iterations=2000,\n",
    "    target_probs={cls_idx: (0.9, 1.0)},\n",
    "    target_size=40,\n",
    "    w_budget_init=0.2,\n",
    "    w_budget_inc=1.1,\n",
    "    w_budget_dec=0.95,\n",
    "    k_samples=16\n",
    ")"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "  0%|          | 0/2000 [00:00<?, ?it/s]"
      ],
      "application/vnd.jupyter.widget-view+json": {
       "version_major": 2,
       "version_minor": 0,
       "model_id": "8377e13bf75f4c6991e3689fa4e02664"
      }
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 88
  },
  {
   "cell_type": "code",
   "id": "10896fc3a8e2ea3d",
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-04-16T03:26:24.833557Z",
     "start_time": "2024-04-16T03:26:24.765511Z"
    }
   },
   "source": [
    "trainer[2].evaluate(threshold=0.5, show=True)"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "n=13 m=26\n",
      "logits=[-7.353414535522461, -22.411876678466797, -3.5287582874298096, -36.285587310791016, -21.52581214904785]\n",
      "probs=[0.021359741687774658, 6.1629590319967065e-09, 0.9786402583122253, 5.8145123000522426e-15, 1.494865742301954e-08]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 600x600 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<networkx.classes.graph.Graph at 0x3403046a0>"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 89
  },
  {
   "cell_type": "markdown",
   "id": "750dd3e232b9e135",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "# Grid"
   ]
  },
  {
   "cell_type": "code",
   "id": "5861e9b3266ebd02",
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-04-16T07:20:01.081008Z",
     "start_time": "2024-04-16T07:20:01.057692Z"
    }
   },
   "source": [
    "cls_idx = 3\n",
    "trainer[cls_idx] = Trainer(\n",
    "    sampler=(s := GraphSampler(\n",
    "        max_nodes=25,\n",
    "        temperature=0.15,\n",
    "        learn_node_feat=False\n",
    "    )),\n",
    "    discriminator=model,\n",
    "    criterion=WeightedCriterion([\n",
    "        dict(key=\"logits\", criterion=ClassScoreCriterion(class_idx=cls_idx, mode='maximize'), weight=2),\n",
    "        dict(key=\"embeds\", criterion=EmbeddingCriterion(target_embedding=mean_embeds[cls_idx]), weight=10),\n",
    "        dict(key=\"logits\", criterion=MeanPenalty(), weight=2),\n",
    "        dict(key=\"omega\", criterion=NormPenalty(order=1), weight=1),\n",
    "        dict(key=\"omega\", criterion=NormPenalty(order=2), weight=1),\n",
    "        # dict(key=\"xi\", criterion=NormPenalty(order=1), weight=0),\n",
    "        # dict(key=\"xi\", criterion=NormPenalty(order=2), weight=0),\n",
    "        # dict(key=\"eta\", criterion=NormPenalty(order=1), weight=0),\n",
    "        # dict(key=\"eta\", criterion=NormPenalty(order=2), weight=0),\n",
    "        dict(key=\"theta_pairs\", criterion=KLDivergencePenalty(binary=True), weight=15),\n",
    "    ]),\n",
    "    optimizer=(o := torch.optim.SGD(s.parameters(), lr=1)),\n",
    "    scheduler=torch.optim.lr_scheduler.ExponentialLR(o, gamma=1),\n",
    "    dataset=dataset,\n",
    "    budget_penalty=BudgetPenalty(budget=20, order=2, beta=1)\n",
    ")"
   ],
   "outputs": [],
   "execution_count": 160
  },
  {
   "cell_type": "code",
   "id": "0cff7d90-c4be-44ac-ba36-25dc028640b7",
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    },
    "scrolled": true,
    "tags": [],
    "ExecuteTime": {
     "end_time": "2024-04-16T07:20:03.287102Z",
     "start_time": "2024-04-16T07:20:01.516283Z"
    }
   },
   "source": [
    "cls_idx = 3\n",
    "trainer[cls_idx].train(\n",
    "    iterations=2000,\n",
    "    target_probs={cls_idx: (0.9, 1.0)},\n",
    "    target_size=40,\n",
    "    w_budget_init=1,\n",
    "    w_budget_inc=1.1,\n",
    "    w_budget_dec=0.95,\n",
    "    k_samples=16\n",
    ")"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "  0%|          | 0/2000 [00:00<?, ?it/s]"
      ],
      "application/vnd.jupyter.widget-view+json": {
       "version_major": 2,
       "version_minor": 0,
       "model_id": "7e0f083c70164b978406d75c771dda8f"
      }
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 161,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 161
  },
  {
   "cell_type": "code",
   "id": "3ea01e28-f2a1-486b-ad1d-49b8513524dd",
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    },
    "scrolled": true,
    "tags": [],
    "ExecuteTime": {
     "end_time": "2024-04-16T07:20:04.397021Z",
     "start_time": "2024-04-16T07:20:04.327464Z"
    }
   },
   "source": [
    "trainer[3].evaluate(threshold=0.5, show=True)"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "n=13 m=17\n",
      "logits=[-5.537380695343018, -15.427905082702637, -26.769681930541992, -0.8409218788146973, -98.59515380859375]\n",
      "probs=[0.009044979698956013, 4.581499410960532e-07, 5.436709676204243e-12, 0.990954577922821, 3.4892331761687945e-43]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 600x600 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<networkx.classes.graph.Graph at 0x340de8f10>"
      ]
     },
     "execution_count": 162,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 162
  },
  {
   "cell_type": "markdown",
   "id": "4231e600719d448c",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "# Star"
   ]
  },
  {
   "cell_type": "code",
   "id": "54eacd62452ea329",
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-04-16T07:22:54.306757Z",
     "start_time": "2024-04-16T07:22:54.282367Z"
    }
   },
   "source": [
    "cls_idx = 4\n",
    "trainer[cls_idx] = Trainer(\n",
    "    sampler=(s := GraphSampler(\n",
    "        max_nodes=25,\n",
    "        temperature=0.15,\n",
    "        learn_node_feat=False\n",
    "    )),\n",
    "    discriminator=model,\n",
    "    criterion=WeightedCriterion([\n",
    "        dict(key=\"logits\", criterion=ClassScoreCriterion(class_idx=cls_idx, mode='maximize'), weight=1),\n",
    "        dict(key=\"embeds\", criterion=EmbeddingCriterion(target_embedding=mean_embeds[cls_idx]), weight=10),\n",
    "        dict(key=\"logits\", criterion=MeanPenalty(), weight=0),\n",
    "        dict(key=\"omega\", criterion=NormPenalty(order=1), weight=1),\n",
    "        dict(key=\"omega\", criterion=NormPenalty(order=2), weight=1),\n",
    "        # dict(key=\"xi\", criterion=NormPenalty(order=1), weight=0),\n",
    "        # dict(key=\"xi\", criterion=NormPenalty(order=2), weight=0),\n",
    "        # dict(key=\"eta\", criterion=NormPenalty(order=1), weight=0),\n",
    "        # dict(key=\"eta\", criterion=NormPenalty(order=2), weight=0),\n",
    "        dict(key=\"theta_pairs\", criterion=KLDivergencePenalty(binary=True), weight=1),\n",
    "    ]),\n",
    "    optimizer=(o := torch.optim.SGD(s.parameters(), lr=1)),\n",
    "    scheduler=torch.optim.lr_scheduler.ExponentialLR(o, gamma=1),\n",
    "    dataset=dataset,\n",
    "    budget_penalty=BudgetPenalty(budget=25, order=2, beta=1),\n",
    ")"
   ],
   "outputs": [],
   "execution_count": 207
  },
  {
   "cell_type": "code",
   "id": "72731ad9-26f5-4229-ab91-f1742e3eddf3",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-04-16T07:22:55.726846Z",
     "start_time": "2024-04-16T07:22:54.672904Z"
    }
   },
   "source": [
    "cls_idx = 4\n",
    "trainer[cls_idx].train(\n",
    "    iterations=2000,\n",
    "    target_probs={cls_idx: (0.9, 1.0)},\n",
    "    target_size=30,\n",
    "    w_budget_init=0.1,\n",
    "    w_budget_inc=1.1,\n",
    "    w_budget_dec=0.95,\n",
    "    k_samples=16\n",
    ")"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "  0%|          | 0/2000 [00:00<?, ?it/s]"
      ],
      "application/vnd.jupyter.widget-view+json": {
       "version_major": 2,
       "version_minor": 0,
       "model_id": "f99270a4f5cb4656b3e45ab1b4e5720a"
      }
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 208,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 208
  },
  {
   "cell_type": "code",
   "id": "15eeaee56eb748d7",
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-04-16T07:22:57.250932Z",
     "start_time": "2024-04-16T07:22:57.173379Z"
    }
   },
   "source": [
    "trainer[4].evaluate(threshold=0.5, show=True)"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "n=19 m=20\n",
      "logits=[-65.79411315917969, -235.32423400878906, -49.21257400512695, -276.167236328125, 45.142982482910156]\n",
      "probs=[0.0, 0.0, 1.0516744974757752e-41, 0.0, 1.0]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 600x600 with 1 Axes>"
      ],
      "image/png": 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