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{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "acd48e6e6d4c4633",
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-10-28T14:36:14.727219Z",
     "start_time": "2023-10-28T14:36:09.043058100Z"
    }
   },
   "outputs": [],
   "source": [
    "from transformers import ViTFeatureExtractor, ViTForImageClassification, TrainingArguments, Trainer\n",
    "from datasets import Dataset\n",
    "import torch\n",
    "from collections import defaultdict\n",
    "from tqdm import tqdm\n",
    "import pandas as pd\n",
    "import evaluate\n",
    "from transformers import AutoFeatureExtractor\n",
    "from transformers import AutoImageProcessor\n",
    "from transformers import DefaultDataCollator\n",
    "from transformers import AutoModelForImageClassification\n",
    "from datasets import load_dataset, Image\n",
    "from torchvision.transforms import RandomResizedCrop, Compose, Normalize, ToTensor, Resize\n",
    "import os\n",
    "from datasets import load_metric\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import huggingface_hub"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "c324102059b1be59",
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-10-28T14:36:14.740390100Z",
     "start_time": "2023-10-28T14:36:14.729879900Z"
    }
   },
   "outputs": [],
   "source": [
    "vit_model = \"google/vit-base-patch16-224-in21k\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Token will not been saved to git credential helper. Pass `add_to_git_credential=True` if you want to set the git credential as well.\n",
      "Token is valid (permission: write).\n",
      "Your token has been saved to C:\\Users\\deser\\.cache\\huggingface\\token\n",
      "Login successful\n"
     ]
    }
   ],
   "source": [
    "huggingface_hub.login(os.getenv(\"HF_TOKEN\"))"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-10-28T14:36:15.213009200Z",
     "start_time": "2023-10-28T14:36:14.733391Z"
    }
   },
   "id": "9d57da91a0e193a5"
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "7f66d3ae1285a826",
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-10-28T14:36:18.519045Z",
     "start_time": "2023-10-28T14:36:15.216010200Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Some weights of ViTForImageClassification were not initialized from the model checkpoint at google/vit-base-patch16-224-in21k and are newly initialized: ['classifier.bias', 'classifier.weight']\n",
      "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n"
     ]
    }
   ],
   "source": [
    "image_processor = AutoImageProcessor.from_pretrained(vit_model)\n",
    "model = ViTForImageClassification.from_pretrained(vit_model)\n",
    "data_collator = DefaultDataCollator()\n",
    "accuracy = evaluate.load(\"accuracy\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "bd8dd697d2a1bff0",
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-10-28T14:36:22.254000800Z",
     "start_time": "2023-10-28T14:36:18.522044700Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\deser\\AppData\\Local\\Temp\\ipykernel_16564\\721318933.py:1: FutureWarning: load_metric is deprecated and will be removed in the next major version of datasets. Use 'evaluate.load' instead, from the new library 🤗 Evaluate: https://huggingface.co/docs/evaluate\n",
      "  accuracy_metric = load_metric(\"accuracy\")\n"
     ]
    }
   ],
   "source": [
    "accuracy_metric = load_metric(\"accuracy\")\n",
    "f1_metric = load_metric(\"f1\")\n",
    "# precision_metric = load_metric(\"precision\")\n",
    "recall_metric = load_metric(\"recall\")\n",
    "\n",
    "def compute_metrics(eval_pred):\n",
    "    logits, labels = eval_pred\n",
    "    predictions = np.argmax(logits, axis=-1)\n",
    "\n",
    "    # Berechnung der Metriken\n",
    "    accuracy = accuracy_metric.compute(predictions=predictions, references=labels)\n",
    "    f1 = f1_metric.compute(predictions=predictions, references=labels, average='weighted')\n",
    "    # precision = precision_metric.compute(predictions=predictions, references=labels, average='weighted')\n",
    "    recall = recall_metric.compute(predictions=predictions, references=labels, average='weighted')\n",
    "    \n",
    "    # Rückgabe der Metriken als Dictionary\n",
    "    return {\n",
    "        'accuracy': accuracy['accuracy'],\n",
    "        'f1': f1['f1'],\n",
    "        # 'precision': precision['precision'],\n",
    "        'recall': recall['recall'],\n",
    "    }"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "6da3c7315a4210c0",
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-10-28T14:36:22.268204Z",
     "start_time": "2023-10-28T14:36:22.256003300Z"
    }
   },
   "outputs": [],
   "source": [
    "normalize = Normalize(mean=image_processor.image_mean, std=image_processor.image_std)\n",
    "size = (\n",
    "    image_processor.size[\"shortest_edge\"]\n",
    "    if \"shortest_edge\" in image_processor.size\n",
    "    else (image_processor.size[\"height\"], image_processor.size[\"width\"])\n",
    ")\n",
    "_transforms = Compose([Resize(size), ToTensor(), normalize])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "9b6b9dc6f90d1a7b",
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-10-28T14:36:22.268204Z",
     "start_time": "2023-10-28T14:36:22.261308300Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(224, 224)\n"
     ]
    }
   ],
   "source": [
    "print(size)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "7e03c63aa76f2d2c",
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-10-28T14:36:22.270206600Z",
     "start_time": "2023-10-28T14:36:22.263418200Z"
    }
   },
   "outputs": [],
   "source": [
    "def transforms(examples):\n",
    "    examples[\"pixel_values\"] = [_transforms(img.convert(\"RGB\")) for img in examples[\"image\"]]\n",
    "    del examples[\"image\"]\n",
    "    return examples"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "c1c43932cbd8f738",
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-10-28T14:36:46.382891200Z",
     "start_time": "2023-10-28T14:36:22.270206600Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "Resolving data files:   0%|          | 0/1080 [00:00<?, ?it/s]",
      "application/vnd.jupyter.widget-view+json": {
       "version_major": 2,
       "version_minor": 0,
       "model_id": "2ab932d2d70a48b691e60292f5be3dd6"
      }
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": "Resolving data files:   0%|          | 0/897 [00:00<?, ?it/s]",
      "application/vnd.jupyter.widget-view+json": {
       "version_major": 2,
       "version_minor": 0,
       "model_id": "84bad9c271cc4329822e7dd5605cf247"
      }
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "34\n"
     ]
    }
   ],
   "source": [
    "dataset = load_dataset(\"desertraider/mahjong_souls_tiles\", keep_in_memory=True)\n",
    "NUM_CLASSES = len(set(dataset['train']['label']))\n",
    "print(NUM_CLASSES)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "c38736161fce0923",
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-10-28T14:36:46.399254700Z",
     "start_time": "2023-10-28T14:36:46.374892300Z"
    }
   },
   "outputs": [],
   "source": [
    "dataset = dataset.with_transform(transforms)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "a5317723a958c74b",
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-10-28T14:36:46.411172600Z",
     "start_time": "2023-10-28T14:36:46.400255200Z"
    }
   },
   "outputs": [],
   "source": [
    "labels = dataset[\"train\"].features[\"label\"].names\n",
    "label2id, id2label = dict(), dict()\n",
    "for i, label in enumerate(labels):\n",
    "    label2id[label] = str(i)\n",
    "    id2label[str(i)] = label"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "7fe633b41e8623a0",
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-10-28T14:36:46.504073800Z",
     "start_time": "2023-10-28T14:36:46.403174500Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "{'label': 0,\n 'pixel_values': tensor([[[-0.9216, -0.9216, -0.9137,  ..., -0.9137, -0.9137, -0.9137],\n          [-0.8510, -0.8353, -0.7882,  ..., -0.8431, -0.8745, -0.8824],\n          [-0.7333, -0.7098, -0.6000,  ..., -0.7490, -0.8275, -0.8431],\n          ...,\n          [-0.7804, -0.7725, -0.7412,  ..., -0.7882, -0.8118, -0.8118],\n          [-0.7882, -0.7882, -0.7882,  ..., -0.7882, -0.7882, -0.7804],\n          [-0.7882, -0.7961, -0.8196,  ..., -0.7804, -0.7647, -0.7569]],\n \n         [[-0.7725, -0.7725, -0.7725,  ..., -0.7725, -0.7725, -0.7725],\n          [-0.7333, -0.7333, -0.7020,  ..., -0.7333, -0.7569, -0.7569],\n          [-0.6784, -0.6706, -0.6078,  ..., -0.6863, -0.7255, -0.7333],\n          ...,\n          [-0.6784, -0.6706, -0.6549,  ..., -0.6784, -0.6941, -0.6941],\n          [-0.6784, -0.6784, -0.6784,  ..., -0.6706, -0.6706, -0.6627],\n          [-0.6706, -0.6784, -0.6941,  ..., -0.6627, -0.6471, -0.6392]],\n \n         [[-0.5137, -0.5137, -0.5137,  ..., -0.5137, -0.5059, -0.5059],\n          [-0.5294, -0.5294, -0.5373,  ..., -0.5294, -0.5137, -0.5137],\n          [-0.5529, -0.5608, -0.5765,  ..., -0.5451, -0.5294, -0.5294],\n          ...,\n          [-0.4902, -0.4902, -0.4824,  ..., -0.4667, -0.4667, -0.4667],\n          [-0.4588, -0.4667, -0.4745,  ..., -0.4431, -0.4353, -0.4353],\n          [-0.4353, -0.4431, -0.4667,  ..., -0.4196, -0.4039, -0.4039]]])}"
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset[\"train\"][0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "ee589376b1b2efdf",
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-10-28T14:36:46.781168200Z",
     "start_time": "2023-10-28T14:36:46.505074100Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).\n"
     ]
    },
    {
     "data": {
      "text/plain": "<matplotlib.image.AxesImage at 0x20b7f291850>"
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "img = dataset[\"train\"][850][\"pixel_values\"]\n",
    "plt.imshow(img.permute(1, 2, 0))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "b4aa39dedcc3091b",
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-10-28T14:36:46.792453300Z",
     "start_time": "2023-10-28T14:36:46.784731200Z"
    }
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "6a00eb1bcd16b972",
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-10-28T14:36:46.792453300Z",
     "start_time": "2023-10-28T14:36:46.787938500Z"
    }
   },
   "outputs": [],
   "source": [
    "# Feature Extractor und Modell laden"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "2eac60f1bf9bbda",
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-10-28T14:36:48.388754500Z",
     "start_time": "2023-10-28T14:36:46.790453Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Some weights of ViTForImageClassification were not initialized from the model checkpoint at google/vit-base-patch16-224-in21k and are newly initialized: ['classifier.bias', 'classifier.weight']\n",
      "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n"
     ]
    }
   ],
   "source": [
    "# Anzahl der Klassen anpassen\n",
    "model = AutoModelForImageClassification.from_pretrained(\n",
    "    vit_model,\n",
    "    num_labels=len(labels),\n",
    "    id2label=id2label,\n",
    "    label2id=label2id,\n",
    ")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "outputs": [],
   "source": [],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-10-28T14:36:48.388754500Z",
     "start_time": "2023-10-28T14:36:48.383257500Z"
    }
   },
   "id": "8a02775d2dd5a617"
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "50dab53e68b10f3e",
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-10-28T14:36:49.250862700Z",
     "start_time": "2023-10-28T14:36:48.386755100Z"
    }
   },
   "outputs": [],
   "source": [
    "# Trainingsargumente setzen\n",
    "training_args = TrainingArguments(\n",
    "    output_dir=\"vision_model_output\", # Log-Dateien werden hier gespeichert\n",
    "    logging_dir=\"vision_model_output/tb_logs\", # Spezifischer Ort für TensorBoard-Logs\n",
    "    remove_unused_columns=False,\n",
    "    evaluation_strategy=\"epoch\",\n",
    "    save_strategy=\"epoch\", # Speichert nur am Ende jeder Epoche\n",
    "    save_total_limit=2,\n",
    "    learning_rate=5e-5,\n",
    "    per_device_train_batch_size=16,\n",
    "    gradient_accumulation_steps=4,\n",
    "    per_device_eval_batch_size=16,\n",
    "    num_train_epochs=250,\n",
    "    warmup_ratio=0.1,\n",
    "    logging_steps=1,\n",
    "    load_best_model_at_end=True,\n",
    "    metric_for_best_model=\"accuracy\",\n",
    "    hub_model_id=\"desertraider/mahjong_soul_vision\",\n",
    "    push_to_hub=True,\n",
    "    auto_find_batch_size=True,\n",
    "    # Setzen Sie Ihren Hugging Face Benutzernamen oder den Organisationsnamen, falls zutreffend\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "c58bec029cfabc5a",
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-10-28T14:36:51.696239800Z",
     "start_time": "2023-10-28T14:36:49.251863300Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "N:\\Projekte\\pythonProject\\mahjong-soul-detector\\venv\\Lib\\site-packages\\pydantic\\_internal\\_fields.py:128: UserWarning: Field \"model_server_url\" has conflict with protected namespace \"model_\".\n",
      "\n",
      "You may be able to resolve this warning by setting `model_config['protected_namespaces'] = ()`.\n",
      "  warnings.warn(\n",
      "N:\\Projekte\\pythonProject\\mahjong-soul-detector\\venv\\Lib\\site-packages\\pydantic\\_internal\\_config.py:317: UserWarning: Valid config keys have changed in V2:\n",
      "* 'schema_extra' has been renamed to 'json_schema_extra'\n",
      "  warnings.warn(message, UserWarning)\n"
     ]
    }
   ],
   "source": [
    "trainer = Trainer(\n",
    "    model=model,\n",
    "    args=training_args,\n",
    "    data_collator=data_collator,\n",
    "    train_dataset=dataset[\"train\"],\n",
    "    eval_dataset=dataset[\"test\"],\n",
    "    tokenizer=image_processor,\n",
    "    compute_metrics=compute_metrics,\n",
    "    \n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "a8b48aab4815ec5",
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-10-28T16:08:47.174973300Z",
     "start_time": "2023-10-28T14:36:51.697241Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "<IPython.core.display.HTML object>",
      "text/html": "\n    <div>\n      \n      <progress value='2' max='4250' style='width:300px; height:20px; vertical-align: middle;'></progress>\n      [   2/4250 : < :, Epoch 0.06/250]\n    </div>\n    <table border=\"1\" class=\"dataframe\">\n  <thead>\n <tr style=\"text-align: left;\">\n      <th>Epoch</th>\n      <th>Training Loss</th>\n      <th>Validation Loss</th>\n    </tr>\n  </thead>\n  <tbody>\n  </tbody>\n</table><p>"
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": "TrainOutput(global_step=4250, training_loss=0.2148646897008533, metrics={'train_runtime': 5505.3667, 'train_samples_per_second': 49.043, 'train_steps_per_second': 0.772, 'total_flos': 2.092883798863872e+19, 'train_loss': 0.2148646897008533, 'epoch': 250.0})"
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "trainer.train()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "initial_id",
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-10-28T16:08:50.495464700Z",
     "start_time": "2023-10-28T16:08:47.177973900Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "'https://huggingface.co/desertraider/mahjong_soul_vision/tree/main/'"
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "# Modell speichern und auf Hugging Face hochladen\n",
    "trainer.save_model()\n",
    "trainer.push_to_hub()\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}