{
 "cells": [
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   "execution_count": 1,
   "id": "bd9232bc-0c38-426d-b29d-7b4a03fd5242",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2024-11-22 22:50:45.568704: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.\n",
      "2024-11-22 22:50:45.569107: I external/local_xla/xla/tsl/cuda/cudart_stub.cc:32] Could not find cuda drivers on your machine, GPU will not be used.\n",
      "2024-11-22 22:50:45.571074: I external/local_xla/xla/tsl/cuda/cudart_stub.cc:32] Could not find cuda drivers on your machine, GPU will not be used.\n",
      "2024-11-22 22:50:45.576441: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:477] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n",
      "WARNING: All log messages before absl::InitializeLog() is called are written to STDERR\n",
      "E0000 00:00:1732312245.585696   11818 cuda_dnn.cc:8310] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n",
      "E0000 00:00:1732312245.588323   11818 cuda_blas.cc:1418] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n",
      "2024-11-22 22:50:45.597922: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n",
      "To enable the following instructions: AVX2 AVX_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n"
     ]
    }
   ],
   "source": [
    "import flair\n",
    "\n",
    "from flair.datasets import ClassificationCorpus\n",
    "\n",
    "from huggingface_hub import hf_hub_download\n",
    "\n",
    "from pathlib import Path\n",
    "from typing import Optional, Union"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "eb688e95-92e3-4b09-a523-eb62fd7cb0bc",
   "metadata": {},
   "outputs": [],
   "source": [
    "class OFFENSEVAL_TR_2020(ClassificationCorpus):\n",
    "    def __init__(\n",
    "        self,\n",
    "        base_path: Optional[Union[str, Path]] = None,\n",
    "        in_memory: bool = True,\n",
    "        **corpusargs,\n",
    "    ) -> None:\n",
    "        base_path = flair.cache_root / \"datasets\" if not base_path else Path(base_path)\n",
    "        dataset_name = self.__class__.__name__.lower()\n",
    "        data_folder = base_path / dataset_name\n",
    "        data_path = flair.cache_root / \"datasets\" / dataset_name\n",
    "\n",
    "        for split in [\"train\", \"dev\", \"test\"]:\n",
    "            hf_hub_download(repo_id=\"stefan-it/offenseval2020_tr\", repo_type=\"dataset\",\n",
    "                            filename=f\"{split}.txt\", token=True, local_dir=data_folder)\n",
    "\n",
    "        super().__init__(\n",
    "            data_path,\n",
    "            **corpusargs,\n",
    "        )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "add7c7f1-2ea2-40be-99a3-a71d20a3a25a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2024-11-22 22:50:51,534 Reading data from /home/stefan/.flair/datasets/offenseval_tr_2020\n",
      "2024-11-22 22:50:51,535 Train: /home/stefan/.flair/datasets/offenseval_tr_2020/train.txt\n",
      "2024-11-22 22:50:51,536 Dev: /home/stefan/.flair/datasets/offenseval_tr_2020/dev.txt\n",
      "2024-11-22 22:50:51,537 Test: /home/stefan/.flair/datasets/offenseval_tr_2020/test.txt\n",
      "2024-11-22 22:50:52,068 Initialized corpus /home/stefan/.flair/datasets/offenseval_tr_2020 (label type name is 'class')\n"
     ]
    }
   ],
   "source": [
    "corpus = OFFENSEVAL_TR_2020()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "f9d2162a-c9bb-46f0-8898-b12ce286ff37",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Corpus: 30000 train + 1756 dev + 3528 test sentences\n"
     ]
    }
   ],
   "source": [
    "print(str(corpus))"
   ]
  }
 ],
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