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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import os\n",
"os.chdir('../')"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'e:\\\\bengla text summarization\\\\train-pegasus-model-on-bengali-text-summarization-using-mlops'"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"%pwd"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"from dataclasses import dataclass\n",
"from pathlib import Path\n",
"\n",
"@dataclass(frozen=True)\n",
"class BanTokenizationConfig:\n",
" root_dir : Path\n",
" source_dir : Path\n",
" save_dir : Path\n",
" output_file : str\n",
" \n"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"from src.benglasummarization.constants import *\n",
"from src.benglasummarization.utils.common import create_directories, read_yaml\n",
"\n",
"class ConfigurationManager:\n",
" def __init__(\n",
" self,\n",
" config_filepath = CONFIG_FILE_PATH,\n",
" params_filepath = PARAMS_FILE_PATH):\n",
"\n",
" self.config = read_yaml(config_filepath)\n",
" self.params = read_yaml(params_filepath)\n",
"\n",
" create_directories([self.config.artifacts_root])\n",
"\n",
" def get_ben_tokenization_config(self) -> BanTokenizationConfig:\n",
" config = self.config.ban_tokenization\n",
" params = self.params.pre_tokenize\n",
" create_directories([config.root_dir])\n",
"\n",
" ben_tokenization_config = BanTokenizationConfig(\n",
" root_dir=config.root_dir,\n",
" source_dir=config.source_dir,\n",
" save_dir= config.save_dir,\n",
" output_file= params.output_file\n",
" )\n",
" \n",
" return ben_tokenization_config\n",
"\n",
" "
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"from pathlib import Path\n",
"from src.benglasummarization.logging import logger\n",
"from tqdm.notebook import tqdm\n",
"\n",
"class BanTokenization:\n",
" def __init__(self, config: BanTokenizationConfig):\n",
" self.config = config\n",
"\n",
" def combine_text_columns(self, text_columns=['main']):\n",
" df = pd.read_csv(self.config.source_dir)\n",
"\n",
" # Ensure save_dir is a Path object\n",
" save_dir = Path(self.config.save_dir)\n",
" \n",
" # Create the directory if it doesn't exist\n",
" save_dir.mkdir(parents=True, exist_ok=True)\n",
"\n",
" # Combine save_dir and output_file to form the output path\n",
" output_txt_file = save_dir / self.config.output_file\n",
" \n",
" # Write the combined text data to the output file\n",
" with open(output_txt_file, 'w', encoding='utf-8') as f:\n",
" for index, row in tqdm(df.iterrows(), total=len(df)):\n",
" combined_text = ' '.join(str(row[col]) for col in text_columns)\n",
" f.write(combined_text + '\\n')\n",
"\n",
" # Log the success of the operation\n",
" logger.info(f\"All text data has been combined into {output_txt_file}\")"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[2024-10-16 19:09:09,141: INFO: common: yaml file: config\\config.yaml loaded successfully]\n",
"[2024-10-16 19:09:09,143: INFO: common: yaml file: params.yaml loaded successfully]\n",
"[2024-10-16 19:09:09,145: INFO: common: created directory at: artifacts]\n",
"[2024-10-16 19:09:09,146: INFO: common: created directory at: artifacts/ban_tokenization]\n"
]
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "46422977ab65463695c98b98ece484c2",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
" 0%| | 0/160000 [00:00<?, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"[2024-10-16 19:10:00,660: INFO: 206824922: All text data has been combined into artifacts\\ban_tokenization\\combined_text.txt]\n"
]
}
],
"source": [
"try:\n",
" config = ConfigurationManager()\n",
" prepare_ben_tok_config = config.get_ben_tokenization_config() \n",
" ben_data_tok = BanTokenization(config=prepare_ben_tok_config)\n",
" ben_data_tok.combine_text_columns()\n",
"except Exception as e:\n",
" raise e"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"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": "3.11.0"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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