


'''simple docstring'''
UpperCAmelCase_ :     Union[str, Any]								=      '\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n'

UpperCAmelCase_ :     Tuple								=      [{'type': 'code', 'content': INSTALL_CONTENT}]
UpperCAmelCase_ :     Any								=      {
    '{processor_class}': 'FakeProcessorClass',
    '{model_class}': 'FakeModelClass',
    '{object_class}': 'FakeObjectClass',
}










'''simple docstring'''
import argparse
import logging
import pickle
import random
import time

import numpy as np

from transformers import BertTokenizer, GPTaTokenizer, RobertaTokenizer


logging.basicConfig(
    format='%(asctime)s - %(levelname)s - %(name)s - %(message)s', datefmt='%m/%d/%Y %H:%M:%S', level=logging.INFO
)
UpperCAmelCase_ :     Any								=      logging.getLogger(__name__)


def 			_lowercase       (				):
 __A  :		Tuple       =			argparse.ArgumentParser(
     description='Preprocess the data to avoid re-doing it several times by (tokenization + token_to_ids).'			)
 parser.add_argument('--file_path',				type=UpperCamelCase__,				default='data/dump.txt',				help='The path to the data.'			)
 parser.add_argument('--tokenizer_type',				type=UpperCamelCase__,				default='bert',				choices=['bert', 'roberta', 'gpt2']			)
 parser.add_argument('--tokenizer_name',				type=UpperCamelCase__,				default='bert-base-uncased',				help='The tokenizer to use.'			)
 parser.add_argument('--dump_file',				type=UpperCamelCase__,				default='data/dump',				help='The dump file prefix.'			)
 __A  :		Tuple       =			parser.parse_args()

 logger.info(f"""Loading Tokenizer ({args.tokenizer_name})"""			)
 if args.tokenizer_type == "bert":
  __A  :		Any       =			BertTokenizer.from_pretrained(args.tokenizer_name			)
  __A  :		Any       =			tokenizer.special_tokens_map['cls_token']  # `[CLS]`
  __A  :		List[Any]       =			tokenizer.special_tokens_map['sep_token']  # `[SEP]`
 elif args.tokenizer_type == "roberta":
  __A  :		Any       =			RobertaTokenizer.from_pretrained(args.tokenizer_name			)
  __A  :		List[Any]       =			tokenizer.special_tokens_map['cls_token']  # `<s>`
  __A  :		Dict       =			tokenizer.special_tokens_map['sep_token']  # `</s>`
 elif args.tokenizer_type == "gpt2":
  __A  :		List[str]       =			GPTaTokenizer.from_pretrained(args.tokenizer_name			)
  __A  :		Any       =			tokenizer.special_tokens_map['bos_token']  # `<|endoftext|>`
  __A  :		Union[str, Any]       =			tokenizer.special_tokens_map['eos_token']  # `<|endoftext|>`

 logger.info(f"""Loading text from {args.file_path}"""			)
 with open(args.file_path,				'r',				encoding='utf8'			) as fp:
  __A  :		Optional[int]       =			fp.readlines()

 logger.info('Start encoding'			)
 logger.info(f"""{len(UpperCamelCase__			)} examples to process."""			)

 __A  :		int       =			[]
 __A  :		List[str]       =			0
 __A  :		Tuple       =			10000
 __A  :		List[str]       =			time.time()
 for text in data:
  __A  :		int       =			f"""{bos} {text.strip()} {sep}"""
  __A  :		List[Any]       =			tokenizer.encode(UpperCamelCase__,				add_special_tokens=UpperCamelCase__			)
  rslt.append(UpperCamelCase__			)

  iter += 1
  if iter % interval == 0:
   __A  :		Any       =			time.time()
   logger.info(f"""{iter} examples processed. - {(end-start):.2f}s/{interval}expl"""			)
   __A  :		Any       =			time.time()
 logger.info('Finished binarization'			)
 logger.info(f"""{len(UpperCamelCase__			)} examples processed."""			)

 __A  :		List[str]       =			f"""{args.dump_file}.{args.tokenizer_name}.pickle"""
 __A  :		str       =			tokenizer.vocab_size
 if vocab_size < (1 << 16):
  __A  :		Optional[int]       =			[np.uintaa(UpperCamelCase__			) for d in rslt]
 else:
  __A  :		int       =			[np.intaa(UpperCamelCase__			) for d in rslt]
 random.shuffle(rslt_			)
 logger.info(f"""Dump to {dp_file}"""			)
 with open(UpperCamelCase__,				'wb'			) as handle:
  pickle.dump(rslt_,				UpperCamelCase__,				protocol=pickle.HIGHEST_PROTOCOL			)


if __name__ == "__main__":
 main()






