


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
)
lowerCAmelCase__    :List[str]       =				logging.getLogger(__name__)

def 			lowerCAmelCase__					(     )    ->						Any:


							'''simple docstring'''





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

							logger.info(F'''Loading Tokenizer ({args.tokenizer_name})'''			)
							if args.tokenizer_type == "bert":
														_UpperCAmelCase											=     BertTokenizer.from_pretrained(args.tokenizer_name			)
														_UpperCAmelCase											=     tokenizer.special_tokens_map['cls_token']  # `[CLS]`
														_UpperCAmelCase											=     tokenizer.special_tokens_map['sep_token']  # `[SEP]`
							elif args.tokenizer_type == "roberta":
														_UpperCAmelCase											=     RobertaTokenizer.from_pretrained(args.tokenizer_name			)
														_UpperCAmelCase											=     tokenizer.special_tokens_map['cls_token']  # `<s>`
														_UpperCAmelCase											=     tokenizer.special_tokens_map['sep_token']  # `</s>`
							elif args.tokenizer_type == "gpt2":
														_UpperCAmelCase											=     GPTaTokenizer.from_pretrained(args.tokenizer_name			)
														_UpperCAmelCase											=     tokenizer.special_tokens_map['bos_token']  # `<|endoftext|>`
														_UpperCAmelCase											=     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:
														_UpperCAmelCase											=     fp.readlines()

							logger.info('Start encoding'			)
							logger.info(F'''{len(a__			)} examples to process.'''			)

							_UpperCAmelCase											=     []
							_UpperCAmelCase											=     0
							_UpperCAmelCase											=     1_0_0_0_0
							_UpperCAmelCase											=     time.time()
							for text in data:
														_UpperCAmelCase											=     F'''{bos} {text.strip()} {sep}'''
														_UpperCAmelCase											=     tokenizer.encode(a__     ,    add_special_tokens=a__			)
														rslt.append(a__			)

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

							_UpperCAmelCase											=     F'''{args.dump_file}.{args.tokenizer_name}.pickle'''
							_UpperCAmelCase											=     tokenizer.vocab_size
							if vocab_size < (1 << 1_6):
														_UpperCAmelCase											=     [np.uintaa(a__			) for d in rslt]
							else:
														_UpperCAmelCase											=     [np.intaa(a__			) for d in rslt]
							random.shuffle(rslt_			)
							logger.info(F'''Dump to {dp_file}'''			)
							with open(a__     ,    'wb'			) as handle:
														pickle.dump(rslt_     ,    a__     ,    protocol=pickle.HIGHEST_PROTOCOL			)


if __name__ == "__main__":
		main()







'''simple docstring'''






def   UpperCamelCase__ (						lowerCAmelCase    ):





      """simple docstring"""


      if divisor % 5 == 0 or divisor % 2 == 0:
            return 0
      _lowerCAmelCase					=				1
      _lowerCAmelCase					=				1
      while repunit:
            _lowerCAmelCase					=				(10 * repunit + 1) % divisor
            repunit_index += 1
      return repunit_index
def   UpperCamelCase__ (						lowerCAmelCase = 1_00_00_00    ):





      """simple docstring"""


      _lowerCAmelCase					=				limit - 1
      if divisor % 2 == 0:
            divisor += 1
      while least_divisible_repunit(lowerCAmelCase    ) <= limit:
            divisor += 2
      return divisor


if __name__ == "__main__":
      print(F"""{solution() = }""")






