



"""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
)
lowerCamelCase  			=		logging.getLogger(__name__)
def   a__      ( ):
      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=lowerCAmelCase__      ,     default="data/dump.txt"      ,     help="The path to the data." )
      parser.add_argument("--tokenizer_type"      ,     type=lowerCAmelCase__      ,     default="bert"      ,     choices=["bert", "roberta", "gpt2"] )
      parser.add_argument("--tokenizer_name"      ,     type=lowerCAmelCase__      ,     default="bert-base-uncased"      ,     help="The tokenizer to use." )
      parser.add_argument("--dump_file"      ,     type=lowerCAmelCase__      ,     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(lowerCAmelCase__ )} examples to process.""" )

      UpperCAmelCase_     					=				[]
      UpperCAmelCase_     					=				0
      UpperCAmelCase_     					=				10000
      UpperCAmelCase_     					=				time.time()
      for text in data:
            UpperCAmelCase_     					=				f"""{bos} {text.strip()} {sep}"""
            UpperCAmelCase_     					=				tokenizer.encode(lowerCAmelCase__      ,     add_special_tokens=lowerCAmelCase__ )
            rslt.append(lowerCAmelCase__ )

            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(lowerCAmelCase__ )} examples processed.""" )

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


if __name__ == "__main__":
  main()








'''simple docstring'''
def 					lowerCamelCase_ ( __UpperCamelCase					:       list							,    __UpperCamelCase					:       int							,    __UpperCamelCase					:       int = 0							,    __UpperCamelCase					:       int = 0		)					->	int:







     """simple docstring"""
     _A				=							right or len(__UpperCamelCase		) - 1
     if left > right:
          return -1
     elif list_data[left] == key:
          return left
     elif list_data[right] == key:
          return right
     else:
          return search(__UpperCamelCase							,    __UpperCamelCase							,    left + 1							,    right - 1		)


if __name__ == "__main__":
    import doctest

    doctest.testmod()





