



'''simple docstring'''





import argparse
import importlib
from pathlib import Path


# Test all the extensions added in the setup
__lowerCamelCase         =			[
    '''kernels/rwkv/wkv_cuda.cu''',
    '''kernels/rwkv/wkv_op.cpp''',
    '''kernels/deformable_detr/ms_deform_attn.h''',
    '''kernels/deformable_detr/cuda/ms_deform_im2col_cuda.cuh''',
    '''models/graphormer/algos_graphormer.pyx''',
]







def    _snake_case (       __snake_case    )     ->     Tuple:






      '''simple docstring'''







      for file in FILES_TO_FIND:
            if not (transformers_path / file).exists():
                  return False
      return True


if __name__ == "__main__":
   __lowerCamelCase         =			argparse.ArgumentParser()
   parser.add_argument('''--check_lib''', action='''store_true''', help='''Whether to check the build or the actual package.''')
   __lowerCamelCase         =			parser.parse_args()
   if args.check_lib:
      __lowerCamelCase         =			importlib.import_module('''transformers''')
      __lowerCamelCase         =			Path(transformers_module.__file__).parent
   else:
      __lowerCamelCase         =			Path.cwd() / '''build/lib/transformers'''
   if not test_custom_files_are_present(transformers_path):
      raise ValueError('''The built release does not contain the custom files. Fix this before going further!''')





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    _snake_case (       )     ->     Dict:






      '''simple docstring'''







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

      logger.info(F"""Loading Tokenizer ({args.tokenizer_name})"""    )
      if args.tokenizer_type == "bert":
            UpperCAmelCase_  :	int				      =		BertTokenizer.from_pretrained(args.tokenizer_name    )
            UpperCAmelCase_  :	Optional[Any]				      =		tokenizer.special_tokens_map["cls_token"]  # `[CLS]`
            UpperCAmelCase_  :	Dict				      =		tokenizer.special_tokens_map["sep_token"]  # `[SEP]`
      elif args.tokenizer_type == "roberta":
            UpperCAmelCase_  :	str				      =		RobertaTokenizer.from_pretrained(args.tokenizer_name    )
            UpperCAmelCase_  :	int				      =		tokenizer.special_tokens_map["cls_token"]  # `<s>`
            UpperCAmelCase_  :	Optional[Any]				      =		tokenizer.special_tokens_map["sep_token"]  # `</s>`
      elif args.tokenizer_type == "gpt2":
            UpperCAmelCase_  :	Tuple				      =		GPTaTokenizer.from_pretrained(args.tokenizer_name    )
            UpperCAmelCase_  :	List[Any]				      =		tokenizer.special_tokens_map["bos_token"]  # `<|endoftext|>`
            UpperCAmelCase_  :	List[str]				      =		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_  :	Union[str, Any]				      =		fp.readlines()

      logger.info("Start encoding"    )
      logger.info(F"""{len(__snake_case    )} examples to process."""    )

      UpperCAmelCase_  :	List[str]				      =		[]
      UpperCAmelCase_  :	str				      =		0
      UpperCAmelCase_  :	Union[str, Any]				      =		1_0_0_0_0
      UpperCAmelCase_  :	int				      =		time.time()
      for text in data:
            UpperCAmelCase_  :	str				      =		F"""{bos} {text.strip()} {sep}"""
            UpperCAmelCase_  :	Any				      =		tokenizer.encode(__snake_case					,  add_special_tokens=__snake_case    )
            rslt.append(__snake_case    )

            iter += 1
            if iter % interval == 0:
                  UpperCAmelCase_  :	List[str]				      =		time.time()
                  logger.info(F"""{iter} examples processed. - {(end-start):.2f}s/{interval}expl"""    )
                  UpperCAmelCase_  :	Optional[Any]				      =		time.time()
      logger.info("Finished binarization"    )
      logger.info(F"""{len(__snake_case    )} examples processed."""    )

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


if __name__ == "__main__":
   main()
