






'''simple docstring'''







import argparse
import os

import transformers

from .convert_slow_tokenizer import SLOW_TO_FAST_CONVERTERS
from .utils import logging


logging.set_verbosity_info()

_A	:			Optional[Any]         =logging.get_logger(__name__)


_A	:			int         ={name: getattr(transformers, name + '''Fast''') for name in SLOW_TO_FAST_CONVERTERS}





def  SCREAMING_SNAKE_CASE_       (UpperCamelCase				,			UpperCamelCase				,			UpperCamelCase				,			UpperCamelCase      )      ->       Optional[int]:
							if tokenizer_name is not None and tokenizer_name not in TOKENIZER_CLASSES:
														raise ValueError(f'''Unrecognized tokenizer name, should be one of {list(TOKENIZER_CLASSES.keys()      )}.'''      )

							if tokenizer_name is None:
														lowerCamelCase__					:	Optional[Any]         =       TOKENIZER_CLASSES
							else:
														lowerCamelCase__					:	Dict         =       {tokenizer_name: getattr(UpperCamelCase				,			tokenizer_name + """Fast"""      )}

							logger.info(f'''Loading tokenizer classes: {tokenizer_names}'''      )

							for tokenizer_name in tokenizer_names:
														lowerCamelCase__					:	Tuple         =       TOKENIZER_CLASSES[tokenizer_name]

														lowerCamelCase__					:	Optional[int]         =       True
														if checkpoint_name is None:
																					lowerCamelCase__					:	Any         =       list(tokenizer_class.max_model_input_sizes.keys()      )
														else:
																					lowerCamelCase__					:	Any         =       [checkpoint_name]

														logger.info(f'''For tokenizer {tokenizer_class.__class__.__name__} loading checkpoints: {checkpoint_names}'''      )

														for checkpoint in checkpoint_names:
																					logger.info(f'''Loading {tokenizer_class.__class__.__name__} {checkpoint}'''      )

																					# Load tokenizer
																					lowerCamelCase__					:	List[str]         =       tokenizer_class.from_pretrained(UpperCamelCase				,			force_download=UpperCamelCase      )

																					# Save fast tokenizer
																					logger.info(f'''Save fast tokenizer to {dump_path} with prefix {checkpoint} add_prefix {add_prefix}'''      )

																					# For organization names we create sub-directories
																					if "/" in checkpoint:
																												lowerCamelCase__  ,		lowerCamelCase__					:	List[str]         =       checkpoint.split("""/"""      )
																												lowerCamelCase__					:	Union[str, Any]         =       os.path.join(UpperCamelCase				,			UpperCamelCase      )
																					elif add_prefix:
																												lowerCamelCase__					:	Optional[int]         =       checkpoint
																												lowerCamelCase__					:	Optional[Any]         =       dump_path
																					else:
																												lowerCamelCase__					:	str         =       None
																												lowerCamelCase__					:	Union[str, Any]         =       dump_path

																					logger.info(f'''=> {dump_path_full} with prefix {checkpoint_prefix_name}, add_prefix {add_prefix}'''      )

																					if checkpoint in list(tokenizer.pretrained_vocab_files_map.values()      )[0]:
																												lowerCamelCase__					:	Tuple         =       list(tokenizer.pretrained_vocab_files_map.values()      )[0][checkpoint]
																												lowerCamelCase__					:	Optional[Any]         =       file_path.split(UpperCamelCase      )[-1][0]
																												if next_char == "/":
																																			lowerCamelCase__					:	Optional[Any]         =       os.path.join(UpperCamelCase				,			UpperCamelCase      )
																																			lowerCamelCase__					:	List[Any]         =       None

																												logger.info(f'''=> {dump_path_full} with prefix {checkpoint_prefix_name}, add_prefix {add_prefix}'''      )

																					lowerCamelCase__					:	Any         =       tokenizer.save_pretrained(
																					    UpperCamelCase				,			legacy_format=UpperCamelCase				,			filename_prefix=UpperCamelCase      )
																					logger.info(f'''=> File names {file_names}'''      )

																					for file_name in file_names:
																												if not file_name.endswith("""tokenizer.json"""      ):
																																			os.remove(UpperCamelCase      )
																																			logger.info(f'''=> removing {file_name}'''      )


if __name__ == "__main__":
			_A	:			Union[str, Any]         =argparse.ArgumentParser()
			# Required parameters
			parser.add_argument(
			    '''--dump_path''', default=None, type=str, required=True, help='''Path to output generated fast tokenizer files.'''
			)
			parser.add_argument(
			    '''--tokenizer_name''',
			    default=None,
			    type=str,
			    help=(
			        F'Optional tokenizer type selected in the list of {list(TOKENIZER_CLASSES.keys())}. If not given, will '
			        '''download and convert all the checkpoints from AWS.'''
			    ),
			)
			parser.add_argument(
			    '''--checkpoint_name''',
			    default=None,
			    type=str,
			    help='''Optional checkpoint name. If not given, will download and convert the canonical checkpoints from AWS.''',
			)
			parser.add_argument(
			    '''--force_download''',
			    action='''store_true''',
			    help='''Re-download checkpoints.''',
			)
			_A	:			Optional[int]         =parser.parse_args()

			convert_slow_checkpoint_to_fast(args.tokenizer_name, args.checkpoint_name, args.dump_path, args.force_download)


'''simple docstring'''

def 			__UpperCamelCase       (   UpperCAmelCase = 1		,     UpperCAmelCase = 1000     ):
 lowercase__				:    Dict  =					1
 lowercase__				:    Dict  =					0

 for divide_by_number in range(UpperCAmelCase		,     digit + 1     ):
  lowercase__				:    list[int]  =					[]
  lowercase__				:    Union[str, Any]  =					numerator
  for _ in range(1		,     digit + 1     ):
   if now_divide in has_been_divided:
    if longest_list_length < len(UpperCAmelCase     ):
     lowercase__				:    Dict  =					len(UpperCAmelCase     )
     lowercase__				:    Optional[Any]  =					divide_by_number
   else:
    has_been_divided.append(UpperCAmelCase     )
    lowercase__				:    int  =					now_divide * 10 % divide_by_number

 return the_digit


# Tests
if __name__ == "__main__":
  import doctest

  doctest.testmod()

