






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



def 						lowercase    (				__snake_case				: List[str]		,					__snake_case				: List[str]		,					__snake_case				: Dict		,					__snake_case				: Dict	):
		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:
				lowercase_ : Optional[Any]							       =   TOKENIZER_CLASSES
		else:
				lowercase_ : Optional[Any]							       =   {tokenizer_name: getattr(UpperCamelCase_		,					tokenizer_name + '''Fast'''	)}

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

		for tokenizer_name in tokenizer_names:
				lowercase_ : List[str]							       =   TOKENIZER_CLASSES[tokenizer_name]

				lowercase_ : int							       =   True
				if checkpoint_name is None:
						lowercase_ : Any							       =   list(tokenizer_class.max_model_input_sizes.keys()	)
				else:
						lowercase_ : List[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
						lowercase_ : 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:
								lowercase_       ,					lowercase_ : Dict							       =   checkpoint.split('''/'''	)
								lowercase_ : str							       =   os.path.join(UpperCamelCase_		,					UpperCamelCase_	)
						elif add_prefix:
								lowercase_ : Dict							       =   checkpoint
								lowercase_ : Union[str, Any]							       =   dump_path
						else:
								lowercase_ : Tuple							       =   None
								lowercase_ : Optional[int]							       =   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]:
								lowercase_ : Optional[Any]							       =   list(tokenizer.pretrained_vocab_files_map.values()	)[0][checkpoint]
								lowercase_ : Union[str, Any]							       =   file_path.split(UpperCamelCase_	)[-1][0]
								if next_char == "/":
										lowercase_ : int							       =   os.path.join(UpperCamelCase_		,					UpperCamelCase_	)
										lowercase_ : Optional[int]							       =   None

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

						lowercase_ : 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		:       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"""





from __future__ import annotations

from fractions import Fraction



def 						_lowerCAmelCase				(				UpperCamelCase_  ,				UpperCamelCase_				):
		return (
		    num != den and num % 10 == den // 10 and (num // 10) / (den % 10) == num / den
		)



def 						_lowerCAmelCase				(				UpperCamelCase_				):
		__SCREAMING_SNAKE_CASE            = []
		__SCREAMING_SNAKE_CASE            = 11
		__SCREAMING_SNAKE_CASE            = int("""1""" + """0""" * digit_len				)
		for num in range(UpperCamelCase_  ,				UpperCamelCase_				):
				while den <= 99:
						if (num != den) and (num % 10 == den // 10) and (den % 10 != 0):
								if is_digit_cancelling(UpperCamelCase_  ,				UpperCamelCase_				):
										solutions.append(f"{num}/{den}"				)
						den += 1
				num += 1
				__SCREAMING_SNAKE_CASE            = 10
		return solutions



def 						_lowerCAmelCase				(				UpperCamelCase_ = 2				):
		__SCREAMING_SNAKE_CASE            = 1.0
		for fraction in fraction_list(UpperCamelCase_				):
				__SCREAMING_SNAKE_CASE            = Fraction(UpperCamelCase_				)
				result *= frac.denominator / frac.numerator
		return int(UpperCamelCase_				)


if __name__ == "__main__":
							print(solution())




