






import argparse
import os

import transformers

from .convert_slow_tokenizer import SLOW_TO_FAST_CONVERTERS
from .utils import logging


logging.set_verbosity_info()

__UpperCamelCase      :      Optional[int]     						=						logging.get_logger(__name__)


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





def 				snake_case  (     lowerCamelCase				,  lowerCamelCase				,  lowerCamelCase				,  lowerCamelCase					):




	'''simple docstring'''







	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             =  TOKENIZER_CLASSES
	else:
		__lowercase             =  {tokenizer_name: getattr(__a				,  tokenizer_name + """Fast"""					)}

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

	for tokenizer_name in tokenizer_names:
		__lowercase             =  TOKENIZER_CLASSES[tokenizer_name]

		__lowercase             =  True
		if checkpoint_name is None:
			__lowercase             =  list(tokenizer_class.max_model_input_sizes.keys()					)
		else:
			__lowercase             =  [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             =  tokenizer_class.from_pretrained(__a				,  force_download=__a					)

			# 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             =  checkpoint.split("""/"""					)
				__lowercase             =  os.path.join(__a				,  __a					)
			elif add_prefix:
				__lowercase             =  checkpoint
				__lowercase             =  dump_path
			else:
				__lowercase             =  None
				__lowercase             =  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             =  list(tokenizer.pretrained_vocab_files_map.values()					)[0][checkpoint]
				__lowercase             =  file_path.split(__a					)[-1][0]
				if next_char == "/":
					__lowercase             =  os.path.join(__a				,  __a					)
					__lowercase             =  None

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

			__lowercase             =  tokenizer.save_pretrained(
			    __a				,  legacy_format=__a				,  filename_prefix=__a					)
			logger.info(F'=> File names {file_names}'					)

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


if __name__ == "__main__":
						__UpperCamelCase      :      Optional[int]     						=						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.""",
						)
						__UpperCamelCase      :      Tuple     						=						parser.parse_args()

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














def 				snake_case  (     lowerCamelCase					):




	'''simple docstring'''







	if not isinstance(lowerCamelCase				,  lowerCamelCase					):
		raise ValueError("""check_bouncy() accepts only integer arguments"""					)
	__lowercase             =  str(lowerCamelCase					)
	__lowercase             =  """""".join(sorted(lowerCamelCase					)					)
	return sorted_str_n != str_n and sorted_str_n[::-1] != str_n





def 				snake_case  (     lowerCamelCase = 99					):




	'''simple docstring'''







	if not 0 < percent < 100:
		raise ValueError("""solution() only accepts values from 0 to 100"""					)
	__lowercase             =  0
	__lowercase             =  1

	while True:
		if check_bouncy(lowerCamelCase					):
			bouncy_num += 1
		if (bouncy_num / num) * 100 >= percent:
			return num
		num += 1


if __name__ == "__main__":
						from doctest import testmod

						testmod()
						print(F'''{solution(99)}''')

