

import argparse
import os

import transformers

from .convert_slow_tokenizer import SLOW_TO_FAST_CONVERTERS
from .utils import logging


logging.set_verbosity_info()

__lowerCAmelCase			     =       logging.get_logger(__name__)


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



def    _lowercase			(	a__						:			Optional[int]							,  a__						:			Tuple							,  a__						:			int							,  a__						:			Optional[int]					)							->					Union[str, Any]:





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

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

	for tokenizer_name in tokenizer_names:
		_UpperCamelCase			=   TOKENIZER_CLASSES[tokenizer_name]

		_UpperCamelCase			=   True
		if checkpoint_name is None:
			_UpperCamelCase			=   list(tokenizer_class.max_model_input_sizes.keys()					)
		else:
			_UpperCamelCase			=   [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
			_UpperCamelCase			=   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:
				_UpperCamelCase	,				_UpperCamelCase			=   checkpoint.split("/"					)
				_UpperCamelCase			=   os.path.join(_UpperCamelCase							,  _UpperCamelCase					)
			elif add_prefix:
				_UpperCamelCase			=   checkpoint
				_UpperCamelCase			=   dump_path
			else:
				_UpperCamelCase			=   None
				_UpperCamelCase			=   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]:
				_UpperCamelCase			=   list(tokenizer.pretrained_vocab_files_map.values()					)[0][checkpoint]
				_UpperCamelCase			=   file_path.split(_UpperCamelCase					)[-1][0]
				if next_char == "/":
					_UpperCamelCase			=   os.path.join(_UpperCamelCase							,  _UpperCamelCase					)
					_UpperCamelCase			=   None

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

			_UpperCamelCase			=   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__":
	__lowerCAmelCase			     =       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.""",
	)
	__lowerCAmelCase			     =       parser.parse_args()

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








from maths.prime_factors import prime_factors


def 		lowercase_	(  _UpperCamelCase	):


			'''simple docstring'''







			if not isinstance(_UpperCamelCase							,      _UpperCamelCase	):
						__lowercase			       = F'Input value of [number={number}] must be an integer'
						raise TypeError(_UpperCamelCase	)
			if number < 1:
						raise ValueError('''Input must be a positive integer'''	)
			return -1 if len(prime_factors(_UpperCamelCase	)	) % 2 else 1


if __name__ == "__main__":
	import doctest

	doctest.testmod()


