

import argparse
import os

import transformers

from .convert_slow_tokenizer import SLOW_TO_FAST_CONVERTERS
from .utils import logging


logging.set_verbosity_info()

A_       : Tuple         =			logging.get_logger(__name__)


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

def 						UpperCamelCase					(lowercase_: int    ,      lowercase_: Optional[Any]    ,      lowercase_: Union[str, Any]    ,      lowercase_: Union[str, Any]					)     ->      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:
		A__							:    Tuple        =		TOKENIZER_CLASSES
	else:
		A__							:    int        =		{tokenizer_name: getattr(SCREAMING_SNAKE_CASE__    ,      tokenizer_name + """Fast"""					)}

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

	for tokenizer_name in tokenizer_names:
		A__							:    Any        =		TOKENIZER_CLASSES[tokenizer_name]

		A__							:    str        =		True
		if checkpoint_name is None:
			A__							:    Dict        =		list(tokenizer_class.max_model_input_sizes.keys()					)
		else:
			A__							:    str        =		[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
			A__							:    int        =		tokenizer_class.from_pretrained(SCREAMING_SNAKE_CASE__    ,      force_download=SCREAMING_SNAKE_CASE__					)

			# 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:
				A__							:    List[str]        =		checkpoint.split("""/"""					)
				A__							:    Union[str, Any]        =		os.path.join(SCREAMING_SNAKE_CASE__    ,      SCREAMING_SNAKE_CASE__					)
			elif add_prefix:
				A__							:    Union[str, Any]        =		checkpoint
				A__							:    str        =		dump_path
			else:
				A__							:    Tuple        =		None
				A__							:    Tuple        =		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]:
				A__							:    Union[str, Any]        =		list(tokenizer.pretrained_vocab_files_map.values()					)[0][checkpoint]
				A__							:    Tuple        =		file_path.split(SCREAMING_SNAKE_CASE__					)[-1][0]
				if next_char == "/":
					A__							:    Tuple        =		os.path.join(SCREAMING_SNAKE_CASE__    ,      SCREAMING_SNAKE_CASE__					)
					A__							:    List[Any]        =		None

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

			A__							:    int        =		tokenizer.save_pretrained(
			    SCREAMING_SNAKE_CASE__    ,      legacy_format=SCREAMING_SNAKE_CASE__    ,      filename_prefix=SCREAMING_SNAKE_CASE__					)
			logger.info(f"""=> File names {file_names}"""					)

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


if __name__ == "__main__":
	A_       : List[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_       : Union[str, Any]         =			parser.parse_args()

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










def 			A__							(    SCREAMING_SNAKE_CASE__ = 200)   ->    int:
  __snake_case:						Optional[int]   =						[1, 2, 5, 10, 20, 50, 100, 200]
  __snake_case:						List[Any]   =						[0] * (pence + 1)
  __snake_case:						int   =						1  # base case: 1 way to make 0 pence

  for coin in coins:
    for i in range(SCREAMING_SNAKE_CASE__					,					pence + 1					,					1):
      number_of_ways[i] += number_of_ways[i - coin]
  return number_of_ways[pence]


if __name__ == "__main__":
      assert solution(200) == 73_682






