






"""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()

lowerCamelCase_       			=   logging.get_logger(__name__)


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

def        snake_case   (     A__			,A__			,A__			,A__		):
			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_  :				Any      =      TOKENIZER_CLASSES
			else:
						UpperCAmelCase_  :				Optional[int]      =      {tokenizer_name: getattr(A__			,tokenizer_name + "Fast"		)}

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

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

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

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

									UpperCAmelCase_  :				int      =      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__":
			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)











"""simple docstring"""
from ..utils import DummyObject, requires_backends







class     UpperCamelCase_ (metaclass=__A  ):
	__magic_name__			   =       ['''onnx''']





	def __init__(   self      :				List[Any]			,			*lowerCAmelCase_      :				Dict			,			**lowerCAmelCase_      :				Dict		)		->    Dict:
				requires_backends(self			,			["onnx"]		)





	@classmethod
	def   _SCREAMING_SNAKE_CASE   (   cls      :				Optional[Any]			,			*lowerCAmelCase_      :				Dict			,			**lowerCAmelCase_      :				Union[str, Any]		)		->    int:
				requires_backends(cls			,			["onnx"]		)





	@classmethod
	def   _SCREAMING_SNAKE_CASE   (   cls      :				str			,			*lowerCAmelCase_      :				Optional[Any]			,			**lowerCAmelCase_      :				str		)		->    Optional[Any]:
				requires_backends(cls			,			["onnx"]		)



