






import argparse
import os

import transformers

from .convert_slow_tokenizer import SLOW_TO_FAST_CONVERTERS
from .utils import logging


logging.set_verbosity_info()

lowerCamelCase     :							Optional[Any]    =logging.get_logger(__name__)


lowerCamelCase     :							List[Any]    ={name: getattr(transformers, name + '''Fast''') for name in SLOW_TO_FAST_CONVERTERS}







def 		SCREAMING_SNAKE_CASE							( __lowerCAmelCase ,   __lowerCAmelCase ,   __lowerCAmelCase ,   __lowerCAmelCase      )			->     Any:
     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__      :       List[str]	    =  TOKENIZER_CLASSES
     else:
          UpperCamelCase__      :       Dict	    =  {tokenizer_name: getattr(__lowerCAmelCase ,   tokenizer_name + "Fast"      )}

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

     for tokenizer_name in tokenizer_names:
          UpperCamelCase__      :       List[Any]	    =  TOKENIZER_CLASSES[tokenizer_name]

          UpperCamelCase__      :       List[Any]	    =  True
          if checkpoint_name is None:
               UpperCamelCase__      :       str	    =  list(tokenizer_class.max_model_input_sizes.keys()      )
          else:
               UpperCamelCase__      :       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__      :       Optional[Any]	    =  tokenizer_class.from_pretrained(__lowerCAmelCase ,   force_download=__lowerCAmelCase      )

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

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

               UpperCamelCase__      :       List[str]	    =  tokenizer.save_pretrained(
                   __lowerCAmelCase ,   legacy_format=__lowerCAmelCase ,   filename_prefix=__lowerCAmelCase      )
               logger.info(f'=> File names {file_names}'      )

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


if __name__ == "__main__":
 lowerCamelCase     :							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.''',
 )
 lowerCamelCase     :							Dict    =parser.parse_args()

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







def 		SCREAMING_SNAKE_CASE							( __lowerCAmelCase      )			->     int:
     assert isinstance(__lowerCAmelCase ,   __lowerCAmelCase      ), f'The input value of [n={number}] is not an integer'

     if number == 1:
          return 2
     elif number < 1:
          UpperCamelCase__      :       List[Any]	    =  f'The input value of [n={number}] has to be > 0'
          raise ValueError(__lowerCAmelCase      )
     else:
          UpperCamelCase__      :       Optional[Any]	    =  sylvester(number - 1      )
          UpperCamelCase__      :       str	    =  num - 1
          UpperCamelCase__      :       int	    =  num
          return lower * upper + 1


if __name__ == "__main__":
 print(F"""The 8th number in Sylvester's sequence: {sylvester(8)}""")