





'''simple docstring'''

import json
from typing import List, Optional, Tuple

from tokenizers import pre_tokenizers, processors

from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_mvp import MvpTokenizer


UpperCAmelCase					:		Tuple		=							logging.get_logger(__name__)


UpperCAmelCase					:		Tuple		=							{'vocab_file': 'vocab.json', 'merges_file': 'merges.txt', 'tokenizer_file': 'tokenizer.json'}

# See all MVP models at https://huggingface.co/models?filter=mvp
UpperCAmelCase					:		List[Any]		=							{
    'vocab_file': {
        'RUCAIBox/mvp': 'https://huggingface.co/RUCAIBox/mvp/resolve/main/vocab.json',
    },
    'added_tokens.json': {
        'RUCAIBox/mvp': 'https://huggingface.co/RUCAIBox/mvp/resolve/main/added_tokens.json',
    },
    'merges_file': {
        'RUCAIBox/mvp': 'https://huggingface.co/RUCAIBox/mvp/resolve/main/merges.txt',
    },
    'tokenizer_file': {
        'RUCAIBox/mvp': 'https://huggingface.co/RUCAIBox/mvp/resolve/main/tokenizer.json',
    },
}

UpperCAmelCase					:		Optional[Any]		=							{
    'RUCAIBox/mvp': 1_0_2_4,
}





class lowerCamelCase						(a__					):
  _lowercase  :	str       					=				VOCAB_FILES_NAMES
  _lowercase  :	str       					=				PRETRAINED_VOCAB_FILES_MAP
  _lowercase  :	Tuple       					=				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  _lowercase  :	str       					=				["""input_ids""", """attention_mask"""]
  _lowercase  :	List[Any]       					=				MvpTokenizer







  def __init__(		self     ,     lowercase__=None     ,     lowercase__=None     ,     lowercase__=None     ,     lowercase__="replace"     ,     lowercase__="<s>"     ,     lowercase__="</s>"     ,     lowercase__="</s>"     ,     lowercase__="<s>"     ,     lowercase__="<unk>"     ,     lowercase__="<pad>"     ,     lowercase__="<mask>"     ,     lowercase__=False     ,     lowercase__=True     ,     **lowercase__     ,     )		->						int:






        """simple docstring"""





        super().__init__(
            lowercase__     ,     lowercase__     ,     tokenizer_file=lowercase__     ,     errors=lowercase__     ,     bos_token=lowercase__     ,     eos_token=lowercase__     ,     sep_token=lowercase__     ,     cls_token=lowercase__     ,     unk_token=lowercase__     ,     pad_token=lowercase__     ,     mask_token=lowercase__     ,     add_prefix_space=lowercase__     ,     trim_offsets=lowercase__     ,     **lowercase__     ,     )

        _snake_case		:	Tuple					     =     json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()		)
        if pre_tok_state.get('''add_prefix_space'''     ,     lowercase__		) != add_prefix_space:
              _snake_case		:	Optional[int]					     =     getattr(lowercase__     ,     pre_tok_state.pop('''type'''		)		)
              _snake_case		:	Union[str, Any]					     =     add_prefix_space
              _snake_case		:	List[str]					     =     pre_tok_class(**lowercase__		)

        _snake_case		:	List[str]					     =     add_prefix_space

        # the pre_tokenizer is already updated in the GPT2TokenizerFast `__init__`
        _snake_case		:	Any					     =     '''post_processor'''
        _snake_case		:	List[str]					     =     getattr(self.backend_tokenizer     ,     lowercase__     ,     lowercase__		)
        if tokenizer_component_instance:
              _snake_case		:	Optional[Any]					     =     json.loads(tokenizer_component_instance.__getstate__()		)

              # The lists 'sep' and 'cls' must be cased in tuples for the object `post_processor_class`
              if "sep" in state:
                    _snake_case		:	Optional[Any]					     =     tuple(state['''sep''']		)
              if "cls" in state:
                    _snake_case		:	int					     =     tuple(state['''cls''']		)

              _snake_case		:	Tuple					     =     False

              if state.get('''add_prefix_space'''     ,     lowercase__		) != add_prefix_space:
                    _snake_case		:	int					     =     add_prefix_space
                    _snake_case		:	List[str]					     =     True

              if state.get('''trim_offsets'''     ,     lowercase__		) != trim_offsets:
                    _snake_case		:	int					     =     trim_offsets
                    _snake_case		:	Union[str, Any]					     =     True

              if changes_to_apply:
                    _snake_case		:	Optional[Any]					     =     getattr(lowercase__     ,     state.pop('''type'''		)		)
                    _snake_case		:	Union[str, Any]					     =     component_class(**lowercase__		)
                    setattr(self.backend_tokenizer     ,     lowercase__     ,     lowercase__		)







  @property
  def 				UpperCAmelCase_				(		self		)		->						str:






        """simple docstring"""





        if self._mask_token is None:
              if self.verbose:
                    logger.error('''Using mask_token, but it is not set yet.'''		)
              return None
        return str(self._mask_token		)







  @mask_token.setter
  def 				UpperCAmelCase_				(		self     ,     lowercase__		)		->						Union[str, Any]:






        """simple docstring"""





        _snake_case		:	Union[str, Any]					     =     AddedToken(lowercase__     ,     lstrip=lowercase__     ,     rstrip=lowercase__		) if isinstance(lowercase__     ,     lowercase__		) else value
        _snake_case		:	List[str]					     =     value







  def 				UpperCAmelCase_				(		self     ,     *lowercase__     ,     **lowercase__		)		->						BatchEncoding:






        """simple docstring"""





        _snake_case		:	Optional[int]					     =     kwargs.get('''is_split_into_words'''     ,     lowercase__		)

        if is_split_into_words and not self.add_prefix_space:
              raise ValueError(
                  F'''You need to instantiate {self.__class__.__name__} with add_prefix_space=True '''
                  '''to use it with pretokenized inputs.'''		)

        return super()._batch_encode_plus(*lowercase__     ,     **lowercase__		)







  def 				UpperCAmelCase_				(		self     ,     *lowercase__     ,     **lowercase__		)		->						BatchEncoding:






        """simple docstring"""





        _snake_case		:	str					     =     kwargs.get('''is_split_into_words'''     ,     lowercase__		)

        if is_split_into_words and not self.add_prefix_space:
              raise ValueError(
                  F'''You need to instantiate {self.__class__.__name__} with add_prefix_space=True '''
                  '''to use it with pretokenized inputs.'''		)

        return super()._encode_plus(*lowercase__     ,     **lowercase__		)







  def 				UpperCAmelCase_				(		self     ,     lowercase__     ,     lowercase__ = None		)		->						Tuple[str]:






        """simple docstring"""





        _snake_case		:	Tuple					     =     self._tokenizer.model.save(lowercase__     ,     name=lowercase__		)
        return tuple(lowercase__		)







  def 				UpperCAmelCase_				(		self     ,     lowercase__     ,     lowercase__=None		)		->						List[Any]:






        """simple docstring"""





        _snake_case		:	int					     =     [self.bos_token_id] + token_ids_a + [self.eos_token_id]
        if token_ids_a is None:
              return output

        return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]







  def 				UpperCAmelCase_				(		self     ,     lowercase__     ,     lowercase__ = None		)		->						List[int]:






        """simple docstring"""





        _snake_case		:	Optional[int]					     =     [self.sep_token_id]
        _snake_case		:	str					     =     [self.cls_token_id]

        if token_ids_a is None:
              return len(cls + token_ids_a + sep		) * [0]
        return len(cls + token_ids_a + sep + sep + token_ids_a + sep		) * [0]









'''simple docstring'''

from argparse import ArgumentParser

from .add_new_model import AddNewModelCommand
from .add_new_model_like import AddNewModelLikeCommand
from .convert import ConvertCommand
from .download import DownloadCommand
from .env import EnvironmentCommand
from .lfs import LfsCommands
from .pt_to_tf import PTtoTFCommand
from .run import RunCommand
from .serving import ServeCommand
from .user import UserCommands




def    _a    (							):





      """simple docstring"""



      _snake_case		:	List[Any]					     =     ArgumentParser('''Transformers CLI tool'''			,      usage='''transformers-cli <command> [<args>]'''	)
      _snake_case		:	List[str]					     =     parser.add_subparsers(help='''transformers-cli command helpers'''	)

      # Register commands
      ConvertCommand.register_subcommand(lowerCAmelCase_	)
      DownloadCommand.register_subcommand(lowerCAmelCase_	)
      EnvironmentCommand.register_subcommand(lowerCAmelCase_	)
      RunCommand.register_subcommand(lowerCAmelCase_	)
      ServeCommand.register_subcommand(lowerCAmelCase_	)
      UserCommands.register_subcommand(lowerCAmelCase_	)
      AddNewModelCommand.register_subcommand(lowerCAmelCase_	)
      AddNewModelLikeCommand.register_subcommand(lowerCAmelCase_	)
      LfsCommands.register_subcommand(lowerCAmelCase_	)
      PTtoTFCommand.register_subcommand(lowerCAmelCase_	)

      # Let's go
      _snake_case		:	str					     =     parser.parse_args()

      if not hasattr(lowerCAmelCase_			,      '''func'''	):
            parser.print_help()
            exit(1	)

      # Run
      _snake_case		:	Union[str, Any]					     =     args.func(lowerCAmelCase_	)
      service.run()


if __name__ == "__main__":
   main()


