


'''simple docstring'''






from argparse import ArgumentParser

from . import BaseTransformersCLICommand


def    _snake_case  (	A			)		->       Optional[Any]:
							return DownloadCommand(args.model					,       args.cache_dir					,       args.force					,       args.trust_remote_code			)






class 						a__							(				a__    ):





							'''simple docstring'''






							@staticmethod
							def     __SCREAMING_SNAKE_CASE				(						lowerCamelCase_  )			->				Dict:
														lowerCAmelCase__			  =      parser.add_parser('''download'''  )
														download_parser.add_argument(
														    '''--cache-dir'''   ,       type=lowerCamelCase_   ,       default=lowerCamelCase_   ,       help='''Path to location to store the models'''  )
														download_parser.add_argument(
														    '''--force'''   ,       action='''store_true'''   ,       help='''Force the model to be download even if already in cache-dir'''  )
														download_parser.add_argument(
														    '''--trust-remote-code'''   ,       action='''store_true'''   ,       help='''Whether or not to allow for custom models defined on the Hub in their own modeling files. Use only if you\'ve reviewed the code as it will execute on your local machine'''   ,       )
														download_parser.add_argument('''model'''   ,       type=lowerCamelCase_   ,       help='''Name of the model to download'''  )
														download_parser.set_defaults(func=lowerCamelCase_  )







							def __init__(						self   ,       lowerCamelCase_   ,       lowerCamelCase_   ,       lowerCamelCase_   ,       lowerCamelCase_  )			->				Optional[int]:
														lowerCAmelCase__			  =      model
														lowerCAmelCase__			  =      cache
														lowerCAmelCase__			  =      force
														lowerCAmelCase__			  =      trust_remote_code







							def     __SCREAMING_SNAKE_CASE				(						self  )			->				List[Any]:
														from ..models.auto import AutoModel, AutoTokenizer

														AutoModel.from_pretrained(
														    self._model   ,       cache_dir=self._cache   ,       force_download=self._force   ,       trust_remote_code=self._trust_remote_code  )
														AutoTokenizer.from_pretrained(
														    self._model   ,       cache_dir=self._cache   ,       force_download=self._force   ,       trust_remote_code=self._trust_remote_code  )



"""simple docstring"""



from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__snake_case       =       {
    """configuration_bigbird_pegasus""": [
        """BIGBIRD_PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """BigBirdPegasusConfig""",
        """BigBirdPegasusOnnxConfig""",
    ],
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __snake_case       =       [
      """BIGBIRD_PEGASUS_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """BigBirdPegasusForCausalLM""",
      """BigBirdPegasusForConditionalGeneration""",
      """BigBirdPegasusForQuestionAnswering""",
      """BigBirdPegasusForSequenceClassification""",
      """BigBirdPegasusModel""",
      """BigBirdPegasusPreTrainedModel""",
  ]


if TYPE_CHECKING:
  from .configuration_bigbird_pegasus import (
      BIGBIRD_PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP,
      BigBirdPegasusConfig,
      BigBirdPegasusOnnxConfig,
  )

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_bigbird_pegasus import (
        BIGBIRD_PEGASUS_PRETRAINED_MODEL_ARCHIVE_LIST,
        BigBirdPegasusForCausalLM,
        BigBirdPegasusForConditionalGeneration,
        BigBirdPegasusForQuestionAnswering,
        BigBirdPegasusForSequenceClassification,
        BigBirdPegasusModel,
        BigBirdPegasusPreTrainedModel,
    )


else:
  import sys

  __snake_case       =       _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)





