





"""simple docstring"""


from argparse import ArgumentParser

from . import BaseTransformersCLICommand




def        lowercase__     (       lowercase_      )       ->		Any:




      """simple docstring"""

      return DownloadCommand(args.model		,args.cache_dir		,args.force		,args.trust_remote_code      )



class   __SCREAMING_SNAKE_CASE     (    _UpperCamelCase ):







  '''simple docstring'''


  @staticmethod
  def  __SCREAMING_SNAKE_CASE					(		__a :							ArgumentParser						)		->					Tuple:
        _UpperCamelCase   :						Union[str, Any]    =							parser.add_parser("download"						)
        download_parser.add_argument(
            "--cache-dir"       , type=__a       , default=__a       , 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=__a       , help="Name of the model to download"						)
        download_parser.set_defaults(func=__a						)

  def __init__(		self :							int       , __a :							str       , __a :							str       , __a :							bool       , __a :							bool						)		->					Tuple:
        _UpperCamelCase   :						str    =							model
        _UpperCamelCase   :						Any    =							cache
        _UpperCamelCase   :						List[Any]    =							force
        _UpperCamelCase   :						List[str]    =							trust_remote_code


  def  __SCREAMING_SNAKE_CASE					(		self :							int						)		->					Tuple:
        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_flax_available,
    is_tf_available,
    is_torch_available,
)


lowerCamelCase__						= {
    "configuration_resnet": ["RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "ResNetConfig", "ResNetOnnxConfig"]
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowerCamelCase__						= [
      "RESNET_PRETRAINED_MODEL_ARCHIVE_LIST",
      "ResNetForImageClassification",
      "ResNetModel",
      "ResNetPreTrainedModel",
      "ResNetBackbone",
  ]

try:
  if not is_tf_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowerCamelCase__						= [
      "TF_RESNET_PRETRAINED_MODEL_ARCHIVE_LIST",
      "TFResNetForImageClassification",
      "TFResNetModel",
      "TFResNetPreTrainedModel",
  ]

try:
  if not is_flax_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowerCamelCase__						= [
      "FlaxResNetForImageClassification",
      "FlaxResNetModel",
      "FlaxResNetPreTrainedModel",
  ]

if TYPE_CHECKING:
  from .configuration_resnet import RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP, ResNetConfig, ResNetOnnxConfig

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_resnet import (
        RESNET_PRETRAINED_MODEL_ARCHIVE_LIST,
        ResNetBackbone,
        ResNetForImageClassification,
        ResNetModel,
        ResNetPreTrainedModel,
    )

  try:
    if not is_tf_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_tf_resnet import (
        TF_RESNET_PRETRAINED_MODEL_ARCHIVE_LIST,
        TFResNetForImageClassification,
        TFResNetModel,
        TFResNetPreTrainedModel,
    )

  try:
    if not is_flax_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_flax_resnet import FlaxResNetForImageClassification, FlaxResNetModel, FlaxResNetPreTrainedModel


else:
  import sys

  lowerCamelCase__						= _LazyModule(__name__, globals()["__file__"], _import_structure)
