






from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_torch_available,
)


__magic_name__   :  Optional[int]        =							{
    '''configuration_resnet''': ['''RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ResNetConfig''', '''ResNetOnnxConfig''']
}

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

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

try:
       if not is_flax_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __magic_name__   :  int        =							[
           '''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

       __magic_name__   :  Union[str, Any]        =							_LazyModule(__name__, globals()['''__file__'''], _import_structure)











from pathlib import Path

import fire
def 		lowercase__  (				_UpperCamelCase       ,							_UpperCamelCase       ,							_UpperCamelCase) ->			Optional[int]:
      """simple docstring"""

      UpperCamelCase					       =  Path(_UpperCamelCase)
      UpperCamelCase					       =  Path(_UpperCamelCase)
      dest_dir.mkdir(exist_ok=_UpperCamelCase)
      for path in src_dir.iterdir():
            UpperCamelCase					       =  [x.rstrip() for x in list(path.open().readlines())][:n]
            UpperCamelCase					       =  dest_dir.joinpath(path.name)
            print(_UpperCamelCase)
            dest_path.open('w').write('\n'.join(_UpperCamelCase))


if __name__ == "__main__":
       fire.Fire(minify)



