





from typing import TYPE_CHECKING

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


_UpperCamelCase    =	{'''configuration_regnet''': ['''REGNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''RegNetConfig''']}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _UpperCamelCase    =	[
         '''REGNET_PRETRAINED_MODEL_ARCHIVE_LIST''',
         '''RegNetForImageClassification''',
         '''RegNetModel''',
         '''RegNetPreTrainedModel''',
     ]

try:
     if not is_tf_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _UpperCamelCase    =	[
         '''TF_REGNET_PRETRAINED_MODEL_ARCHIVE_LIST''',
         '''TFRegNetForImageClassification''',
         '''TFRegNetModel''',
         '''TFRegNetPreTrainedModel''',
     ]

try:
     if not is_flax_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _UpperCamelCase    =	[
         '''FlaxRegNetForImageClassification''',
         '''FlaxRegNetModel''',
         '''FlaxRegNetPreTrainedModel''',
     ]


if TYPE_CHECKING:
     from .configuration_regnet import REGNET_PRETRAINED_CONFIG_ARCHIVE_MAP, RegNetConfig

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_regnet import (
              REGNET_PRETRAINED_MODEL_ARCHIVE_LIST,
              RegNetForImageClassification,
              RegNetModel,
              RegNetPreTrainedModel,
          )

     try:
          if not is_tf_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_tf_regnet import (
              TF_REGNET_PRETRAINED_MODEL_ARCHIVE_LIST,
              TFRegNetForImageClassification,
              TFRegNetModel,
              TFRegNetPreTrainedModel,
          )

     try:
          if not is_flax_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_flax_regnet import (
              FlaxRegNetForImageClassification,
              FlaxRegNetModel,
              FlaxRegNetPreTrainedModel,
          )


else:
     import sys

     _UpperCamelCase    =	_LazyModule(__name__, globals()['''__file__'''], _import_structure)








import warnings

from ...utils import logging
from .image_processing_maskformer import MaskFormerImageProcessor


_UpperCamelCase    =	logging.get_logger(__name__)




class 			_lowerCamelCase	(      a      ):



      """simple docstring"""






      def __init__(	self			,  *UpperCAmelCase			,  **UpperCAmelCase				)    ->				None:






        '''simple docstring'''






        warnings.warn(
            "The class MaskFormerFeatureExtractor is deprecated and will be removed in version 5 of Transformers."
            " Please use MaskFormerImageProcessor instead."			,  UpperCAmelCase			,  )
        super().__init__(*UpperCAmelCase			,  **UpperCAmelCase				)

