






from typing import TYPE_CHECKING

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


snake_case__   :						Dict													=   {
    """configuration_efficientformer""": [
        """EFFICIENTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """EfficientFormerConfig""",
    ]
}

try:
 if not is_vision_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 snake_case__   :						List[Any]													=   ["""EfficientFormerImageProcessor"""]

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 snake_case__   :						Optional[int]													=   [
     """EFFICIENTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
     """EfficientFormerForImageClassification""",
     """EfficientFormerForImageClassificationWithTeacher""",
     """EfficientFormerModel""",
     """EfficientFormerPreTrainedModel""",
 ]

try:
 if not is_tf_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 snake_case__   :						Dict													=   [
     """TF_EFFICIENTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
     """TFEfficientFormerForImageClassification""",
     """TFEfficientFormerForImageClassificationWithTeacher""",
     """TFEfficientFormerModel""",
     """TFEfficientFormerPreTrainedModel""",
 ]

if TYPE_CHECKING:
 from .configuration_efficientformer import EFFICIENTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, EfficientFormerConfig

 try:
  if not is_vision_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .image_processing_efficientformer import EfficientFormerImageProcessor

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_efficientformer import (
      EFFICIENTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
      EfficientFormerForImageClassification,
      EfficientFormerForImageClassificationWithTeacher,
      EfficientFormerModel,
      EfficientFormerPreTrainedModel,
  )
 try:
  if not is_tf_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_tf_efficientformer import (
      TF_EFFICIENTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
      TFEfficientFormerForImageClassification,
      TFEfficientFormerForImageClassificationWithTeacher,
      TFEfficientFormerModel,
      TFEfficientFormerPreTrainedModel,
  )

else:
 import sys

 snake_case__   :						Tuple													=   _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)










"""simple docstring"""






from ..utils import DummyObject, requires_backends



class     UpperCAmelCase    (	metaclass=__SCREAMING_SNAKE_CASE  ):
   A__		:	Optional[int]           =  ['''torch''', '''scipy''']



   def __init__(       self    :	Any							,       *__lowerCamelCase    :	List[Any]							,       **__lowerCamelCase    :	Any				):



     """simple docstring"""
     requires_backends(self							,       ['''torch''', '''scipy''']				)



   @classmethod
   def    __UpperCAmelCase    (       cls    :	Dict							,       *__lowerCamelCase    :	List[str]							,       **__lowerCamelCase    :	Tuple				):



     """simple docstring"""
     requires_backends(cls							,       ['''torch''', '''scipy''']				)





   @classmethod
   def    __UpperCAmelCase    (       cls    :	int							,       *__lowerCamelCase    :	Union[str, Any]							,       **__lowerCamelCase    :	Tuple				):



     """simple docstring"""
     requires_backends(cls							,       ['''torch''', '''scipy''']				)





