





from typing import TYPE_CHECKING

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


_UpperCamelCase							=			{
    'configuration_efficientformer': [
        'EFFICIENTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'EfficientFormerConfig',
    ]
}

try:
     if not is_vision_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _UpperCamelCase							=			['EfficientFormerImageProcessor']

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _UpperCamelCase							=			[
         'EFFICIENTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
         'EfficientFormerForImageClassification',
         'EfficientFormerForImageClassificationWithTeacher',
         'EfficientFormerModel',
         'EfficientFormerPreTrainedModel',
     ]

try:
     if not is_tf_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _UpperCamelCase							=			[
         '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

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





'''simple docstring'''
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


UpperCAmelCase_			:  Any										=   {
    'configuration_maskformer': ['MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MaskFormerConfig'],
    'configuration_maskformer_swin': ['MaskFormerSwinConfig'],
}

try:
 if not is_vision_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 UpperCAmelCase_			:  Tuple										=   ['MaskFormerFeatureExtractor']
 UpperCAmelCase_			:  List[str]										=   ['MaskFormerImageProcessor']


try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 UpperCAmelCase_			:  Optional[Any]										=   [
     'MASKFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
     'MaskFormerForInstanceSegmentation',
     'MaskFormerModel',
     'MaskFormerPreTrainedModel',
 ]
 UpperCAmelCase_			:  Optional[int]										=   [
     'MaskFormerSwinBackbone',
     'MaskFormerSwinModel',
     'MaskFormerSwinPreTrainedModel',
 ]

if TYPE_CHECKING:
 from .configuration_maskformer import MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, MaskFormerConfig
 from .configuration_maskformer_swin import MaskFormerSwinConfig

 try:
  if not is_vision_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .feature_extraction_maskformer import MaskFormerFeatureExtractor
  from .image_processing_maskformer import MaskFormerImageProcessor
 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_maskformer import (
      MASKFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
      MaskFormerForInstanceSegmentation,
      MaskFormerModel,
      MaskFormerPreTrainedModel,
  )
  from .modeling_maskformer_swin import (
      MaskFormerSwinBackbone,
      MaskFormerSwinModel,
      MaskFormerSwinPreTrainedModel,
  )


else:
 import sys

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






