'''simple docstring'''


import warnings

from ...utils import logging
from .image_processing_mobilenet_va import MobileNetVaImageProcessor


snake_case__     :			Any      			=  logging.get_logger(__name__)






class      __SCREAMING_SNAKE_CASE						(       lowerCamelCase_       ):







  '''simple docstring'''






  def __init__( self      ,		*snake_case_      ,		**snake_case_						):




       '''simple docstring'''

       warnings.warn(
           'The class MobileNetV2FeatureExtractor is deprecated and will be removed in version 5 of Transformers.'
           ' Please use MobileNetV2ImageProcessor instead.'      ,		snake_case_      ,		)
       super().__init__(*snake_case_      ,		**snake_case_						)







'''simple docstring'''


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


snake_case__     :			Optional[Any]      			=  {'''configuration_nat''': ['''NAT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''NatConfig''']}


try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 snake_case__     :			Tuple      			=  [
     '''NAT_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''NatForImageClassification''',
     '''NatModel''',
     '''NatPreTrainedModel''',
     '''NatBackbone''',
 ]

if TYPE_CHECKING:
 from .configuration_nat import NAT_PRETRAINED_CONFIG_ARCHIVE_MAP, NatConfig

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_nat import (
      NAT_PRETRAINED_MODEL_ARCHIVE_LIST,
      NatBackbone,
      NatForImageClassification,
      NatModel,
      NatPreTrainedModel,
  )

else:
 import sys

 snake_case__     :			int      			=  _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)






