import re





def    __lowercase     (						lowerCamelCase					:     str	):
 return [char.split() for char in re.split(R'[^ a-z A-Z 0-9 \s]'  ,  str_	)]





def    __lowercase     (						lowerCamelCase					:     str	):
 UpperCamelCase_					:						Any =					split_input(str_	)
 return "".join(
     [''.join([char.capitalize() for char in sub_str]	) for sub_str in string_split]	)





def    __lowercase     (						lowerCamelCase					:     str  ,  lowerCamelCase					:     bool  ,  lowerCamelCase					:     str	):
 try:
  UpperCamelCase_					:						Optional[Any] =					split_input(lowerCamelCase	)
  if upper:
   UpperCamelCase_					:						int =					''.join(
       [
           separator.join([char.upper() for char in sub_str]	)
           for sub_str in string_split
       ]	)
  else:
   UpperCamelCase_					:						int =					''.join(
       [
           separator.join([char.lower() for char in sub_str]	)
           for sub_str in string_split
       ]	)
  return res_str
 except IndexError:
  return "not valid string"





def    __lowercase     (						lowerCamelCase					:     str	):
 return to_simple_case(lowerCamelCase	)





def    __lowercase     (						lowerCamelCase					:     str	):
 try:
  UpperCamelCase_					:						List[str] =					to_simple_case(lowerCamelCase	)
  return res_str[0].lower() + res_str[1:]
 except IndexError:
  return "not valid string"





def    __lowercase     (						lowerCamelCase					:     str  ,  lowerCamelCase					:     bool	):
 return to_complex_case(lowerCamelCase  ,  lowerCamelCase  ,  '_'	)





def    __lowercase     (						lowerCamelCase					:     str  ,  lowerCamelCase					:     bool	):
 return to_complex_case(lowerCamelCase  ,  lowerCamelCase  ,  '-'	)


if __name__ == "__main__":
   __import__('doctest').testmod()




from typing import TYPE_CHECKING

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


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

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

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

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

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



