
from typing import TYPE_CHECKING

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


__lowerCamelCase							=       {
    """configuration_efficientformer""": [
        """EFFICIENTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """EfficientFormerConfig""",
    ]
}

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

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

try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   __lowerCamelCase							=       [
       """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

   __lowerCamelCase							=       _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)









def    snake_case_     (  snake_case			,							snake_case     )  ->				str:
       if number < 0 or shift_amount < 0:
              raise ValueError('both inputs must be positive integers'     )

       lowercase__:   str  			=   str(bin(snake_case     )     )
       binary_number += "0" * shift_amount
       return binary_number




def    snake_case_     (  snake_case			,							snake_case     )  ->				str:
       if number < 0 or shift_amount < 0:
              raise ValueError('both inputs must be positive integers'     )

       lowercase__:   Optional[Any]  			=   str(bin(snake_case     )     )[2:]
       if shift_amount >= len(snake_case     ):
              return "0b0"
       lowercase__:   Optional[int]  			=   binary_number[: len(snake_case     ) - shift_amount]
       return "0b" + shifted_binary_number




def    snake_case_     (  snake_case			,							snake_case     )  ->				str:
       if number >= 0:  # Get binary representation of positive number
              lowercase__:   Union[str, Any]  			=   '0' + str(bin(snake_case     )     ).strip('-'     )[2:]
       else:  # Get binary (2's complement) representation of negative number
              lowercase__:   Dict  			=   len(bin(snake_case     )[3:]     )  # Find 2's complement of number
              lowercase__:   int  			=   bin(abs(snake_case     ) - (1 << binary_number_length)     )[3:]
              lowercase__:   Any  			=   (
                  '1' + '0' * (binary_number_length - len(snake_case     )) + binary_number
              )

       if shift_amount >= len(snake_case     ):
              return "0b" + binary_number[0] * len(snake_case     )
       return (
           "0b"
           + binary_number[0] * shift_amount
           + binary_number[: len(snake_case     ) - shift_amount]
       )


if __name__ == "__main__":
 import doctest

 doctest.testmod()


