from typing import TYPE_CHECKING

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


_lowerCAmelCase  :List[Any]  				=    {
    """configuration_clip""": [
        """CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """CLIPConfig""",
        """CLIPOnnxConfig""",
        """CLIPTextConfig""",
        """CLIPVisionConfig""",
    ],
    """processing_clip""": ["""CLIPProcessor"""],
    """tokenization_clip""": ["""CLIPTokenizer"""],
}

try:
 if not is_tokenizers_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _lowerCAmelCase  :Optional[Any]  				=    ["""CLIPTokenizerFast"""]

try:
 if not is_vision_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _lowerCAmelCase  :Optional[Any]  				=    ["""CLIPFeatureExtractor"""]
 _lowerCAmelCase  :List[Any]  				=    ["""CLIPImageProcessor"""]

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _lowerCAmelCase  :Union[str, Any]  				=    [
     """CLIP_PRETRAINED_MODEL_ARCHIVE_LIST""",
     """CLIPModel""",
     """CLIPPreTrainedModel""",
     """CLIPTextModel""",
     """CLIPTextModelWithProjection""",
     """CLIPVisionModel""",
     """CLIPVisionModelWithProjection""",
 ]

try:
 if not is_tf_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _lowerCAmelCase  :Optional[int]  				=    [
     """TF_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST""",
     """TFCLIPModel""",
     """TFCLIPPreTrainedModel""",
     """TFCLIPTextModel""",
     """TFCLIPVisionModel""",
 ]

try:
 if not is_flax_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _lowerCAmelCase  :Dict  				=    [
     """FlaxCLIPModel""",
     """FlaxCLIPPreTrainedModel""",
     """FlaxCLIPTextModel""",
     """FlaxCLIPTextPreTrainedModel""",
     """FlaxCLIPVisionModel""",
     """FlaxCLIPVisionPreTrainedModel""",
 ]


if TYPE_CHECKING:
 from .configuration_clip import (
     CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
     CLIPConfig,
     CLIPOnnxConfig,
     CLIPTextConfig,
     CLIPVisionConfig,
 )
 from .processing_clip import CLIPProcessor
 from .tokenization_clip import CLIPTokenizer

 try:
  if not is_tokenizers_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .tokenization_clip_fast import CLIPTokenizerFast

 try:
  if not is_vision_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .feature_extraction_clip import CLIPFeatureExtractor
  from .image_processing_clip import CLIPImageProcessor

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_clip import (
      CLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
      CLIPModel,
      CLIPPreTrainedModel,
      CLIPTextModel,
      CLIPTextModelWithProjection,
      CLIPVisionModel,
      CLIPVisionModelWithProjection,
  )

 try:
  if not is_tf_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_tf_clip import (
      TF_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
      TFCLIPModel,
      TFCLIPPreTrainedModel,
      TFCLIPTextModel,
      TFCLIPVisionModel,
  )

 try:
  if not is_flax_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_flax_clip import (
      FlaxCLIPModel,
      FlaxCLIPPreTrainedModel,
      FlaxCLIPTextModel,
      FlaxCLIPTextPreTrainedModel,
      FlaxCLIPVisionModel,
      FlaxCLIPVisionPreTrainedModel,
  )


else:
 import sys

 _lowerCAmelCase  :str  				=    _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)




'''simple docstring'''





def     __lowerCAmelCase						(       a_       ,      a_		)      ->	str:





     '''simple docstring'''





     if number < 0 or shift_amount < 0:
          raise ValueError('both inputs must be positive integers'		)

     SCREAMING_SNAKE_CASE					:			str    	=       str(bin(a_		)		)
     binary_number += "0" * shift_amount
     return binary_number


def     __lowerCAmelCase						(       a_       ,      a_		)      ->	str:





     '''simple docstring'''





     if number < 0 or shift_amount < 0:
          raise ValueError('both inputs must be positive integers'		)

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


def     __lowerCAmelCase						(       a_       ,      a_		)      ->	str:





     '''simple docstring'''





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

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


if __name__ == "__main__":
 import doctest

 doctest.testmod()



