






'''simple docstring'''

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,
)


SCREAMING_SNAKE_CASE__     =       {
    "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:
     SCREAMING_SNAKE_CASE__     =       ["CLIPTokenizerFast"]

try:
     if not is_vision_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     SCREAMING_SNAKE_CASE__     =       ["CLIPFeatureExtractor"]
     SCREAMING_SNAKE_CASE__     =       ["CLIPImageProcessor"]

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

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

try:
     if not is_flax_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     SCREAMING_SNAKE_CASE__     =       [
         "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

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








'''simple docstring'''

from timeit import timeit







def    lowercase__			(				__UpperCamelCase   )->			int:
      if number < 0:
            raise ValueError("""the value of input must not be negative"""   )
      UpperCamelCase      = 0
      while number:
            number &= number - 1
            result += 1
      return result







def    lowercase__			(				__UpperCamelCase   )->			int:
      if number < 0:
            raise ValueError("""the value of input must not be negative"""   )
      UpperCamelCase      = 0
      while number:
            if number % 2 == 1:
                  result += 1
            number >>= 1
      return result







def    lowercase__			(				)->			None:

      def do_benchmark(__UpperCamelCase   ) -> None:
            UpperCamelCase      = """import __main__ as z"""
            print(F"Benchmark when {number = }:"   )
            print(F"{get_set_bits_count_using_modulo_operator(__UpperCamelCase   ) = }"   )
            UpperCamelCase      = timeit("""z.get_set_bits_count_using_modulo_operator(25)"""		,						setup=__UpperCamelCase   )
            print(F"timeit() runs in {timing} seconds"   )
            print(F"{get_set_bits_count_using_brian_kernighans_algorithm(__UpperCamelCase   ) = }"   )
            UpperCamelCase      = timeit(
                """z.get_set_bits_count_using_brian_kernighans_algorithm(25)"""		,						setup=__UpperCamelCase		,						)
            print(F"timeit() runs in {timing} seconds"   )

      for number in (25, 37, 58, 0):
            do_benchmark(__UpperCamelCase   )
            print()


if __name__ == "__main__":
     import doctest

     doctest.testmod()
     benchmark()
