

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


a_    :						int    		=      {
    "configuration_clap": [
        "CLAP_PRETRAINED_MODEL_ARCHIVE_LIST",
        "ClapAudioConfig",
        "ClapConfig",
        "ClapTextConfig",
    ],
    "processing_clap": ["ClapProcessor"],
}

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      a_    :						Union[str, Any]    		=      [
          "CLAP_PRETRAINED_MODEL_ARCHIVE_LIST",
          "ClapModel",
          "ClapPreTrainedModel",
          "ClapTextModel",
          "ClapTextModelWithProjection",
          "ClapAudioModel",
          "ClapAudioModelWithProjection",
      ]
      a_    :						Dict    		=      ["ClapFeatureExtractor"]

if TYPE_CHECKING:
      from .configuration_clap import (
          CLAP_PRETRAINED_MODEL_ARCHIVE_LIST,
          ClapAudioConfig,
          ClapConfig,
          ClapTextConfig,
      )
      from .processing_clap import ClapProcessor

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .feature_extraction_clap import ClapFeatureExtractor
            from .modeling_clap import (
                CLAP_PRETRAINED_MODEL_ARCHIVE_LIST,
                ClapAudioModel,
                ClapAudioModelWithProjection,
                ClapModel,
                ClapPreTrainedModel,
                ClapTextModel,
                ClapTextModelWithProjection,
            )


else:
      import sys

      a_    :						Optional[Any]    		=      _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)




import numpy as np


def        __lowerCAmelCase    (       _UpperCamelCase		:  np.ndarray	)		->							np.ndarray:
 '''simple docstring'''


 return 1 / (1 + np.exp(-vector	))


def        __lowerCAmelCase    (       _UpperCamelCase		:  np.ndarray	)		->							np.ndarray:
 '''simple docstring'''


 return vector * sigmoid(_UpperCamelCase	)


if __name__ == "__main__":
      import doctest

      doctest.testmod()

