


"""simple docstring"""
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


SCREAMING_SNAKE_CASE :    Optional[Any]									=				{
    """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:
			SCREAMING_SNAKE_CASE :    Tuple									=				[
			    """CLAP_PRETRAINED_MODEL_ARCHIVE_LIST""",
			    """ClapModel""",
			    """ClapPreTrainedModel""",
			    """ClapTextModel""",
			    """ClapTextModelWithProjection""",
			    """ClapAudioModel""",
			    """ClapAudioModelWithProjection""",
			]
			SCREAMING_SNAKE_CASE :    Any									=				["""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

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







'''simple docstring'''







def 					UpperCAmelCase_		(__a      :    list ,	__a      :    list ,	__a      :    int ):






   """simple docstring"""

   _a				:	Optional[Any]			=   len(__a )
   _a				:	int			=   [[0] * n for i in range(__a )]
   for i in range(__a ):
      _a				:	Tuple			=   y_points[i]

   for i in range(2 ,	__a ):
      for j in range(__a ,	__a ):
         _a				:	Tuple			=   (
             (xa - x_points[j - i + 1]) * q[j][i - 1]
             - (xa - x_points[j]) * q[j - 1][i - 1]
         ) / (x_points[j] - x_points[j - i + 1])

   return [q[n - 1][n - 1], q]


if __name__ == "__main__":
  import doctest

  doctest.testmod()



