






'''simple docstring'''

def 				snake_case       (  a_				:			str     , a_				:			Optional[int]						)							->					Any:





      """simple docstring"""

      UpperCamelCase_					: Tuple            =				(boundary[1] - boundary[0]) / steps
      UpperCamelCase_					: Dict            =				boundary[0]
      UpperCamelCase_					: Any            =				boundary[1]
      UpperCamelCase_					: Union[str, Any]            =				make_points(a_     , a_     , a_						)
      UpperCamelCase_					: Any            =				0.0
      y += (h / 2.0) * f(a_						)
      for i in x_i:
            # print(i)
            y += h * f(a_						)
      y += (h / 2.0) * f(a_						)
      return y



def 				snake_case       (  a_				:			Tuple     , a_				:			Any     , a_				:			Tuple						)							->					Tuple:





      """simple docstring"""

      UpperCamelCase_					: Optional[int]            =				a + h
      while x < (b - h):
            yield x
            UpperCamelCase_					: List[str]            =				x + h



def 				snake_case       (  a_				:			List[str]						)							->					Tuple:  # enter your function here





      """simple docstring"""

      UpperCamelCase_					: int            =				(x - 0) * (x - 0)
      return y



def 				snake_case       (  )							->					Dict:





      """simple docstring"""

      UpperCamelCase_					: Optional[Any]            =				0.0  # Lower bound of integration
      UpperCamelCase_					: Optional[int]            =				1.0  # Upper bound of integration
      UpperCamelCase_					: Optional[Any]            =				10.0  # define number of steps or resolution
      UpperCamelCase_					: Optional[Any]            =				[a, b]  # define boundary of integration
      UpperCamelCase_					: Any            =				method_a(a_     , a_						)
      print(f"y = {y}"						)


if __name__ == "__main__":
      main()














'''simple docstring'''

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


UpperCamelCase      					={
    "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:
      UpperCamelCase      					=[
          "CLAP_PRETRAINED_MODEL_ARCHIVE_LIST",
          "ClapModel",
          "ClapPreTrainedModel",
          "ClapTextModel",
          "ClapTextModelWithProjection",
          "ClapAudioModel",
          "ClapAudioModelWithProjection",
      ]
      UpperCamelCase      					=["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

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






