
def 							SCREAMING_SNAKE_CASE_      (			UpperCamelCase__ ,		UpperCamelCase__		):
      _validate_point(UpperCamelCase__		)
      _validate_point(UpperCamelCase__		)
      if len(UpperCamelCase__		) != len(UpperCamelCase__		):
            raise ValueError('''Both points must be in the same n-dimensional space'''		)

      return float(sum(abs(a - b		) for a, b in zip(UpperCamelCase__ ,		UpperCamelCase__		)		)		)


def 							SCREAMING_SNAKE_CASE_      (			UpperCamelCase__		):
      if point:
            if isinstance(UpperCamelCase__ ,		UpperCamelCase__		):
                  for item in point:
                        if not isinstance(UpperCamelCase__ ,		(int, float)		):
                              UpperCamelCase__    :   Optional[Any]					=				(
                                  '''Expected a list of numbers as input, found '''
                                  f'''{type(UpperCamelCase__		).__name__}'''
                              )
                              raise TypeError(UpperCamelCase__		)
            else:
                  UpperCamelCase__    :   List[str]					=				f'''Expected a list of numbers as input, found {type(UpperCamelCase__		).__name__}'''
                  raise TypeError(UpperCamelCase__		)
      else:
            raise ValueError('''Missing an input'''		)


def 							SCREAMING_SNAKE_CASE_      (			UpperCamelCase__ ,		UpperCamelCase__		):
      _validate_point(UpperCamelCase__		)
      _validate_point(UpperCamelCase__		)
      if len(UpperCamelCase__		) != len(UpperCamelCase__		):
            raise ValueError('''Both points must be in the same n-dimensional space'''		)

      return float(sum(abs(x - y		) for x, y in zip(UpperCamelCase__ ,		UpperCamelCase__		)		)		)


if __name__ == "__main__":
    import doctest

    doctest.testmod()




from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available


lowerCamelCase      ={"configuration_swin": ["SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP", "SwinConfig", "SwinOnnxConfig"]}


try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCamelCase      =[
        "SWIN_PRETRAINED_MODEL_ARCHIVE_LIST",
        "SwinForImageClassification",
        "SwinForMaskedImageModeling",
        "SwinModel",
        "SwinPreTrainedModel",
        "SwinBackbone",
    ]

try:
    if not is_tf_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCamelCase      =[
        "TF_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST",
        "TFSwinForImageClassification",
        "TFSwinForMaskedImageModeling",
        "TFSwinModel",
        "TFSwinPreTrainedModel",
    ]

if TYPE_CHECKING:
    from .configuration_swin import SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP, SwinConfig, SwinOnnxConfig

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_swin import (
            SWIN_PRETRAINED_MODEL_ARCHIVE_LIST,
            SwinBackbone,
            SwinForImageClassification,
            SwinForMaskedImageModeling,
            SwinModel,
            SwinPreTrainedModel,
        )

    try:
        if not is_tf_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_tf_swin import (
            TF_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST,
            TFSwinForImageClassification,
            TFSwinForMaskedImageModeling,
            TFSwinModel,
            TFSwinPreTrainedModel,
        )

else:
    import sys

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


