

def 						_snake_case(   SCREAMING_SNAKE_CASE__      :     list				)							->				list:





    '''simple docstring'''






    if len(SCREAMING_SNAKE_CASE__				) <= 1:
        return [tuple(SCREAMING_SNAKE_CASE__				)]

    A__   				=       []

    def generate(SCREAMING_SNAKE_CASE__      :     int   ,      SCREAMING_SNAKE_CASE__      :     list				):
        if k == 1:
            res.append(tuple(arr[:]				)				)
            return

        generate(k - 1   ,      SCREAMING_SNAKE_CASE__				)

        for i in range(k - 1				):
            if k % 2 == 0:  # k is even
                A__				,						A__   				=       arr[k - 1], arr[i]
            else:  # k is odd
                A__				,						A__   				=       arr[k - 1], arr[0]
            generate(k - 1   ,      SCREAMING_SNAKE_CASE__				)

    generate(len(SCREAMING_SNAKE_CASE__				)   ,      SCREAMING_SNAKE_CASE__				)
    return res


if __name__ == "__main__":
     lowercase_			=  input("Enter numbers separated by a comma:\n").strip()
     lowercase_			=  [int(item) for item in user_input.split(",")]
     print(heaps(arr))




from ...utils import (
    OptionalDependencyNotAvailable,
    is_torch_available,
    is_transformers_available,
    is_transformers_version,
)


try:
     if not (is_transformers_available() and is_torch_available()):
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     from ...utils.dummy_torch_and_transformers_objects import (
         ImageTextPipelineOutput,
         UniDiffuserPipeline,
     )
else:
     from .modeling_text_decoder import UniDiffuserTextDecoder
     from .modeling_uvit import UniDiffuserModel, UTransformeraDModel
     from .pipeline_unidiffuser import ImageTextPipelineOutput, UniDiffuserPipeline

