(arrays: Sequence[ArrayType], backend: str)
return backend
Find out what backend we should use, dipatching based on the first
    array if ``backend='auto'`` is specified.
Find out what backend we should use, dipatching based on the first
    array if ``backend='auto'`` is specified.
Find out what backend we should use dipatching based on the first array if backend = auto is specified .
def parse_backend(arrays: Sequence[ArrayType], backend: str) -> str:
    """Find out what backend we should use, dipatching based on the first
    array if ``backend='auto'`` is specified.
    """
    if backend != "auto":
        return backend
    backend = infer_backend(arrays[0])

    # some arrays will be defined in modules that don't implement tensordot
    # etc. so instead default to numpy
    if not backends.has_tensordot(backend):
        return "numpy"

    return backend
def parse_backend ( arrays : Sequence [ ArrayType ] , backend : str ) -> str : if backend != "auto" : return backend backend = infer_backend ( arrays [ 0 ] ) # some arrays will be defined in modules that don't implement tensordot # etc. so instead default to numpy if not backends . has_tensordot ( backend ) : return "numpy" return backend