def generate_imports_bijectors()

in scripts/generate_imports.py [0:0]

• 30 lines of code
• 10 McCabe index (conditional complexity)

def generate_imports_bijectors(filename):
    bij = list_bijectors()
    meta_bijectors = []
    standard_bijectors = []

    # Standard bijectors can be initialized with a shape, whereas
    # meta bijectors will throw a TypeError or require additional
    # keyword arguments (e.g., bij.Compose)
    # TODO: Refactor this into flowtorch.utils.ismetabijector
    for b in bij:
        try:
            cls = b[1]
            x = cls(shape=torch.Size([2] * cls.domain.event_dim))
        except TypeError:
            meta_bijectors.append(b)
        else:
            if isinstance(x, flowtorch.Lazy):
                meta_bijectors.append(b)
            else:
                standard_bijectors.append(b)

    with io.StringIO() as file:
        # Sort classes by qualified name
        classes = standard_bijectors + meta_bijectors
        classes = sorted(classes, key=lambda tup: classname(tup[1]))

        # Copyright header and warning message
        print(copyright_header, file=file)
        print(autogen_msg, file=file)

        # Non-FlowTorch imports
        print(bijectors_imports, file=file)

        # FlowTorch imports
        for s, cls in classes:
            print(f"from {cls.__module__} import {s}", file=file)
        print("", file=file)

        # Create lists of bijectors for each type
        meta_str = ",\n    ".join([f'("{b[0]}", {b[0]})' for b in meta_bijectors])
        standard_str = ",\n    ".join(
            [f'("{b[0]}", {b[0]})' for b in standard_bijectors]
        )

        print(
            f"""standard_bijectors = [