How to use the einops.einops.TransformRecipe function in einops

for composite_axis in composite_axes_left:
        known = {axis for axis in composite_axis if known_lengths[axis] is not None}
        unknown = {axis for axis in composite_axis if known_lengths[axis] is None}
        lookup = dict(zip(list(known_lengths), range(len(known_lengths))))
        if len(unknown) > 1:
            raise EinopsError('Could not infer sizes for {}'.format(unknown))
        assert len(unknown) + len(known) == len(composite_axis)
        input_axes_known_unknown.append(([lookup[axis] for axis in known], [lookup[axis] for axis in unknown]))

    result_axes_grouping = [[position_lookup_after_reduction[axis] for axis in composite_axis]
                            for composite_axis in composite_axes_rght]

    ellipsis_left = math.inf if _ellipsis not in composite_axes_left else composite_axes_left.index(_ellipsis)
    ellipsis_rght = math.inf if _ellipsis not in composite_axes_rght else composite_axes_rght.index(_ellipsis)

    return TransformRecipe(elementary_axes_lengths=list(known_lengths.values()),
                           input_composite_axes=input_axes_known_unknown,
                           output_composite_axes=result_axes_grouping,
                           reduction_type=reduction,
                           reduced_elementary_axes=tuple(reduced_axes),
                           ellipsis_positions=(ellipsis_left, ellipsis_rght)
                           )