def METHOD_NAME(dtype, layout, shape):
    batch_size = Pipeline.current().max_batch_size
    input = fn.external_source(
        source=[[np.full((10, 10, 3), 42, dtype=np.int32) for _ in range(batch_size)]], cycle=True)
    pred = fn.external_source(
        source=[[np.array(i % 2 == 0, dtype=bool) for i in range(batch_size)]], cycle=True)
    true_branch, false_branch = fn._conditional.split(input, predicate=pred)
    false_changed = fn.reinterpret(false_branch, dtype=dtype, layout=layout, shape=shape)
    return fn._conditional.merge(true_branch, false_changed, predicate=pred)