Function _test_empty_input

dali/test/python/operator_2/test_resize.py:763–799

(dim, backend)

def _test_empty_input(dim, backend):
    batch_size = 8
    pipe = Pipeline(batch_size=batch_size, num_threads=8, device_id=0, seed=1234)
    if dim == 2:
        files, labels = dali.fn.readers.caffe(path=db_2d_folder, random_shuffle=True)
        images_cpu = dali.fn.decoders.image(files, device="cpu")
    else:
        images_cpu = dali.fn.external_source(source=random_3d_loader(batch_size), layout="DHWC")

    images = images_cpu if backend_device(backend) == "cpu" else images_cpu.gpu()

    in_rel_shapes = np.ones([batch_size, dim], dtype=np.float32)

    in_rel_shapes[::2, :] *= 0  # all zeros in every second sample

    degenerate_images = fn.slice(
        images, np.zeros([dim]), fn.external_source(lambda: in_rel_shapes), axes=list(range(dim))
    )

    sizes = np.random.randint(20, 50, [batch_size, dim], dtype=np.int32)
    size_inp = fn.external_source(lambda: [x.astype(np.float32) for x in sizes])

    resize_no_empty = resize_op(backend)(images, size=size_inp, mode="not_larger")
    resize_with_empty = resize_op(backend)(degenerate_images, size=size_inp, mode="not_larger")

    pipe.set_outputs(resize_no_empty, resize_with_empty)

    for it in range(3):
        out_no_empty, out_with_empty = pipe.run()
        if backend_device(backend) == "gpu":
            out_no_empty = out_no_empty.as_cpu()
            out_with_empty = out_with_empty.as_cpu()
        for i in range(batch_size):
            if i % 2 != 0:
                assert np.array_equal(out_no_empty.at(i), out_with_empty.at(i))
            else:
                assert np.prod(out_with_empty.at(i).shape) == 0


def test_empty_input():