def METHOD_NAME(self):
    spatial_size = (16, 16, 16)
    rescaler_1 = Resize(spatial_size=spatial_size, anti_aliasing=True, anti_aliasing_sigma=(0.5, 1.0, 2.0))
    rescaler_2 = Resize(spatial_size=spatial_size, anti_aliasing=True, anti_aliasing_sigma=None)
    rescaler_dict = Resized(
        keys=["img1", "img2"],
        spatial_size=spatial_size,
        anti_aliasing=(True, True),
        anti_aliasing_sigma=[(0.5, 1.0, 2.0), None],
    )
    test_input_1 = torch.randn([3, 32, 32, 32])
    test_input_2 = torch.randn([3, 32, 32, 32])
    test_input_dict = {"img1": test_input_1, "img2": test_input_2}
    assert_allclose(rescaler_1(test_input_1), rescaler_dict(test_input_dict)["img1"])
    assert_allclose(rescaler_2(test_input_2), rescaler_dict(test_input_dict)["img2"])