def METHOD_NAME(self, seed, expected_slice):
    model = PriorTransformer.from_pretrained("kandinsky-community/kandinsky-2-1-prior", subfolder="prior")
    model.to(torch_device)
    input = self.get_dummy_seed_input(seed=seed)
    with torch.no_grad():
        sample = model(**input)[0]
    assert list(sample.shape) == [1, 768]
    output_slice = sample[0, :8].flatten().cpu()
    print(output_slice)
    expected_output_slice = torch.tensor(expected_slice)
    assert torch_all_close(output_slice, expected_output_slice, atol=1e-3)