def METHOD_NAME(self):
    expected_query = torch.tensor(
        [[[[-1.0235, 0.0409], [0.4008, 1.3077], [0.5396, 2.0698]]]]
    )
    expected_key = torch.tensor(
        [[[[0.5053, -0.4965], [-0.3730, -0.9473], [-0.7019, -0.1935]]]]
    )
    expected_val = torch.tensor(
        [[[[-0.9940, 0.5403], [0.5924, -0.7619], [0.7504, -1.0892]]]]
    )
    sample_t = self.sample.transpose(0, 1)
    query, key, val = self.MHA.forward_qkv(sample_t, sample_t, sample_t)
    self.assertTrue(
        np.allclose(
            expected_query.cpu().detach().numpy(),
            query.cpu().detach().numpy(),
            atol=1e-4,
        )
    )
    self.assertTrue(
        np.allclose(
            expected_key.cpu().detach().numpy(),
            key.cpu().detach().numpy(),
            atol=1e-4,
        )
    )
    self.assertTrue(
        np.allclose(
            expected_val.cpu().detach().numpy(),
            val.cpu().detach().numpy(),
            atol=1e-4,
        )
    )