[Help wanted] Some tests are failing about nnaudio HOT 6 OPEN

@pytest.mark.parametrize("device", [*device_args])
def test_cqt_1992_v2_linear(device):
    # Linear sweep case
    fs = 44100
    t = 1
    f0 = 55
    f1 = 22050
    s = np.linspace(0, t, fs * t)
    x = chirp(s, f0, 1, f1, method="linear")
    x = x.astype(dtype=np.float32)


    # Get the complex ground truth for CQT1992v2, magnitude and phase can be derived from it
    complex_ground_truth = np.load(
        os.path.join(
            dir_path, "ground-truths/linear-sweep-cqt-1992-complex-ground-truth.npy"
        )
    )
    ground_truth_complex_real = complex_ground_truth[..., 0]
    ground_truth_complex_img = complex_ground_truth[..., 1]

    magnitude_ground_truth = np.log(np.sqrt(np.power(ground_truth_complex_real, 2) + np.power(ground_truth_complex_img, 2)) + 1e-5)
    
    phase_ground_truth_atan2 = np.arctan2(ground_truth_complex_img, ground_truth_complex_real)
    phase_ground_truth_real = np.cos(phase_ground_truth_atan2)
    phase_ground_truth_img = np.sin(phase_ground_truth_atan2)
    phase_ground_truth = np.stack([phase_ground_truth_real, phase_ground_truth_img], axis=-1)

    # Magnitude
    stft = CQT1992v2(
        sr=fs, fmin=55, output_format="Magnitude", n_bins=207, bins_per_octave=24
    ).to(device)
    X = stft(torch.tensor(x, device=device).unsqueeze(0))
    X = torch.log(X + 1e-5)
    assert np.allclose(X.cpu(), magnitude_ground_truth, rtol=1e-3, atol=1e-3)

    # Complex
    stft = CQT1992v2(
        sr=fs, fmin=55, output_format="Complex", n_bins=207, bins_per_octave=24
    ).to(device)
    X = stft(torch.tensor(x, device=device).unsqueeze(0))
    assert np.allclose(X.cpu(), complex_ground_truth, rtol=1e-3, atol=1e-3)
    assert np.allclose(np.arctan2(X[..., 1].cpu(), X[..., 0].cpu()), phase_ground_truth_atan2, rtol=1e-3, atol=1e-3)
    assert np.allclose(torch.atan2(X[..., 1].cpu(), X[..., 0].cpu()), phase_ground_truth_atan2, rtol=1e-3, atol=1e-3)

    # Phase
    stft = CQT1992v2(
        sr=fs, fmin=55, output_format="Phase", n_bins=207, bins_per_octave=24
    ).to(device)
    X = stft(torch.tensor(x, device=device).unsqueeze(0))

    assert np.allclose(X.cpu(), phase_ground_truth, rtol=1e-3, atol=1e-3)