How to use the torchaudio.functional.compute_deltas function in torchaudio

def test_compute_deltas_transform_same_as_functional(self, atol=1e-6, rtol=1e-8):
        channel = 13
        n_mfcc = channel * 3
        time = 1021
        win_length = 2 * 7 + 1
        specgram = torch.randn(channel, n_mfcc, time)

        transform = transforms.ComputeDeltas(win_length=win_length)
        computed_transform = transform(specgram)

        computed_functional = F.compute_deltas(specgram, win_length=win_length)
        torch.testing.assert_allclose(computed_functional, computed_transform, atol=atol, rtol=rtol)

def _test_compute_deltas(self, specgram, expected, win_length=3, atol=1e-6, rtol=1e-8):
        computed = F.compute_deltas(specgram, win_length=win_length)
        self.assertTrue(computed.shape == expected.shape, (computed.shape, expected.shape))
        torch.testing.assert_allclose(computed, expected, atol=atol, rtol=rtol)

def test_compute_deltas_randn(self):
        channel = 13
        n_mfcc = channel * 3
        time = 1021
        win_length = 2 * 7 + 1
        specgram = torch.randn(channel, n_mfcc, time)
        computed = F.compute_deltas(specgram, win_length=win_length)
        self.assertTrue(computed.shape == specgram.shape, (computed.shape, specgram.shape))
        _test_torchscript_functional(F.compute_deltas, specgram, win_length=win_length)

def test_compute_deltas_randn(self):
        channel = 13
        n_mfcc = channel * 3
        time = 1021
        win_length = 2 * 7 + 1
        specgram = torch.randn(channel, n_mfcc, time)
        computed = F.compute_deltas(specgram, win_length=win_length)
        self.assertTrue(computed.shape == specgram.shape, (computed.shape, specgram.shape))
        _test_torchscript_functional(F.compute_deltas, specgram, win_length=win_length)

def forward(self, specgram):
        r"""
        Args:
            specgram (torch.Tensor): Tensor of audio of dimension (channel, freq, time)

        Returns:
            deltas (torch.Tensor): Tensor of audio of dimension (channel, freq, time)
        """
        return F.compute_deltas(specgram, win_length=self.win_length, mode=self.mode)