def test_batch_compute_deltas(self):
specgram = torch.randn(2, 31, 2786)
# Single then transform then batch
expected = transforms.ComputeDeltas()(specgram).repeat(3, 1, 1, 1)
# Batch then transform
computed = transforms.ComputeDeltas()(specgram.repeat(3, 1, 1, 1))
# shape = (3, 2, 201, 1394)
self.assertTrue(computed.shape == expected.shape, (computed.shape, expected.shape))
self.assertTrue(torch.allclose(computed, expected))
def test_compute_deltas_twochannel(self):
specgram = torch.tensor([1., 2., 3., 4.]).repeat(1, 2, 1)
expected = torch.tensor([[[0.5, 1.0, 1.0, 0.5],
[0.5, 1.0, 1.0, 0.5]]])
transform = transforms.ComputeDeltas()
computed = transform(specgram)
self.assertTrue(computed.shape == specgram.shape, (computed.shape, specgram.shape))
def test_compute_deltas_twochannel(self):
specgram = torch.tensor([1., 2., 3., 4.]).repeat(1, 2, 1)
expected = torch.tensor([[[0.5, 1.0, 1.0, 0.5], [0.5, 1.0, 1.0, 0.5]]])
transform = transforms.ComputeDeltas(win_length=3)
computed = transform(specgram)
assert computed.shape == expected.shape, (computed.shape,
expected.shape)
self.assertEqual(computed, expected, atol=1e-6, rtol=1e-8)
def test_compute_deltas(self):
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(specgram)
self.assertTrue(computed.shape == specgram.shape, (computed.shape, specgram.shape))
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):
transform = T.ComputeDeltas()
spec = torch.rand(10, 20)
self.assert_grad(transform, [spec])
def __init__(self, order=2, **kwargs):
super(Delta, self).__init__()
self.order = order
self.compute_delta = transforms.ComputeDeltas(**kwargs)
