def test_normalize():
"""Ensures normalized tensor has mean zero, std one."""
normalize = preprocess.Normalize()
tensor = (np.random.rand(100, 10) - 0.5) * 100
normed = normalize(tensor)
assert np.allclose(normed.mean(), 0.0)
assert np.allclose(normed.std(), 1.0)
def transform(self):
return Compose([lambda t: t.astype(np.float32),
preprocess.LogMagnitudeSTFT(
winlen=self._winlen,
winstep=self._winstep,
sample_rate=self._sample_rate),
preprocess.Normalize(),
torch.from_numpy,
lambda t: (t, Network.output_len(len(t))),
])
def transform(self):
return Compose([
preprocess.MFCC(self._n_mfcc),
preprocess.AddContextFrames(self._n_context),
preprocess.Normalize(), torch.FloatTensor, lambda t: (t, len(t))
])