def _test_both_ways():
_seed()
n_quantize = 256
encoding_layer = MuLawEncoding(n_quantize)
decoding_layer = MuLawDecoding(n_quantize)
x_mu = torch.randint(low=0, high=n_quantize - 1, size=(1, 1024))
assert _all_equal(x_mu, encoding_layer(decoding_layer(x_mu)))
def _test_mu_encoding():
_seed()
n_quantize = 256
encoding_layer = MuLawEncoding(n_quantize)
waveform = 2 * (torch.rand(1, 1024) - 0.5) # in [-1, 1)
# manual computation
mu = torch.tensor(n_quantize - 1, dtype=waveform.dtype, requires_grad=False)
waveform_mu = waveform.sign() * torch.log1p(mu * waveform.abs()) / torch.log1p(mu)
waveform_mu = ((waveform_mu + 1) / 2 * mu + 0.5).long()
assert _all_equal(encoding_layer(waveform),
waveform_mu)