dtype=self.dtype,
device=self.device)
b_coeffs = torch.tensor([1, 0], dtype=self.dtype, device=self.device)
a_coeffs = torch.tensor([1, -0.95],
dtype=self.dtype,
device=self.device)
output_signal = F.lfilter(input_signal, a_coeffs, b_coeffs, clamp=True)
assert output_signal.max() <= 1
output_signal = F.lfilter(input_signal,
a_coeffs,
b_coeffs,
clamp=False)
assert output_signal.max() > 1
common_utils.define_test_suites(globals(), [Lfilter])
class TestComputeDeltas(unittest.TestCase):
"""Test suite for correctness of compute_deltas"""
def test_one_channel(self):
specgram = torch.tensor([[[1.0, 2.0, 3.0, 4.0]]])
expected = torch.tensor([[[0.5, 1.0, 1.0, 0.5]]])
computed = F.compute_deltas(specgram, win_length=3)
torch.testing.assert_allclose(computed, expected)
def test_two_channels(self):
specgram = torch.tensor([[[1.0, 2.0, 3.0, 4.0], [1.0, 2.0, 3.0, 4.0]]])
expected = torch.tensor([[[0.5, 1.0, 1.0, 0.5], [0.5, 1.0, 1.0, 0.5]]])
computed = F.compute_deltas(specgram, win_length=3)
torch.testing.assert_allclose(computed, expected)
from common_utils import define_test_suites from torchscript_consistency_impl import Functional, Transforms define_test_suites(globals(), [Functional, Transforms], devices=['cuda'])
import common_utils from kaldi_compatibility_impl import Kaldi common_utils.define_test_suites(globals(), [Kaldi], devices=['cuda'])
fade_out_len = 3000
self._assert_consistency(T.Fade(fade_in_len, fade_out_len), waveform)
def test_FrequencyMasking(self):
tensor = torch.rand((10, 2, 50, 10, 2))
self._assert_consistency(
T.FrequencyMasking(freq_mask_param=60, iid_masks=False), tensor)
def test_TimeMasking(self):
tensor = torch.rand((10, 2, 50, 10, 2))
self._assert_consistency(
T.TimeMasking(time_mask_param=30, iid_masks=False), tensor)
def test_Vol(self):
test_filepath = common_utils.get_asset_path(
'steam-train-whistle-daniel_simon.wav')
waveform, _ = torchaudio.load(test_filepath)
self._assert_consistency(T.Vol(1.1), waveform)
def test_SlidingWindowCmn(self):
tensor = torch.rand((1000, 10))
self._assert_consistency(T.SlidingWindowCmn(), tensor)
def test_Vad(self):
filepath = common_utils.get_asset_path("vad-go-mono-32000.wav")
waveform, sample_rate = torchaudio.load(filepath)
self._assert_consistency(T.Vad(sample_rate=sample_rate), waveform)
common_utils.define_test_suites(globals(), [Functional, Transforms])