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])