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PaddleSpeech/third_party/python_kaldi_features/test/test_sigproc.py

32 lines
1.1 KiB

E2E/Streaming Transformer/Conformer ASR (#578) * add cmvn and label smoothing loss layer * add layer for transformer * add glu and conformer conv * add torch compatiable hack, mask funcs * not hack size since it exists * add test; attention * add attention, common utils, hack paddle * add audio utils * conformer batch padding mask bug fix #223 * fix typo, python infer fix rnn mem opt name error and batchnorm1d, will be available at 2.0.2 * fix ci * fix ci * add encoder * refactor egs * add decoder * refactor ctc, add ctc align, refactor ckpt, add warmup lr scheduler, cmvn utils * refactor docs * add fix * fix readme * fix bugs, refactor collator, add pad_sequence, fix ckpt bugs * fix docstring * refactor data feed order * add u2 model * refactor cmvn, test * add utils * add u2 config * fix bugs * fix bugs * fix autograd maybe has problem when using inplace operation * refactor data, build vocab; add format data * fix text featurizer * refactor build vocab * add fbank, refactor feature of speech * refactor audio feat * refactor data preprare * refactor data * model init from config * add u2 bins * flake8 * can train * fix bugs, add coverage, add scripts * test can run * fix data * speed perturb with sox * add spec aug * fix for train * fix train logitc * fix logger * log valid loss, time dataset process * using np for speed perturb, remove some debug log of grad clip * fix logger * fix build vocab * fix logger name * using module logger as default * fix * fix install * reorder imports * fix board logger * fix logger * kaldi fbank and mfcc * fix cmvn and print prarams * fix add_eos_sos and cmvn * fix cmvn compute * fix logger and cmvn * fix subsampling, label smoothing loss, remove useless * add notebook test * fix log * fix tb logger * multi gpu valid * fix log * fix log * fix config * fix compute cmvn, need paddle 2.1 * add cmvn notebook * fix layer tools * fix compute cmvn * add rtf * fix decoding * fix layer tools * fix log, add avg script * more avg and test info * fix dataset pickle problem; using 2.1 paddle; num_workers can > 0; ckpt save in exp dir;fix setup.sh; * add vimrc * refactor tiny script, add transformer and stream conf * spm demo; librisppech scripts and confs * fix log * add librispeech scripts * refactor data pipe; fix conf; fix u2 default params * fix bugs * refactor aishell scripts * fix test * fix cmvn * fix s0 scripts * fix ds2 scripts and bugs * fix dev & test dataset filter * fix dataset filter * filter dev * fix ckpt path * filter test, since librispeech will cause OOM, but all test wer will be worse, since mismatch train with test * add comment * add syllable doc * fix ds2 configs * add doc * add pypinyin tools * fix decoder using blank_id=0 * mmseg with pybind11 * format code
3 years ago
from python_speech_features import sigproc
import unittest
import numpy as np
import time
class test_case(unittest.TestCase):
def test_frame_sig(self):
n = 10000124
frame_len = 37
frame_step = 13
x = np.random.rand(n)
t0 = time.time()
y_old = sigproc.framesig(x, frame_len=frame_len, frame_step=frame_step, stride_trick=False)
t1 = time.time()
y_new = sigproc.framesig(x, frame_len=frame_len, frame_step=frame_step, stride_trick=True)
t_new = time.time() - t1
t_old = t1 - t0
self.assertTupleEqual(y_old.shape, y_new.shape)
np.testing.assert_array_equal(y_old, y_new)
self.assertLess(t_new, t_old)
print('new run time %3.2f < %3.2f sec' % (t_new, t_old))
def test_rolling(self):
x = np.arange(10)
y = sigproc.rolling_window(x, window=4, step=3)
y_expected = np.array([[0, 1, 2, 3],
[3, 4, 5, 6],
[6, 7, 8, 9]]
)
y = np.testing.assert_array_equal(y, y_expected)