Function test_decoded_vs_generated

dali/test/python/decoder/test_audio.py:103–150

()

@attr("sanitizer_skip")
def test_decoded_vs_generated():
    pipeline = DecoderPipeline()
    idx = 0
    for iter in range(1):
        out = pipeline.run()
        for i in range(len(out[0])):
            plain = out[0].at(i)
            res = out[1].at(i)
            mix = out[2].at(i)[:, np.newaxis]
            res_mix = out[3].at(i)[:, np.newaxis]

            ref_len = [0, 0, 0, 0]
            ref_len[0] = lengths[idx]
            ref_len[1] = lengths[idx] * rate1 / rates[idx]
            ref_len[2] = lengths[idx]
            ref_len[3] = lengths[idx] * rate2 / rates[idx]

            ref0 = generate_waveforms(ref_len[0], freqs[idx]) * 32767
            ref1 = generate_waveforms(ref_len[1], freqs[idx] * (rates[idx] / rate1)) * 32767
            ref2 = generate_waveforms(ref_len[2], freqs[idx]) * 32767
            ref2 = ref2.mean(axis=1, keepdims=1)
            ref3 = generate_waveforms(ref_len[3], freqs[idx] * (rates[idx] / rate2))
            ref3 = ref3.mean(axis=1, keepdims=1)

            assert out[4].at(i) == rates[idx]
            assert out[5].at(i) == rate1
            assert out[6].at(i) == rates[idx]
            assert out[7].at(i) == rate2

            # just reading - allow only for rounding
            assert np.allclose(plain, ref0, rtol=0, atol=0.5)
            # resampling - allow for 1e-3 dynamic range error
            assert np.allclose(res, ref1, rtol=0, atol=32767 * 1e-3)
            # downmixing - allow for 2 bits of error
            # - one for quantization of channels, one for quantization of result
            assert np.allclose(mix, ref2, rtol=0, atol=2)
            # resampling with weird ratio - allow for 3e-3 dynamic range error
            assert np.allclose(res_mix, ref3, rtol=0, atol=3e-3)

            rosa_in1 = plain.astype(np.float32)
            rosa1 = rosa_resample(rosa_in1, rates[idx], rate1)
            rosa_in3 = rosa_in1 / 32767
            rosa3 = rosa_resample(rosa_in3.mean(axis=1, keepdims=1), rates[idx], rate2)

            assert np.allclose(res, rosa1, rtol=0, atol=32767 * 1e-3)
            assert np.allclose(res_mix, rosa3, rtol=0, atol=3e-3)

            idx = (idx + 1) % len(names)


batch_size_alias_test = 16