122 lines
4.8 KiB
Python
122 lines
4.8 KiB
Python
"""``load_audio`` must survive torchaudio 2.9 without TorchCodec (#1931).
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torchaudio >= 2.9 routes ``load()`` through TorchCodec, which needs FFmpeg
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*shared libraries* on the system. Where those are absent the call raises
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``ImportError`` — but ``load_audio`` caught only ``(RuntimeError, OSError)``,
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so the pydub fallback written for precisely this situation never ran. Every
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voice-clone reference read, watermark check and dub segment load then failed
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with "TorchCodec is required for load_with_torchcodec".
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This is the read-side twin of the ``_safe_torchaudio_save`` regression in
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``tests/backend/services/test_audio_io.py``, and it reaches the same users:
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#1931 guarded ``set_audio_backend()`` against torchaudio 2.9 but left
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``load()`` unprotected. arm64 CUDA hosts reach it unavoidably, since torch
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2.8.0 publishes no aarch64 wheel.
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Note that ``backend="soundfile"`` does not avoid this — torchaudio 2.9
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accepts that argument and ignores it.
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"""
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from __future__ import annotations
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import numpy as np
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import pytest
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import soundfile as sf
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import torch
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def _write_sine_wav(path, *, seconds: float = 0.5, sample_rate: int = 24000):
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n = int(seconds * sample_rate)
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t = np.arange(n, dtype=np.float32) / sample_rate
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sf.write(str(path), 0.5 * np.sin(2 * np.pi * 440.0 * t), sample_rate,
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subtype="PCM_16")
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return sample_rate
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def _torchcodec_missing(*_a, **_kw):
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raise ImportError(
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"TorchCodec is required for load_with_torchcodec. "
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"Please install torchcodec to use this function."
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)
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def test_load_audio_falls_back_when_torchcodec_missing(tmp_path, monkeypatch):
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"""Without the ImportError catch this raises instead of returning audio."""
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from omnivoice.utils.audio import load_audio
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import torchaudio
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ref = tmp_path / "ref.wav"
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sample_rate = _write_sine_wav(ref)
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monkeypatch.setattr(torchaudio, "load", _torchcodec_missing)
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waveform = load_audio(str(ref), sample_rate)
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assert isinstance(waveform, torch.Tensor)
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assert waveform.ndim == 2, f"expected (1, T), got {tuple(waveform.shape)}"
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assert waveform.shape[0] == 1, "load_audio must return mono"
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assert waveform.shape[-1] > 0
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assert waveform.abs().max() > 0.05, "fallback produced silence"
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def test_load_audio_fallback_resamples_to_target(tmp_path, monkeypatch):
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"""The fallback path must still honour the requested sampling rate."""
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from omnivoice.utils.audio import load_audio
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import torchaudio
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ref = tmp_path / "ref_16k.wav"
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_write_sine_wav(ref, seconds=0.5, sample_rate=16000)
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monkeypatch.setattr(torchaudio, "load", _torchcodec_missing)
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waveform = load_audio(str(ref), 24000)
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# 0.5 s resampled 16k -> 24k is ~12000 samples; allow resampler edge slack.
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assert abs(waveform.shape[-1] - 12000) <= 64, (
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f"expected ~12000 samples at 24 kHz, got {waveform.shape[-1]}"
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)
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@pytest.mark.parametrize("subtype", ["PCM_U8", "PCM_16", "PCM_24", "PCM_32", "FLOAT"])
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def test_load_audio_fallback_amplitude_matches_bit_depth(
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tmp_path, monkeypatch, subtype
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):
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"""The fallback must scale by the decoded width, not a fixed 32768.
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pydub reports 8-bit as ``sample_width`` 1 and widens 24-bit to a
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full-range int32 (``sample_width`` 4, contrary to the stale comment in
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its own source). Dividing every decode by 32768 therefore returned 24-
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and 32-bit references 32768x too loud and 8-bit ones 256x too quiet.
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Nothing downstream clamps, so a clone reference silently became noise.
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Before the ImportError catch this path was rare; on torchaudio >= 2.9
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without TorchCodec it is the only path, which is what makes it a bug
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worth fixing here.
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"""
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from omnivoice.utils.audio import load_audio
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import torchaudio
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sample_rate = 24000
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peak = 0.5
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t = np.arange(sample_rate // 2, dtype=np.float64) / sample_rate
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ref = tmp_path / f"ref_{subtype.lower()}.wav"
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sf.write(str(ref), peak * np.sin(2 * np.pi * 440.0 * t), sample_rate,
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subtype=subtype)
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monkeypatch.setattr(torchaudio, "load", _torchcodec_missing)
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waveform = load_audio(str(ref), sample_rate)
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assert waveform.abs().max().item() == pytest.approx(peak, abs=0.02), (
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f"{subtype} decoded at the wrong scale: peak "
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f"{waveform.abs().max().item():.6f}, expected ~{peak}"
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)
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@pytest.mark.parametrize("subtype", ["PCM_U8", "PCM_16", "PCM_24", "PCM_32"])
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def test_audiosegment_conversion_preserves_amplitude(tmp_path, subtype):
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from pydub import AudioSegment
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from omnivoice.utils.audio import audiosegment_to_tensor
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path = tmp_path / "stereo.wav"
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samples = np.tile([0.5, -0.25], (100, 1))
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sf.write(path, samples, 24000, subtype=subtype)
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converted = audiosegment_to_tensor(AudioSegment.from_file(path)).numpy()
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np.testing.assert_allclose(converted, samples.T, atol=0.01)
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