mirror of
https://github.com/mudler/LocalAI.git
synced 2026-09-13 06:45:26 -04:00
Ettore Di Giacinto
f8e228e0ba
Keep the relocated upstream source importable, select CUDA 13 PyTorch wheels instead of the aarch64 CPU fallback, and decode reference audio without torchcodec, which has no Linux arm64 wheels. Assisted-by: Codex:gpt-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
137 lines
4.9 KiB
Python
137 lines
4.9 KiB
Python
# SPDX-License-Identifier: MIT
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import importlib.util
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import sys
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import tempfile
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import types
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import unittest
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from pathlib import Path
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MODULE_PATH = Path(__file__).with_name("prepare_upstream.py")
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def load_prepare_upstream():
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if not MODULE_PATH.exists():
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raise AssertionError("prepare_upstream.py is missing")
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spec = importlib.util.spec_from_file_location("prepare_upstream", MODULE_PATH)
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module = importlib.util.module_from_spec(spec)
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spec.loader.exec_module(module)
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return module
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class FakeAudioData:
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@property
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def T(self):
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return self
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def copy(self):
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return "channels-first"
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class PrepareUpstreamTests(unittest.TestCase):
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def test_cuda13_dependencies_follow_available_pytorch_wheels(self):
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prepare_upstream = load_prepare_upstream()
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with tempfile.TemporaryDirectory() as tmp:
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pyproject = Path(tmp) / "pyproject.toml"
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pyproject.write_text(
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'dependencies = [\n "torch==2.8.0",\n "torchaudio==2.8.0",\n]\n'
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'stable = [\n "torch==2.8.0",\n "torchaudio",\n]\n'
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)
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prepare_upstream.patch_cuda13_dependencies(pyproject)
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self.assertEqual(
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pyproject.read_text(),
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'dependencies = [\n "torch==2.9.1",\n "torchaudio==2.9.1",\n]\n'
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'stable = [\n "torch==2.9.1",\n "torchaudio",\n]\n',
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)
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def test_reference_audio_uses_soundfile_without_torchcodec(self):
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prepare_upstream = load_prepare_upstream()
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with tempfile.TemporaryDirectory() as tmp:
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loader = Path(tmp) / "reference_loader.py"
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loader.write_text(
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"class ReferenceLoader:\n"
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" def load_audio(self, reference_audio):\n"
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" waveform, original_sr = torchaudio.load(reference_audio, backend=self.backend)\n"
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" return waveform, original_sr\n"
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)
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prepare_upstream.patch_reference_loader(loader)
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calls = []
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fake_soundfile = types.SimpleNamespace(
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read=lambda source, **kwargs: (
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calls.append((source, kwargs)) or FakeAudioData(),
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24000,
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)
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)
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fake_torch = types.SimpleNamespace(
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from_numpy=lambda data: ("tensor", data),
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)
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previous_soundfile = sys.modules.get("soundfile")
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previous_torch = sys.modules.get("torch")
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sys.modules["soundfile"] = fake_soundfile
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sys.modules["torch"] = fake_torch
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try:
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namespace = {"torchaudio": None}
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exec(compile(loader.read_text(), str(loader), "exec"), namespace)
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instance = namespace["ReferenceLoader"]()
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instance.backend = "soundfile"
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waveform, sample_rate = instance.load_audio("voice.wav")
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finally:
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if previous_soundfile is None:
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del sys.modules["soundfile"]
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else:
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sys.modules["soundfile"] = previous_soundfile
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if previous_torch is None:
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del sys.modules["torch"]
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else:
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sys.modules["torch"] = previous_torch
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self.assertEqual(waveform, ("tensor", "channels-first"))
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self.assertEqual(sample_rate, 24000)
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self.assertEqual(
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calls,
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[("voice.wav", {"dtype": "float32", "always_2d": True})],
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)
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def test_reference_loader_drift_fails_the_build(self):
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prepare_upstream = load_prepare_upstream()
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with tempfile.TemporaryDirectory() as tmp:
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loader = Path(tmp) / "reference_loader.py"
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loader.write_text("def load_audio():\n pass\n")
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with self.assertRaisesRegex(RuntimeError, "torchaudio.load call"):
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prepare_upstream.patch_reference_loader(loader)
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def test_preparation_can_be_repeated(self):
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prepare_upstream = load_prepare_upstream()
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with tempfile.TemporaryDirectory() as tmp:
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pyproject = Path(tmp) / "pyproject.toml"
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pyproject.write_text(
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'dependencies = ["torch==2.8.0", "torchaudio==2.8.0"]\n'
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)
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loader = Path(tmp) / "reference_loader.py"
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loader.write_text(
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"def load_audio(reference_audio):\n"
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" waveform, original_sr = torchaudio.load(reference_audio, backend=self.backend)\n"
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)
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prepare_upstream.patch_cuda13_dependencies(pyproject)
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prepare_upstream.patch_reference_loader(loader)
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try:
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prepare_upstream.patch_cuda13_dependencies(pyproject)
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prepare_upstream.patch_reference_loader(loader)
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except RuntimeError as err:
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self.fail(f"preparation is not idempotent: {err}")
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if __name__ == "__main__":
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unittest.main()
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