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https://github.com/mudler/LocalAI.git
synced 2026-09-13 14:56:11 -04:00
Ettore Di Giacinto
ab3f7fc904
The Intel backend installs PyTorch XPU wheels, but Qwen ASR only checked CUDA and MPS. Every Intel model therefore loaded on the CPU. Select XPU when available and place the model on xpu:0. Keep the existing CUDA, MPS, and CPU placement behavior. Assisted-by: Codex:GPT-5 [apply_patch] [gh] Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
59 lines
1.6 KiB
Python
59 lines
1.6 KiB
Python
import unittest
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from device_utils import device_map_for, select_device
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class Availability:
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def __init__(self, available):
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self._available = available
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def is_available(self):
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return self._available
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class TorchStub:
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def __init__(self, *, cuda=False, mps=False, xpu=False):
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self.cuda = Availability(cuda)
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self.backends = type("Backends", (), {"mps": Availability(mps)})()
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self.xpu = Availability(xpu)
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class SelectDeviceTest(unittest.TestCase):
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def test_preserves_cuda_selection(self):
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torch_module = TorchStub(cuda=True)
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self.assertEqual(select_device(torch_module), "cuda")
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def test_preserves_mps_selection(self):
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torch_module = TorchStub(mps=True)
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self.assertEqual(select_device(torch_module), "mps")
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def test_selects_xpu_when_intel_gpu_is_available(self):
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torch_module = TorchStub(xpu=True)
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self.assertEqual(select_device(torch_module), "xpu")
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def test_falls_back_to_cpu(self):
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torch_module = TorchStub()
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self.assertEqual(select_device(torch_module), "cpu")
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class DeviceMapTest(unittest.TestCase):
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def test_preserves_cuda_model_placement(self):
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self.assertEqual(device_map_for("cuda"), "cuda:0")
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def test_preserves_mps_model_placement(self):
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self.assertIsNone(device_map_for("mps"))
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def test_places_the_model_on_the_first_xpu(self):
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self.assertEqual(device_map_for("xpu"), "xpu:0")
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def test_preserves_cpu_model_placement(self):
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self.assertEqual(device_map_for("cpu"), "cpu")
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if __name__ == "__main__":
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unittest.main()
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