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ZFTurbo / MVSEP-MDX23-music-separation-model

Model for MDX23 music separation contest
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FAIL : bad allocation #34

Open kevinlinxc opened 7 months ago

kevinlinxc commented 7 months ago

Running in CPU mode, I get this error:

D:\Downloads\MVSep-MDX23_v1.0.1\inference.py:131: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at ..\torch\csrc\utils\tensor_new.cpp:248.)
  mix_waves = torch.tensor(mix_waves, dtype=torch.float32).to(device)
Traceback (most recent call last):
  File "D:\Downloads\MVSep-MDX23_v1.0.1\inference.py", line 906, in <module>
    predict_with_model(options)
  File "D:\Downloads\MVSep-MDX23_v1.0.1\inference.py", line 844, in predict_with_model
    result, sample_rates = model.separate_music_file(
  File "D:\Downloads\MVSep-MDX23_v1.0.1\inference.py", line 621, in separate_music_file
    sources1 = demix_full(
  File "D:\Downloads\MVSep-MDX23_v1.0.1\inference.py", line 163, in demix_full
    sources = demix_base(mix_part, device, models, infer_session)
  File "D:\Downloads\MVSep-MDX23_v1.0.1\inference.py", line 136, in demix_base
    res = _ort.run(None, {'input': stft_res.cpu().numpy()})[0]
  File "D:\Downloads\MVSep-MDX23_v1.0.1\Miniconda\lib\site-packages\onnxruntime\capi\onnxruntime_inference_collection.py", line 200, in run
    return self._sess.run(output_names, input_feed, run_options)
onnxruntime.capi.onnxruntime_pybind11_state.Fail: [ONNXRuntimeError] : 1 : FAIL : bad allocation

Any idea for how to solve?