[ONNXRuntimeError] : 7 : INVALID_PROTOBUF : Load model from onnx/bass.onnx failed:Protobuf parsing failed. #13
Description
I was unable to build leaderboard B by following the instructions in it's README on my host OS (Ubuntu 20.04) but was unable to get it working.
I then decided to try to build it from scratch withing an nvidia-ubuntu18.04 with no success (same errors as the bare metal attempt. will update issue once I replicate those errors). I then decided to try using the the docker_build.sh utility and was able to get past those errors, however, every time the model tries to perform demixing I receive the following errors:
python predict_blend.py
/home/aicrowd/data/test/Matroda - On My Mind/mixture.wav
92.74054026603699
/home/aicrowd/predict_blend.py:50: 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:210.)
mix_waves = torch.tensor(mix_waves, dtype=torch.float32)
Traceback (most recent call last):
File "/home/aicrowd/evaluator/music_demixing.py", line 145, in run
self.evaluation()
File "/home/aicrowd/evaluator/music_demixing.py", line 132, in evaluation
self.prediction(mixture_file_path=self.get_music_file_location(music_name),
File "/home/aicrowd/predict_blend.py", line 24, in prediction
sources = self.demix(mix.T)
File "/home/aicrowd/predict_blend.py", line 30, in demix
base_out = self.demix_base(mix)
File "/home/aicrowd/predict_blend.py", line 53, in demix_base
_ort = ort.InferenceSession(f'onnx/{model.target_name}.onnx')
File "/srv/conda/envs/notebook/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 280, in __init__
self._create_inference_session(providers, provider_options)
File "/srv/conda/envs/notebook/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 307, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_path, True, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidProtobuf: [ONNXRuntimeError] : 7 : INVALID_PROTOBUF : Load model from onnx/bass.onnx failed:Protobuf parsing failed.
Traceback (most recent call last):
File "/home/aicrowd/predict_blend.py", line 84, in <module>
submission.run()
File "/home/aicrowd/evaluator/music_demixing.py", line 151, in run
raise e
File "/home/aicrowd/evaluator/music_demixing.py", line 145, in run
self.evaluation()
File "/home/aicrowd/evaluator/music_demixing.py", line 132, in evaluation
self.prediction(mixture_file_path=self.get_music_file_location(music_name),
File "/home/aicrowd/predict_blend.py", line 24, in prediction
sources = self.demix(mix.T)
File "/home/aicrowd/predict_blend.py", line 30, in demix
base_out = self.demix_base(mix)
File "/home/aicrowd/predict_blend.py", line 53, in demix_base
_ort = ort.InferenceSession(f'onnx/{model.target_name}.onnx')
File "/srv/conda/envs/notebook/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 280, in __init__
self._create_inference_session(providers, provider_options)
File "/srv/conda/envs/notebook/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 307, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_path, True, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidProtobuf: [ONNXRuntimeError] : 7 : INVALID_PROTOBUF : Load model from onnx/bass.onnx failed:Protobuf parsing failed.Has anyone tried a fresh install of this lately?
Would I have better luck using: https://github.com/kuielab/mdx-net ? (I have 2 RTX 3070 available for this project, in the future I would like to train the model to be better at recognising electronic instruments/synths)