Script quits unexpectedly (without errors) when trying to export model to ONNX about nisqa HOT 6 CLOSED

Other update: this issue is currently tracked on pytorch repo: pytorch/pytorch#75383

from nisqa.

Update: when trying to export the model from Linux (or WSL in my case), I get the following, more verbose errors:

Device: cpu
Model architecture: NISQA_DIM
Loaded pretrained model from weights/nisqa.tar
/home/username/miniconda3/envs/nisqa/lib/python3.9/site-packages/torch/onnx/utils.py:1294: UserWarning: Provided key output for dynamic axes is not a valid input/output name
  warnings.warn("Provided key {} for dynamic axes is not a valid input/output name".format(key))
WARNING: The shape inference of prim::PackPadded type is missing, so it may result in wrong shape inference for the exported graph. Please consider adding it in symbolic function.
WARNING: The shape inference of prim::PackPadded type is missing, so it may result in wrong shape inference for the exported graph. Please consider adding it in symbolic function.
/home/username/miniconda3/envs/nisqa/lib/python3.9/site-packages/torch/onnx/symbolic_helper.py:258: UserWarning: ONNX export failed on adaptive_max_pool2d because input size not accessible not supported
  warnings.warn("ONNX export failed on " + op + " because " + msg + " not supported")
/home/username/miniconda3/envs/nisqa/lib/python3.9/site-packages/torch/onnx/symbolic_helper.py:716: UserWarning: allowzero=0 by default. In order to honor zero value in shape use allowzero=1
  warnings.warn("allowzero=0 by default. In order to honor zero value in shape use allowzero=1")
WARNING: The shape inference of prim::PadPacked type is missing, so it may result in wrong shape inference for the exported graph. Please consider adding it in symbolic function.
WARNING: The shape inference of prim::PadPacked type is missing, so it may result in wrong shape inference for the exported graph. Please consider adding it in symbolic function.
Segmentation fault

PS: you can access my script here: https://github.com/miccio-dk/NISQA
Notice that run_export.py behaves exactly like run_predict.py except I'm forcing CPU.

from nisqa.

Thanks, hopefully, someone will be able to help in the PyTorch repo. I haven't converted this particular model to ONNX before but a workaround you could try is to remove the packed sequence parts altogether if this is causing the errors. Actually, that's what I used to do with other models because ONNX didn't use to support packed sequences then.

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Closing this as it is not directly related to the model but rather to PyTorch. BTW - if you want to export it to ONNX you probably need to use the model without adaptive pooling layers and without packed sequences. Then it should work

from nisqa.

@gabrielmittag do I need to retrain the model after removing packed sequences or there are some kind of workaround here? Stuck on similar problem, only packed sequences are the issue for me

from nisqa.

Update: when trying to export the model from Linux (or WSL in my case), I get the following, more verbose errors:

Device: cpu
Model architecture: NISQA_DIM
Loaded pretrained model from weights/nisqa.tar
/home/username/miniconda3/envs/nisqa/lib/python3.9/site-packages/torch/onnx/utils.py:1294: UserWarning: Provided key output for dynamic axes is not a valid input/output name
  warnings.warn("Provided key {} for dynamic axes is not a valid input/output name".format(key))
WARNING: The shape inference of prim::PackPadded type is missing, so it may result in wrong shape inference for the exported graph. Please consider adding it in symbolic function.
WARNING: The shape inference of prim::PackPadded type is missing, so it may result in wrong shape inference for the exported graph. Please consider adding it in symbolic function.
/home/username/miniconda3/envs/nisqa/lib/python3.9/site-packages/torch/onnx/symbolic_helper.py:258: UserWarning: ONNX export failed on adaptive_max_pool2d because input size not accessible not supported
  warnings.warn("ONNX export failed on " + op + " because " + msg + " not supported")
/home/username/miniconda3/envs/nisqa/lib/python3.9/site-packages/torch/onnx/symbolic_helper.py:716: UserWarning: allowzero=0 by default. In order to honor zero value in shape use allowzero=1
  warnings.warn("allowzero=0 by default. In order to honor zero value in shape use allowzero=1")
WARNING: The shape inference of prim::PadPacked type is missing, so it may result in wrong shape inference for the exported graph. Please consider adding it in symbolic function.
WARNING: The shape inference of prim::PadPacked type is missing, so it may result in wrong shape inference for the exported graph. Please consider adding it in symbolic function.
Segmentation fault

PS: you can access my script here: https://github.com/miccio-dk/NISQA Notice that run_export.py behaves exactly like run_predict.py except I'm forcing CPU.

I wondor if you have solve this problem. Same Problem I met.

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