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How to tranform efficient-pytorch to efficient-onnx #20
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Yes, I can try to make the kernel size static in the next significant update. |
@lukemelas Thansk! |
Done! I had to change some things with the padding, so it took a little while. Here is an example: |
Closing this issue, but definitely re-open if you have any issues. Also, let me know if exporting to ONNX / mobile works for you! |
@lukemelas Successd and thanks! |
Great to hear! |
@lukemelas Hey! Appreciate your great work. |
Please use model.set_swish(memory_efficient=False). |
@bkhti4 Thanks! When I replaced SwishImplementation() with Swish(), I converted the model to onnx successfully. |
How there's The older functions are still included for backward compatibility with old versions of PyTorch |
@lukemelas Hi, when I simply ran
, and got error as blow, any ideas? Thanks. environment: |
Is it resolved? I need your help! |
@aojue1109 I converted the model to onnx successfully. There's my gist link. |
@chilin0525 thanks!! |
I have tried to convert efficient-pytorch to efficient-onnx with api (torch.onnx.export), but I meet a problem showing below info
Failed to export an ONNX attribute, since it's not constant, please try to make things (e.g., kernel size) static if possible
How could I fix it ?
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