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ONNX operators needed to be supported #17

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daquexian opened this issue Dec 11, 2018 · 11 comments
Open
4 of 5 tasks

ONNX operators needed to be supported #17

daquexian opened this issue Dec 11, 2018 · 11 comments

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@daquexian
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daquexian commented Dec 11, 2018

This issue is to summarize all operators which needed to be supported. If you want an operator to be supported, please feel free to post it here.

@AmienKhaled
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Constant operator

@daquexian
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PReLU has been supported in #23

@AmienKhaled I'll implement it soon

@daquexian
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daquexian commented Jan 11, 2019

@AmienKhaled @yunhaia

In version 0.6.0, identity, prelu and constant op should be supported (please also use the latest onnx2daq)

@daquexian daquexian pinned this issue Jan 11, 2019
@ericdanz
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Reshape can only be the last layer

@daquexian
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@ericdanz reshape layer is somewhat special due to the difference between nhwc(nnapi) and nchw(onnx) layout. I think there is no general, simple way to implement reshape layer, and most reshape layers in an onnx model are indeed generated implicitly. Could you please provide your model so that I can analyze it?

@ericdanz
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I can share the onnx file. Quick warning - it's a bit complicated ;)
https://drive.google.com/file/d/1WdWn12HPr5Ziz69PBk-JyU8YtiEfU2mu/view?usp=sharing

There are a few places reshape is used, in my special batchnorm and shuffle-net like layers.

@daquexian
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daquexian commented Jan 22, 2019

@ericdanz Thanks for your model. Unfortunately, the reshape here is hard to implement in nnapi. I'll open another issue to track it. However, it may be a long-term work.

@ericdanz
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Concat is causing some problems - had to disable the shape checking in shaper.cpp

Upsample is also not supported yet.

Made a model that is compatible, about to test it out! Very excited to see more and more ops supported ;)

@daquexian
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daquexian commented Jan 28, 2019 via email

@mbishop-neurala
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Transpose would be useful when converting caffe models.

@neginraoof
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@ericdanz @daquexian Do you happen to have such large pytorch model that could be further optimized after ONNX export?

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