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Enable ONNX test in circle CI #3144
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Hi @jiafatom Thanks for the PR!
I don't know what could be the issue. This looks like something inside ORT might be problematic? |
Codecov Report
@@ Coverage Diff @@
## master #3144 +/- ##
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Coverage 72.75% 72.75%
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Files 99 99
Lines 8979 8979
Branches 1431 1431
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Hits 6533 6533
Misses 1999 1999
Partials 447 447 Continue to review full report at Codecov.
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@fmassa Just fixed the issue, and test_onnx passes in CircleCI, so we are enabling test_onnx now. Could you please sign off? Thank you! |
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Awesome work and investigation @jiafatom. Thanks for the PR.
@jiafatom I think the test broke again, possibly due to upstream changes. Could you have a look on your side and confirm? |
@datumbox The latest job failure is https://travis-ci.org/github/pytorch/vision/jobs/748808277 v0.8.2 did Try to use the released version of onnxruntime. |
Hi @fmassa - thank you for your help with this. @jiafatom is working with our team. This latest PR #3160 should fix the tests. It was broken because of a commit that went into PyTorch recently (just yesterday). It seems like there was a bit of difference in test running in PyTorch CI which is why this wasn't immediately detected for the PyTorch commit. We are going to update the version of tests running in PyTorch CI so that it matches vision tests with priority. |
@spandantiwari @jiafatom I confirm that the PR #3160 fixed the issue. Thanks a lot for your speedy response and support. We just merged the fix into master. Have great weekend. |
Thanks @jiafatom and @spandantiwari for the help! |
Summary: * Enable ONNX test in circle CI Reviewed By: datumbox Differential Revision: D25531035 fbshipit-source-id: 022b8613ac5bd8cb7165e9cbaa9daf99a9e1694e
The PR disable onnx test since it is failing since 11/14/2020.
I did a test locally and find that onnx need update to 1.8.0. So This PR aims to enable onnx test by pulling latest onnx==1.8.0.The root cause is that
onnx_shape_inference
is enabled on 11/13/2020, but the shape inference PR (committed 9/30/2020) does not handle invalid dynamic axes input well. In torch vision CI, there are some invalid axes, so we fixed it in this PR, and enable onnx test. In a separate pytorch PR, we add exception handling for invalid axes input, then it will give meaningful failure msg rather than seg fault here.