ONNX CI workflow is broken

[pmeier]

Since the 5th of May our CI workflow for ONNX is broken (commit 970ba35). Looking at the warnings emitted by the failing tests

WARNING: The shape inference of prim::Constant type is missing, so it may result in wrong shape inference for the exported graph. Please consider adding it in symbolic function.
[...]
AssertionError: The values for attribute 'shape' do not match: torch.Size([1, 4]) != torch.Size([0, 4]).

Two models are affected faster_rcnn and mask_rcnn. To reproduce run:

pytest test/test_onnx.py -k "test_faster_rcnn" 
pytest test/test_onnx.py -k "test_mask_rcnn" 

I believe a recent patch to primtorch might be the offender here. cc @neginraoof @seemethere @mruberry

[mruberry]

It does seem like primTorch would be to blame because we also use the "prim" or "prims" prefix, but we don't have a prim::Constant or any C++ code

[pmeier]

Looking through the commit history again, pytorch/pytorch#76622 might be the offender. See #5971 (comment).

[sanchitintel]

Hi @pmeier @datumbox,

Could you please elaborate on how PyTorch PR #76622 could be causing this issue?
It adds some prim interned strings, but could that affect shape inference of prim::Constant?

Thank you!

[pmeier]

My bad, I linked the wrong PR 🤦 Sorry for the noise. It should have been pytorch/pytorch#76875 See #5971 (comment)

[pmeier]

After some painful bisection, I finally found the real offender: pytorch/pytorch#73284. After seeing that the PR title contains the phrase ONNX and our ONNX tests are failing, I have no idea how I missed that when looking at the PRs 🤦