Closed morriscb closed 10 months ago
Merging #620 (747a8de) into main (51166ba) will increase coverage by
0.14%
. The diff coverage isn/a
.
@@ Coverage Diff @@
## main #620 +/- ##
==========================================
+ Coverage 96.13% 96.27% +0.14%
==========================================
Files 105 105
Lines 7944 8249 +305
Branches 775 775
==========================================
+ Hits 7637 7942 +305
Misses 229 229
Partials 78 78
Flag | Coverage Δ | |
---|---|---|
general_tests | 96.27% <ø> (+0.14%) |
:arrow_up: |
Flags with carried forward coverage won't be shown. Click here to find out more.
I dug into it also. The issue is a conflict with
deepinterpolation @ git+https://github.com/danielsf/deepinterpolation@staging/cleaner/ophys_etl
this installs tensorflow 2.5.0 which is pretty old, and has typing_extensions pinned to ~=3.7 https://github.com/tensorflow/tensorflow/blob/v2.5.0/tensorflow/tools/pip_package/setup.py#L93C5-L93C33
this conflicts with pytorch which is trying to install the latest typing_extensions. You can see that in the build output.
Only typing_extensions >= 3.10 apparently has the ParamSpec https://github.com/optuna/optuna/issues/3558
Another fix would be to instead of using Scott's fork of deepinterpolation (it's not even being used in the main branch ?) you could change it to deepinterpolation @ git+https://github.com/AllenInstitute/deepinterpolation_ai_internal
which has tensorflow unpinned. More recent versions of tensorflow have a more relaxed constraint on that library: https://github.com/tensorflow/tensorflow/blob/v2.14.0/tensorflow/tools/pip_package/setup.py#L103
Sorry that was a long comment.
Not at all. Sounds like a better solution. Just changed the deepinterpolation requirement and seeing what happens.
Still getting the crash on 3.8. I'll keep the switch from Scott's fork and also pin torch and see if that fixes.
It looked like a different issue? You might to add https://github.com/AllenInstitute/ophys_etl_pipelines/blob/workflow_v2/src/ophys_etl/workflows/Dockerfile#L19 to the Dockerfile
Pin torch to 1.13.1.
The version of suite2p we are using grabs torch version >=1.7.1. There is a more recent version that seems to be causing the issue. Subsequent suite2p releases (latest is 0.14 ours is 0.10.2) pin the version of torch to a similar value. Attempted to update suite2p to 0.14 and 0.11 but found failures in testing one of which is non trivial. Suggest deploying this for now and creating a ticket to bump the suite2p version to 0.14 so we can unpin in our requirements.