-
Notifications
You must be signed in to change notification settings - Fork 2.1k
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Improve error robustness of unit tests #5535
Conversation
Codecov Report
@@ Coverage Diff @@
## master #5535 +/- ##
==========================================
- Coverage 75.43% 75.19% -0.25%
==========================================
Files 711 711
Lines 65757 65757
==========================================
- Hits 49607 49449 -158
- Misses 16150 16308 +158
Flags with carried forward coverage won't be shown. Click here to find out more.
... and 4 files with indirect coverage changes 📣 Codecov offers a browser extension for seamless coverage viewing on GitHub. Try it in Chrome or Firefox today! |
Thanks, but we still have an issue... |
This is weird. I cannot reproduce the error with the same PyTorch version... |
Is this operation actually used? |
Are you talking about the We still use the |
I mean the matrix inverse function, not wpe or beamformer. |
Because it is using the |
Got it. I want to remove such dependencies in the future. |
I think so. It is what I did before, and probably we can just replace from espnet.nets.pytorch_backend.frontends.dnn_beamformer import DNN_Beamformer
from espnet.nets.pytorch_backend.frontends.dnn_wpe import DNN_WPE with the new implementations in espnet2 from espnet2.enh.layers.dnn_beamformer import DNN_Beamformer
from espnet2.enh.layers.dnn_wpe import DNN_WPE |
Sounds good! |
I think at least we can remove |
Nice! |
|
OK, it passes the test! |
Sure. |
for more information, see https://pre-commit.ci
Can you remove it at https://github.com/espnet/espnet/blob/master/setup.py#L42? |
Yes, I already removed it in the latest commit. |
Thanks a lot! |
What?
This PR is a followup PR of #5523 to improve two unit tests to avoid occasional errors caused by numerical precision or randomness.
Why?
Sometimes we may observe errors as in https://github.com/espnet/espnet/actions/runs/6719461822/job/18261148245 which are essentially numerical issues. After the modifications in this PR, these errors should be avoided in most cases.