Crowd-Kit Learning

[pilot7747]

This is just an example of what this subpackage will contain.

We need to configure setup.cfg and add new tests. Here I suggest to discuss the concept.

[pilot7747]

Received a concept approve by @dustalov. Now start to adding tests and trying to configure it as a subpackage with extra requirements. Also waiting for approve by @zdchu to use a code derived from the original CoNAL implementation

[codecov-commenter]

Codecov Report

Base: 93.02% // Head: 93.07% // Increases project coverage by +0.04% 🎉

Coverage data is based on head (7a1f876) compared to base (3129208).
Patch coverage: 98.05% of modified lines in pull request are covered.

Additional details and impacted files

@@            Coverage Diff             @@
##             main      #47      +/-   ##
==========================================
+ Coverage   93.02%   93.07%   +0.04%     
==========================================
  Files          43       47       +4     
  Lines        1908     2007      +99     
==========================================
+ Hits         1775     1868      +93     
- Misses        133      139       +6     

Impacted Files	Coverage Δ
crowdkit/aggregation/__init__.py	66.66% <ø> (-27.46%)	⬇️
crowdkit/learning/crowd_layer.py	94.73% <94.73%> (ø)
crowdkit/learning/__init__.py	100.00% <100.00%> (ø)
crowdkit/learning/conal.py	100.00% <100.00%> (ø)
crowdkit/learning/text_summarization.py	52.38% <100.00%> (ø)
crowdkit/learning/utils.py	100.00% <100.00%> (ø)

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[pilot7747]

@dustalov The PR is ready for a review. @zdchu has approved the code usage and now the tests are passing.

[dustalov]

• Please add py.typed to every new source directory, excluding tests: https://github.com/Toloka/crowd-kit/blob/main/crowdkit/py.typed
• Kindly move the summarization aggregation tests to the learning module tests
• We have to do it in a separate PR, but have you tried installing Crowd-Kit without the learning module to a bare venv? Has it worked?
• If you initialize parameters randomly, is it possible to choose the seed value and then canonize the tests?

[pilot7747]

• Kindly move the summarization aggregation tests to the learning module tests

These tests have never existed. One of the reasons it is difficult to implement them is the fact they are extremely heavy. You need to download a 3 GB model from HuggingFace and do this on every commit.

• If you initialize parameters randomly, is it possible to choose the seed value and then canonize the tests?

Yes, but I'm not sure this will be consistent across platforms and PyTorch versions.

[dustalov]

Good. We're almost there. Please fix the newlines and we're good to go.

[pilot7747]

Please fix the newlines and we're good to go.

What newlines?

[dustalov]

This one: https://github.com/Toloka/crowd-kit/pull/47/files/b4d07cc2eb30db31ca6234d8bec4f7530afe3dec#diff-f1e0b25eeb099b940ecba4b0d893c38ef7ad7d122ab962a58118fef33936d4f5

[pilot7747]

This one: https://github.com/Toloka/crowd-kit/pull/47/files/b4d07cc2eb30db31ca6234d8bec4f7530afe3dec#diff-f1e0b25eeb099b940ecba4b0d893c38ef7ad7d122ab962a58118fef33936d4f5

Done. I specifically checked for other py.typed files and looked if they have a trailing newline but I didn't realize that GitHub doesn't show trailing newlines.

[dustalov]

Good.

[pilot7747]

Btw, yes, I've checked, the package installs without learning extra