Implement DeepDrug model

[kajocina]

Closes #14

Added the DeepDrug model, trying to copy as much as possible from their approach. The paper didn't use any context features, but I implemented the model so that it could be used in both ways. I ran the model with and without context feats on DrugCombDB with around 0.76 AUROC (no context features led to a minor drop in AUROC).

Provided an example that runs the model and a unit test which tests both the context and no-context modes of this model.

• [X] Unit tests provided for these changes
• [X] Documentation and docstrings added for these changes

[cthoyt]

@kajocina please pass CI before we review this PR. You can either read the results in the GitHub browser or run tox locally to see all issues that need to be fixed

[cthoyt]

I would suggest implementing this class only to have the functionality as originally described, then to consider subclassing it to have your additional functionality (adding in the context features may actually make it the same as one of the other models)

[kajocina]

@kajocina please pass CI before we review this PR. You can either read the results in the GitHub browser or run tox locally to see all issues that need to be fixed

@cthoyt I am getting CI errors from code in our tox dependencies so I can't really fix those, e.g.:

lint/bin/activate_this.py:28: error: "str" has no attribute "decode"; maybe "encode"?
lint/bin/activate_this.py:31: error: Module has no attribute "real_prefix"
Found 2 errors in 1 file (checked 39 source files)

I did fix tox issues related to my commits now.

[cthoyt]

@kajocina you can try running tox where it automatically rebuilds the virtualenvs with tox -r. If that's not going well you can even consider reinstalling tox itself. However, the CI run on GitHub actions still shows issues in the lint and documentation tasks. Please look into those

[kajocina]

@cthoyt thanks for the tip, rebuilt tox and works ok, local CI was green now. I added the wrapper as you suggested, but it didnt really decrease the number of lines of code in total, only the number of assignments performed.

[cthoyt]

@kajocina the goal was to make the model more legibile. I will demonstrate by pushing to your branch - see 1c60cae .

[codecov-commenter]

Codecov Report

Merging #68 (e459ba6) into main (5449f96) will increase coverage by 0.14%. The diff coverage is 97.56%.

@@            Coverage Diff             @@
##             main      #68      +/-   ##
==========================================
+ Coverage   93.87%   94.01%   +0.14%     
==========================================
  Files          29       29              
  Lines         832      869      +37     
==========================================
+ Hits          781      817      +36     
- Misses         51       52       +1     

Impacted Files	Coverage Δ
chemicalx/models/deepdrug.py	96.77% <96.66%> (-3.23%)	:arrow_down:
tests/unit/test_models.py	100.00% <100.00%> (ø)

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[cthoyt]

Now that we have all of the implementations, I can see some interesting abstractions we can provide!