Unit tests for the models
Nobody has claimed this yet.
Assessment
- Difficulty
- 3/5
- Estimated time
- Half a day
- Newbie friendliness
- 52/100
- Issue type
- Feature
- Clarity
- Mostly clear
- Activity status
- Active
- Tech stack
- python
- Domain
- machine-learning, testing-qa
Research direction
Work goes in tests/test_models.py. Check issue #17 first, since this issue depends on it, and find where ModelA, ModelB, count_params and the layer table are defined. Add tests for the output shapes, the 100,000-parameter limit on ModelB, and agreement between the layer-table total and count_params. Done when pytest passes.
Written by the indexing model from the issue text.
Description
Guards against accidentally breaking the 100k limit.
Files: tests/test_models.py
Tasks
- Test output shapes of ModelA and ModelB
- Test
count_params(ModelB()) <= 100_000 - Test that the layer-table parameter total equals
count_params
Done when
pytest passes.
Depends on
#17
Close with a commit or PR message containing Closes #<this issue>.
- Dominant language
- Jupyter Notebook
- Stars
- 0
- Forks
- 0
- Avg merge
- 1m
- Merged PRs (30d)
- 3
Getting set up
This project ships no dev container, Dockerfile or contributing guide, so setting up is up to you: start from its README, and see our first-contribution guide for the general steps.
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
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