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Run3 Run Unit Test in Python 3 10 Environment

Skill cxcscmu/SkillLearnBench/skills/b3-teacher-feedback-claude-haiku-4-5/nlp-paper-reproduction/run3_Run-Unit-Test-in-Python-3-10-Environment

[COLM'26] SkillLearnBench is the first benchmark for evaluating continual learning methods that automatically generate agent skills.

Install
npx -y skills add cxcscmu/SkillLearnBench --skill run3_Run-Unit-Test-in-Python-3-10-Environment

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What its author says it does

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Use to execute the unit test within the Python 3.10 virtual environment after implementing the loss function. This validates the implementation against fixed input tensors.

SKILL.md

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  1. Ensure Python 3.10 environment is active:

    source /root/.venv310/bin/activate
python -VV

  2. Navigate to project root:

    cd /root/SimPO

  3. Run the unit test:

    python unit_test/unit_test_1.py

  4. Verify output file was created:

    ls -lh /root/loss.npz

  5. Inspect the saved loss values (optional verification):

    python -c "import numpy as np; data = np.load('/root/loss.npz'); print(data['losses'])"

  6. Check for any error messages:

    • If test fails, review error traceback
    • Verify tensor shapes match test expectations
    • Confirm loss computation logic against paper formula

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