Use inference_mode for evaluation methods

[JeremieGince]

Description

Import torch.autograd.inference_mode and apply @inference_mode() to run_train_validation, run_validation, and run_test. This disables autograd during evaluation/metric gathering, reducing memory usage and overhead and improving runtime performance. The import was added near the other imports at the top of lightning_pipeline.py.

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Checklist

Please complete the following checklist when submitting a PR. The PR will not be reviewed until all items are checked.

• All new features include a unit test.
  Make sure that the tests passed and the coverage is
  sufficient by running pytest tests --cov=src --cov-report=term-missing.
• All new functions and code are clearly documented.
• The code is formatted using Black.
  You can do this by running black src tests.
• The imports are sorted using isort.
  You can do this by running isort src tests.
• The code is type-checked using Mypy.
  You can do this by running mypy src tests.

[github-actions]

☂️ Python Coverage

current status: ✅

Overall Coverage

Lines	Covered	Coverage	Threshold	Status
901	875	97%	90%	🟢

New Files

No new covered files...

Modified Files

File	Coverage	Status
src/matchcake_opt/tr_pipeline/lightning_pipeline.py	96%	🟢
TOTAL	96%	🟢

updated for commit: 4f9df9f by action🐍