Add train metrics in Lightning Pipeline output

[JeremieGince]

Description

This pull request updates the training and validation metrics handling in the lightning_pipeline.py pipeline, ensuring both train and validation metrics are saved and returned, and adds corresponding test assertions. The changes improve clarity and completeness of reported metrics after running the pipeline.

Pipeline metrics handling improvements:

• Modified the run method in lightning_pipeline.py to separately compute and save both train and validation metrics, and return a merged dictionary containing both sets of metrics.
• Added a new run_train_validation method to evaluate metrics on the training set, save them, and ensure metric keys are renamed from val_ to train_ for clarity.
• Updated the run_validation method to save validation metrics to the checkpoint folder after computation.

Testing improvements:

• Enhanced the test_run_and_run_test test to assert that the output of run() includes both val_loss and train_loss, and that test_loss is only present after calling run_test().

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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
899	873	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: 8e82e7e by action🐍