Dev

[JeremieGince]

Description

This pull request updates several Jupyter notebooks and the project dependencies to improve compatibility, reproducibility, and hardware specification. The most significant changes include explicitly setting the computation accelerator to CPU in training pipelines, updating the matchcake package version, and refactoring quantum operation imports and usage in the deep learning notebook.

Dependency updates:

• Updated the matchcake package requirement in pyproject.toml from >=0.0.4 to >=0.1.2 to ensure compatibility with newer features and fixes.
• Added jupyter and notebook as development dependencies in pyproject.toml for improved local notebook support.

Notebook improvements:

• Explicitly set accelerator="cpu" in the pipeline initialization for notebooks/nif_deep_learning.ipynb, notebooks/ligthning_pipeline_tutorial.ipynb, and notebooks/automl_pipeline_tutorial.ipynb to ensure CPU usage for training. [1] [2] [3] [4]
• Refactored quantum operation imports and usage in notebooks/nif_deep_learning.ipynb from SptmfRxRx and SptmFHH to CompRxRx and CompHH for improved clarity and compatibility with the updated matchcake package. [1] [2]

Minor notebook adjustments:

• Reduced automl_iterations and inner_max_time parameters in notebooks/nif_deep_learning.ipynb to enable faster tutorial runs.
• Added empty outputs and execution_count fields to several notebook cells for consistency with Jupyter notebook standards. [1] [2] [3]

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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
882	859	97%	90%	🟢

New Files

No new covered files...

Modified Files

No covered modified files...

updated for commit: ee7bca9 by action🐍