feat(KMR): add end-to-end integration tests for models#2
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piotrlaczkowski merged 9 commits intomainfrom Oct 30, 2025
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…d Terminator models - Introduced comprehensive integration tests for Autoencoder, SFNEBlock, and TerminatorModel, covering workflows with and without KDP preprocessing. - Each test validates model training, prediction accuracy, and serialization. - Implemented error handling tests for invalid input data and performance tests with larger datasets. - Enhanced documentation within test files to clarify testing procedures and expectations.
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- Moved the `extend-unsafe-fixes` setting to the lint section in `ruff.toml` for better organization. - Updated per-file ignores to specify patterns for test files, enhancing linting accuracy. - Reformatted code in various files for consistency, including adjustments to whitespace and line breaks. - Improved readability of test functions and model definitions by standardizing formatting across the codebase.
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- Updated `ruff.toml` to include additional linting rules for test files, improving code quality checks. - Reformatted multiple Python files to ensure consistent whitespace and line breaks, enhancing readability. - Adjusted function signatures and argument formatting across various test and model files for better clarity. - Improved overall code organization and maintainability through consistent formatting practices.
- Expanded per-file ignores in `ruff.toml` for test, example, script, and experimental files to include additional linting rules, enhancing code quality checks. - Adjusted formatting in `test_terminator_e2e.py` for improved readability by modifying argument placement in the `model.predict` call.
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- Removed unnecessary whitespace in `__init__.py` and `autoencoder.py` to enhance code readability. - Ensured consistent formatting across files for better maintainability.
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- Updated instance variable declarations in multiple layers to include type annotations for better clarity and type safety. - Added validation checks in various layers to ensure they are properly built before use, improving error handling and robustness. - Refactored the documentation and comments for clarity and consistency across the codebase.
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- Upgraded Poetry version from 1.8.3 to 2.1.2 in poetry.lock. - Added 'plotly' dependency in pyproject.toml for enhanced visualization capabilities. - Modified GitHub Actions workflows to ensure documentation builds only on the main branch and streamlined PR preview conditions. - Improved documentation deployment configurations for better clarity and efficiency.
- Added write permissions for contents, pull-requests, pages, and id-token in the PR_PREVIEW.yml workflow to enhance deployment capabilities and streamline preview generation.
- Updated the documentation workflow to include caching for Poetry dependencies and MkDocs builds, improving efficiency. - Introduced a new pre-commit workflow to enforce code quality checks on pull requests, including title validation and pre-commit hooks. - Added a comprehensive testing workflow with linting, type checking, and unit/integration tests for multiple Python versions, ensuring robust code quality. - Refactored layer classes to ensure they are built before use, enhancing error handling and stability.
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…d Terminator models