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This pull request introduces a comprehensive testing infrastructure for the VBLL library, including automated CI setup, configuration files, fixtures, and documentation. The changes enable robust, reproducible, and flexible testing using pytest, and provide clear guidance for contributors on running and extending the test suite.
Testing Infrastructure and Automation
.github/workflows/ci.yml) to automatically run tests on pushes and pull requests tomain/masterbranches. The workflow sets up Python, installs dependencies (including PyTorch), and runs the test suite with pytest.run_tests.py) that provides a command-line interface for running the test suite with options for quick/unit/integration/benchmark tests, parallel execution, coverage, and optional GPU/JAX support.Test Suite Configuration and Fixtures
pytest.inito configure pytest: specifies test discovery patterns, verbosity, warning filters, and custom markers for slow, GPU, integration, and unit tests.tests/conftest.pywith a comprehensive set of fixtures for devices, seeds, batch sizes, sample data, and common parameter sets for classification and regression layers, supporting reproducible and parameterized tests.Documentation and Developer Guidance
tests/README.mddetailing test structure, categories, running instructions, coverage, benchmarks, and troubleshooting tips, guiding contributors on best practices for testing and extending the suite.README.mdwith instructions for installing test dependencies and running tests using pytest.Project Configuration
pyproject.tomlto includepytestas a development dependency, ensuring test requirements are managed via Poetry.tests/__init__.pyto mark the tests directory as a package.These changes collectively establish a solid foundation for automated and manual testing, improving code quality and maintainability.