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Introduces the RetinaMNISTDataset class for handling the RetinaMNIST dataset, including data loading, transformation, and output shape methods. Adds comprehensive unit tests to verify dataset initialization, item retrieval, tensor conversion, length, and output shape.
Added RetinaMNISTDataset to the datasets module import. Updated the RetinaMNIST dataset test to use the correct dataset name, mock class, and label shape, ensuring consistency with the actual dataset implementation.
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Description
This pull request adds support for the RetinaMNIST dataset to the project. It introduces a new dataset class, integrates it into the dataset registry, and provides comprehensive unit tests to ensure correct functionality.
RetinaMNIST dataset integration:
RetinaMNISTDatasetclass inretinamnist_dataset.py, supporting loading, preprocessing, and combining train/validation splits for the RetinaMNIST dataset, with appropriate transformations and output shape handling.RetinaMNISTDatasetin thedataset_name_to_type_mapin__init__.pyto make it available for use throughout the codebase.Testing:
test_retinamnist_dataset.pywith fixtures and tests for initialization, data retrieval, tensor conversion, length, and output shape ofRetinaMNISTDataset. Uses mocking to avoid external dependencies.Checklist
Please complete the following checklist when submitting a PR. The PR will not be reviewed until all items are checked.
Make sure that the tests passed and the coverage is
sufficient by running
pytest tests --cov=src --cov-report=term-missing.You can do this by running
black src tests.You can do this by running
isort src tests.You can do this by running
mypy src tests.