[ENH] Adience download with credentials - #155
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…onfig hashing - Replace filesystem-based partition logic with CSV-based train/test splits - Introduce deterministic cache key based on ranges, test_size and version - Persist split configuration in JSON alongside cached splits - Remove symlink-based partitioning in favour of CSV-driven loading - Add split cache validation via config.json and file existence checks
victormvy
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May 12, 2026 07:53
[MNT] Use GPU runner wrapper script to avoid OOM errors
…onfig hashing - Replace filesystem-based partition logic with CSV-based train/test splits - Introduce deterministic cache key based on ranges, test_size and version - Persist split configuration in JSON alongside cached splits - Remove symlink-based partitioning in favour of CSV-driven loading - Add split cache validation via config.json and file existence checks
…o enh/adience-download
franberchez
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May 13, 2026
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Thanks @victormvy , great job on the improvement. The new fake dataset definition is better, and giving users the option to download the full dataset with their credentials is a fantastic touch.
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This PR introduces several improvements and refactors to the
Adiencedataset class, primarily focusing on download handling, API consistency, and test robustness.1. Automatic dataset download
__init__:downloadusernamepassworddownload=Trueand valid credentials are provided, the dataset is automatically downloaded into the specified root directory.2. Root directory behaviour update
rootparameter has been updated:torchvision.datasets.VisionDataset.adiencesubdirectory.3. Warning for
rangesmodificationrangesparameter.4. Test suite improvements
The test suite for the Adience dataset has been significantly expanded and refactored:
rangeschangestest_sizechanges5. Test utilities refactor
tests/utils/adience.py