Furen Xiao a491ae0523 feat(train): implement checkpointing and robust data loading ... Enhance the training pipeline with stateful checkpointing and improve the resilience of the data loading process against filesystem latency and transient I/O errors. - Implement auto-resuming in `train_ddp` by loading model, optimizer, and scheduler states from `state.pt`. - Add atomic state saving using temporary files to prevent corruption. - Introduce `_read_nii` with exponential backoff retries to handle transient NFS/filesystem failures during NIfTI reading. - Add explicit error handling for missing or unreadable label files in `PatchDataset`. - Update `sliding_window_probs` to conditionally apply Test-Time Augmentation (TTA) based on the `tta` parameter. - Add `scripts/test_dataloader.py` for verifying dataset integrity.		2026-09-26 03:44:12 +08:00
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01_build_ntuh_manifest.py	refactor(core): improve data pipeline robustness and manifest generation	2026-09-25 22:12:32 +08:00
02_build_m6_dataset.py	feat: initial project structure	2026-09-25 16:00:37 +08:00
03_scan_lee_t1c.py	feat: initial project structure	2026-09-25 16:00:37 +08:00
04_reconstruct_lee.py	feat: initial project structure	2026-09-25 16:00:37 +08:00
05_build_splits.py	feat: initial project structure	2026-09-25 16:00:37 +08:00
06_pseudo_label.py	feat: initial project structure	2026-09-25 16:00:37 +08:00
07_train.py	feat: initial project structure	2026-09-25 16:00:37 +08:00
08_eval.py	feat: initial project structure	2026-09-25 16:00:37 +08:00
09_run_iterative.py	feat: initial project structure	2026-09-25 16:00:37 +08:00
preprocess.py	feat: initial project structure	2026-09-25 16:00:37 +08:00
scan_procs.py	refactor(core): improve data pipeline robustness and manifest generation	2026-09-25 22:12:32 +08:00
test_dataloader.py	feat(train): implement checkpointing and robust data loading	2026-09-26 03:44:12 +08:00