- Add --cdc_debug flag to enable verbose bucket-by-bucket output
- When debug=False (default): Show tqdm progress bar, concise logging
- When debug=True: Show detailed bucket information, no progress bar
- Improves user experience during CDC cache generation
Fixes shape mismatch bug in multi-subset training where CDC preprocessing
and training used different index calculations, causing wrong CDC data to
be loaded for samples.
Changes:
- CDC cache now stores/loads data using image_key strings instead of integer indices
- Training passes image_key list instead of computed integer indices
- All CDC lookups use stable image_key identifiers
- Improved device compatibility check (handles "cuda" vs "cuda:0")
- Updated all 30 CDC tests to use image_key-based access
Root cause: Preprocessing used cumulative dataset indices while training
used sorted keys, resulting in mismatched lookups during shuffled multi-subset
training.
- Remove @torch.no_grad() decorator from compute_sigma_t_x()
- Gradients now properly flow through CDC transformation during training
- Add comprehensive gradient flow tests for fast/slow paths and fallback
- All 25 CDC tests passing
- Cache all shapes during GammaBDataset initialization
- Eliminates file I/O on every training step (9.5M accesses/sec)
- Reduces get_shape() from file operation to dict lookup
- Memory overhead: ~126 bytes/sample (~12.6 MB per 100k images)
