Janis Eccarius
9d656624d8
Build & Test (NowChessSystems) TeamCity build finished
Densifying the 98304-dim HalfKP vector per item filled host RAM and crashed the Colab runtime even at small batch sizes. The dataset now yields only the ~64 active feature indices; a custom collate carries (row, col) pairs and the training loop scatters them into a dense [B, INPUT_SIZE] tensor on the GPU. Host RAM stays tiny; GPU holds one dense batch transiently. - NNUEDataset.__getitem__ returns indices via new fen_to_indices. - fen_to_features now derives from fen_to_indices (kept for external callers). - _collate_sparse builds row/col index batches; loaders use it. - train/val loops scatter to a GPU dense batch; loss weighting uses batch size. - Notebook: BATCH_SIZE 4096 -> 8192 (host no longer the limit; GPU is). Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>