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authortslil <tslil@posteo.de>2026-09-12 19:37:56 +0100
committertslil <tslil@posteo.de>2026-09-13 20:15:31 +0100
commit7f1566fb21dfe8c99bc770885cc2cc4e478e16b4 (patch)
treefc93f79abfe985c3d0cf3d95c6d44714b8062371 /src/selfplay.c
parentf3ed463e8a215b0ca3219aebbb14c4a7073a0f9f (diff)
move data generation into the epoch loop
Previously we would spend all of the training epochs on making the network a better predictor of the *initial* TD-leaf values that we computed before the start of the first epoch. There's definitely something stale about this, given that the TD-leaf training targets involved the net evaluation at PVs. I'm not overly confident that this makes sense, but as a kind of compromise between fully on-line TD-leaf and the fully stale version we had before, we now recompute the TD-leaf values in each epoch with the fine-tuned net instead of the epoch 0 net. Perhaps we were just lucky, but this seems to train a strong network under the default setting. More experimentation is required.
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