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Refactor promotion handling in MCTS logic #19

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Merged
Codex-Crusader merged 1 commit into from
Sep 16, 2025
Merged

Refactor promotion handling in MCTS logic #19

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6 changes: 3 additions & 3 deletions azlite_portfolio_clean.py
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Original file line number Diff line number Diff line change
Expand Up @@ -187,7 +187,7 @@ def score_moves(self, state_embed: torch.Tensor,
return logits


# ----------------------------- MCTS -----------------------------------------
# ----------------------------- MCTS -------------------------------

@dataclass
class MCTSNode:
Expand Down Expand Up @@ -344,8 +344,8 @@ def _simulate(self, board: chess.Board, root: MCTSNode) -> float:
if mv.promotion is None:
promo_idxs.append(0)
else:
PROMOTION_MAP.get(mv.promotion, 0)
promo_idxs.append(PROMOTION_MAP.get(mv.promotion, 0))
promo_value = PROMOTION_MAP.get(mv.promotion, 0)
promo_idxs.append(promo_value)
Comment on lines +347 to +348

Copilot AI Sep 16, 2025

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The removed line 347 in the original code suggests there was a redundant PROMOTION_MAP.get(mv.promotion, 0) call that wasn't assigned to any variable. The refactor correctly fixes this by storing the result in promo_value and using it, eliminating the wasteful computation.

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@Codex-Crusader Codex-Crusader Sep 16, 2025

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if adequate approve

logits = self.net.score_moves(
state_embed.squeeze(0),
torch.tensor(from_idxs, dtype=torch.long,
Expand Down
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