Commit Graph
2 Commits
Author SHA1 Message Date
coolguyandClaude Opus 4.7 b6863b3ba0 Fix ColorSharedNetwork to use real per-color encoding layout
ColorSharedNetwork previously sliced the input vector into n_colors equal
chunks (input_dim // n_colors). The slice boundaries do not align with the
actual encoding layout: adjacent slices contain phase flags, hand slots,
expedition state, scores, etc. mixed together. The "color-shared" encoder
was therefore sharing weights across semantically unrelated chunks, not
across per-color blocks. The single archived run that exercised this path
(2026-05-07_092137_color_shared_attention_1000iter) was killed at iter 41
and produced no eval data, so we have no measurement of whether a real
per-color architecture would help.

Adds compute_lost_cities_color_layout(input_dim) which returns explicit
per-color and common index lists for the standard Lost Cities encoding
(n_colors=5, hand_size=8, n_ranks=9). It recognises input_dim values
171, 219, 249, 297 across derived_playability and slot_aware_playability
flag combinations.

Per-color block (39 dims when derived_playability is on): both players'
expedition state for that color, discard top, public-histogram row,
pending-discard one-hot bit, legal-action draw-pile bit, and the
derived_playability per-color block. Slot-aware features are slot-major
and stay in common.

ColorSharedNetwork.forward now indexes per-color blocks via the layout
when input_dim matches a known schema. For other dims (unit tests,
non-Lost Cities use), it falls back to chunked slicing with a UserWarning
- preserves backward compatibility for tests but makes the legacy
behaviour visible.

No fair test of the new architecture was run as part of this commit.
Documented in docs/plans/deep-cfr-selectivity.md section 7.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-10 14:42:32 +09:00
coolguyandClaude Haiku 4.5 cee8849e04 Add backward-compatible color_shared network architecture
- Add network.kind field to config (mlp/color_shared)
- Implement ColorSharedNetwork that:
  - Splits input into 5 equal color blocks
  - Encodes each block with shared weights
  - Pools with mean/max aggregation
  - Concatenates pooled embeddings with remainder
  - Outputs same action logits as MLP
- Add ColorAttention for optional self-attention over color embeddings
- Add network.color_attention_layers and color_attention_heads config
- Maintain full backward compatibility (default kind=mlp)
- Add 28 comprehensive tests covering all architectures

Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>
2026-05-07 09:18:13 +09:00