coolguyandClaude Opus 4.7
a7ab94e096
Implements the central inference server pattern: a dedicated GPU process owns advantage/strategy/league networks, batches policy requests across traversal workers via shared-memory tensor pool, and returns logits. Workers route forward calls through InferenceClient / NetworkProxy when traversal.inference_backend == "server". Default remains traversal.inference_backend: local. The server backend regresses iter time ~3.8× on the inspected default config (small-model dispatch + sync-blocking traversal capping realized batch at ~num_workers=8 instead of the bs=64-256 needed to amortize IPC overhead). Keeping the implementation behind the flag lets us re-enable when (a) model size grows, (b) per-worker interleaved traversal lands, or (c) eval becomes dominant — see docs/performance.md "Option A Bench Result and Structural Ceiling" for the full diagnosis. Plumbing included: - inference_buffers.py: shared-memory tensor pool with slot management. - inference_client.py: per-worker client + NetworkProxy adapter for the existing traversal.pyx call sites. - inference_server.py: spawn-context server process with batch-window aggregation, weight sync, shutdown sentinel. - bench_inference_backend.py: A/B between local and server backends with eval/checkpoint disabled. - test_inference_server.py: round-trip and integration tests. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
coolrl-lost-cities
Focused Lost Cities extraction from the legacy coolrl repository.
The current implementation starts with the classic two-player card game:
- classic 5-expedition rules by default
- Python/Cython game engine
- env wrapper
- random, passive-discard, and safe-heuristic bots
- core rule, scoring, mask, env, canonical-state, bot, and GUI smoke tests
Training code, Deep CFR, learned-policy evaluation, GUI, and web client are intentionally outside the first port.
Development
uv run pytest tests/games/classic
uv run lost-cities-classic
For future GUI work, install the optional GUI dependencies:
uv sync --extra gui
Run the classic pygame GUI:
uv run lost-cities-classic-gui --mode pvc --bot safe-heuristic
The GUI uses the in-process Cython game engine.
Basic Usage
from coolrl_lost_cities.games.classic import GameState, build_bot, classic_config
state = GameState.new_game(classic_config(seed=1))
bot = build_bot("random", seed=1)
while not state.terminal:
state.apply_action(bot.act(state))
print(state.total_score(0), state.total_score(1))
See classic port notes for the current direction.