Deep CFR 기초 모듈 추가

2026-05-06 23:06:23 +09:00
parent 4224ef7a88
commit 6c35b878a5
11 changed files with 371 additions and 0 deletions
@@ -0,0 +1,95 @@
+from __future__ import annotations
+
+import numpy as np
+import pytest
+from coolrl_lost_cities.games.classic.deep_cfr.cfr_math import (
+    normalize_legal_policy,
+    regret_matching,
+    sample_policy,
+)
+from coolrl_lost_cities.games.classic.deep_cfr.encoding import encode_info_state, input_dim
+from coolrl_lost_cities.games.classic.game import GameState, LostCitiesConfig
+
+
+def test_swap_deck_cards_swaps_internal_deck_order_and_validates_bounds() -> None:
+    state = GameState.new_game(LostCitiesConfig(seed=7))
+    before = state.to_snapshot()
+    first = before["deck"][0]
+    last = before["deck"][-1]
+
+    state.swap_deck_cards(0, len(before["deck"]) - 1)
+
+    after = state.to_snapshot()
+    assert after["deck"][0] == last
+    assert after["deck"][-1] == first
+    state.validate_invariants()
+
+    state.swap_deck_cards(0, len(before["deck"]) - 1)
+    assert state.to_snapshot() == before
+
+    with pytest.raises(IndexError, match="deck index out of range"):
+        state.swap_deck_cards(-1, 0)
+    with pytest.raises(IndexError, match="deck index out of range"):
+        state.swap_deck_cards(0, len(before["deck"]))
+
+
+def test_regret_matching_uses_positive_legal_regrets() -> None:
+    policy = regret_matching(
+        np.asarray([1.0, -2.0, 3.0, 5.0], dtype=np.float32),
+        np.asarray([True, True, False, True]),
+    )
+
+    np.testing.assert_allclose(policy, [1.0 / 6.0, 0.0, 0.0, 5.0 / 6.0])
+
+
+def test_regret_matching_falls_back_to_uniform_legal_policy() -> None:
+    policy = regret_matching(
+        np.asarray([-1.0, 0.0, 3.0, 5.0], dtype=np.float32),
+        np.asarray([True, True, False, False]),
+    )
+    no_legal = regret_matching(
+        np.asarray([1.0, 2.0], dtype=np.float32),
+        np.asarray([False, False]),
+    )
+
+    np.testing.assert_allclose(policy, [0.5, 0.5, 0.0, 0.0])
+    np.testing.assert_allclose(no_legal, [0.0, 0.0])
+
+
+def test_normalize_legal_policy_clamps_and_normalizes_legal_weights() -> None:
+    policy = normalize_legal_policy(
+        np.asarray([2.0, -1.0, 4.0, 6.0], dtype=np.float32),
+        np.asarray([True, True, False, True]),
+    )
+    fallback = normalize_legal_policy(
+        np.asarray([0.0, -1.0, 3.0], dtype=np.float32),
+        np.asarray([True, True, False]),
+    )
+
+    np.testing.assert_allclose(policy, [0.25, 0.0, 0.0, 0.75])
+    np.testing.assert_allclose(fallback, [0.5, 0.5, 0.0])
+
+
+def test_sample_policy_uses_cumulative_probability_boundaries() -> None:
+    policy = np.asarray([0.2, 0.3, 0.5], dtype=np.float32)
+
+    assert sample_policy(policy, 0.0) == 0
+    assert sample_policy(policy, 0.21) == 1
+    assert sample_policy(policy, 0.51) == 2
+    assert sample_policy(policy, 0.999) == 2
+
+
+def test_encode_info_state_is_deterministic_and_matches_legal_mask_tail() -> None:
+    state = GameState.new_game(LostCitiesConfig(seed=13))
+
+    encoded = encode_info_state(state, 0)
+    encoded_again = encode_info_state(state, 0)
+    legal_mask = np.asarray(state.unified_legal_mask(), dtype=np.float32)
+
+    assert encoded.dtype == np.float32
+    assert encoded.shape == (input_dim(state),)
+    np.testing.assert_array_equal(encoded, encoded_again)
+    np.testing.assert_array_equal(encoded[-len(legal_mask) :], legal_mask)
+
+    with pytest.raises(ValueError, match="invalid player"):
+        encode_info_state(state, 2)