36 lines
1.3 KiB
Python
36 lines
1.3 KiB
Python
# -*- coding: utf-8 -*-
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# Created by: Vincentzyx
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from douzero.env.game import GameEnv
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from douzero.evaluation.deep_agent import DeepAgent
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RealCard2EnvCard = {'3': 3, '4': 4, '5': 5, '6': 6, '7': 7,
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'8': 8, '9': 9, 'T': 10, 'J': 11, 'Q': 12,
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'K': 13, 'A': 14, '2': 17, 'X': 20, 'D': 30}
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card_play_model_path_dict = {
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'landlord': "baselines/douzero_WP/landlord.ckpt",
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'landlord_up': "baselines/douzero_WP/landlord_up.ckpt",
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'landlord_down': "baselines/douzero_WP/landlord_down.ckpt"
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}
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user_position = "landlord" # 玩家角色代码：0-地主上家, 1-地主, 2-地主下家
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ai_players = [0, 0]
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ai_players[0] = user_position
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ai_players[1] = DeepAgent(user_position, card_play_model_path_dict[user_position])
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env = GameEnv(ai_players)
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card_play_data_list = {}
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def GetWinRate(cards):
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env.reset()
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card_play_data_list.update({
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'three_landlord_cards': [RealCard2EnvCard[i] for i in "333"],
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'landlord': [RealCard2EnvCard[i] for i in cards],
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'landlord_up': [RealCard2EnvCard[i] for i in "33333333333333333"],
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'landlord_down': [RealCard2EnvCard[i] for i in "33333333333333333"]
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})
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env.card_play_init(card_play_data_list)
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action_message = env.step(user_position)
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win_rate = float(action_message["win_rate"].replace("%",""))
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return win_rate |