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Daochen Zha
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docs/api.md
42
docs/api.md
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@ -17,31 +17,31 @@ The definitions of the fields are as follows:
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* `index`: Integer. The index of the game of the same environent and same agent. It is in the range \[0, eval_num-1\]
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| type | Resource | Parameters | Description |
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|------|-------------------------------------|-------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------|
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| GET | tournament/launch | `eval_num`, `name` | Launch tournment on the game. Each pair of models will play `eval_num` times. Results will be saved in database. |
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| GET | tournament/query\_game | `name`, `index`, `agent0`, `agent1`, `win`, `payoff`, `elements_every_page`, `page_index` | Query the games with the given parameters |
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| GET | tournament/query\_payoff | `name`, `agent0`, `agent1`, `payoff` | Query the payoffs with the given parameters |
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| GET | tournament/query\_agent\_payoff | `name`, `elements_every_page`, `page_index`, | Query the payoffs of all the agents |
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| GET | tournament/replay | `name`, `agent0`, `agent1`, `index` | Return the replay data |
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| POST | tournament/upload\_agent | `model`(Python file), `name`, `game`, | Upload a model file. `name` is model ID |
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| GET | tournament/delete\_agent | `name` | Delete the agent of the given name |
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| GET | tournament/list\_uploaded\_agents | `game` | list all the uploaded agents |
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| GET | tournament/list\_baseline\_agents | `game` | list all the baseline agents |
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| GET | download\_examples | `name` | download the example agents |
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|------|-------------------------------------|-------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------|
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| GET | tournament/launch | `num_eval_games`, `name` | Launch tournment on the game. Each pair of models will play `num_eval_games` times. Results will be saved in database. |
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| GET | tournament/query\_game | `name`, `index`, `agent0`, `agent1`, `win`, `payoff`, `elements_every_page`, `page_index` | Query the games with the given parameters |
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| GET | tournament/query\_payoff | `name`, `agent0`, `agent1`, `payoff` | Query the payoffs with the given parameters |
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| GET | tournament/query\_agent\_payoff | `name`, `elements_every_page`, `page_index`, | Query the payoffs of all the agents |
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| GET | tournament/replay | `name`, `agent0`, `agent1`, `index` | Return the replay data |
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| POST | tournament/upload\_agent | `model`(Python file), `name`, `game`, | Upload a model file. `name` is model ID |
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| GET | tournament/delete\_agent | `name` | Delete the agent of the given name |
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| GET | tournament/list\_uploaded\_agents | `game` | list all the uploaded agents |
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| GET | tournament/list\_baseline\_agents | `game` | list all the baseline agents |
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| GET | download\_examples | `name` | download the example agents |
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### Example API
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| API | Description |
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|------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------|
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| http://127.0.0.1:8000/tournament/launch?eval\_num=200&name=leduc-holdem | Evaluate on Leduc Holdem with 200 games for each pair of models |
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| http://127.0.0.1:8000/tournament/launch?num_eval_games=200&name=leduc-holdem | Evaluate on Leduc Holdem with 200 games for each pair of models |
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| http://127.0.0.1:8000/tournament/replay?name=leduc-holdem&agent0=leduc-holdem-rule-v1&agent1=leduc-holdem-cfr&index=3 | Obtain the replay data between rule model and CFR model. Obtain the data of the 3rd game |
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| http://127.0.0.1:8000/tournament/query\_game&elements\_every\_page=10&page\_index=0 | Get all the game data |
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| http://127.0.0.1:8000/tournament/query\_game?name=leduc-holdem&elements\_every\_page=10&page\_index=0 | Get all the game data of Leduc Holdem |
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| http://127.0.0.1:8000/tournament/query\_payoff | Get all the payoffs |
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| http://127.0.0.1:8000/tournament/query\_payoff?agent0=leduc-holdem-cfr&agent1=leduc-holdem-rule-v1 | Get all the payoffs between rule and CFR models |
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| http://127.0.0.1:8000/tournament/query\_agent\_payoff?name=leduc-holdem&elements\_every\_page=1&page\_index=1 | Get the payoffs of all the agents of leduc-holdem |
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| http://127.0.0.1:8000/tournament/list\_uploaded\_agents?game=leduc-holdem | List the uploaded agents of leduc-holdem |
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| http://127.0.0.1:8000/tournament/list\_baseline\_agents?game=leduc-holdem | List the baseline agents of leduc-holdem |
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| http://127.0.0.1:8000/tournament/download\_examples?name=example\_luduc\_nfsp\_model | Download the NFSP example model for Leduc Hold'em |
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| http://127.0.0.1:8000/tournament/query_game&elements_every_page=10&page_index=0 | Get all the game data |
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| http://127.0.0.1:8000/tournament/query_game?name=leduc-holdem&elements_every_page=10&page_index=0 | Get all the game data of Leduc Holdem |
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| http://127.0.0.1:8000/tournament/query_payoff | Get all the payoffs |
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| http://127.0.0.1:8000/tournament/query_payoff?agent0=leduc-holdem-cfr&agent1=leduc-holdem-rule-v1 | Get all the payoffs between rule and CFR models |
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| http://127.0.0.1:8000/tournament/query_agent_payoff?name=leduc-holdem&elements\_every\_page=1&page\_index=1 | Get the payoffs of all the agents of leduc-holdem |
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| http://127.0.0.1:8000/tournament/list_uploaded_agents?game=leduc-holdem | List the uploaded agents of leduc-holdem |
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| http://127.0.0.1:8000/tournament/list_baseline_agents?game=leduc-holdem | List the baseline agents of leduc-holdem |
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| http://127.0.0.1:8000/tournament/download_examples?name=example_luduc_nfsp_model | Download the NFSP example model for Leduc Hold'em |
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## Registered Models
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Some models have been pre-registered as baselines
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@ -64,7 +64,7 @@ curl -F 'model=@example_luduc_nfsp_model.zip' -F "name=leduc-nfsp" -F "game=ledu
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```
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Launch the tounament with:
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```
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curl 'http://127.0.0.1:8000/tournament/launch?eval_num=200&name=leduc-holdem'
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curl 'http://127.0.0.1:8000/tournament/launch?num_eval_games=200&name=leduc-holdem'
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```
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We list the uploaded agent with
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```
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@ -1,5 +1,10 @@
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rlcard
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Django
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tqdm
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tensorflow==1.14
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django-cors-headers
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torch==1.6.0
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flask==1.1
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flask-cors
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onnx
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onnxruntime
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@ -21,8 +21,8 @@ class DoudizhuRandomModel(Model):
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''' Load random model
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'''
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env = rlcard.make('doudizhu')
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self.agent = RandomAgent(action_num=env.action_num)
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self.player_num = env.player_num
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self.agent = RandomAgent(num_actions=env.num_actions)
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self.num_players = env.num_players
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@property
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def agents(self):
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@ -34,7 +34,7 @@ class DoudizhuRandomModel(Model):
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Note: Each agent should be just like RL agent with step and eval_step
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functioning well.
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'''
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return [self.agent for _ in range(self.player_num)]
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return [self.agent for _ in range(self.num_players)]
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@property
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def use_raw(self):
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@ -21,8 +21,8 @@ class LeducHoldemRandomModel(Model):
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''' Load random model
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'''
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env = rlcard.make('leduc-holdem')
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self.agent = RandomAgent(action_num=env.action_num)
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self.player_num = env.player_num
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self.agent = RandomAgent(num_actions=env.num_actions)
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self.num_players = env.num_players
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@property
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def agents(self):
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@ -34,7 +34,7 @@ class LeducHoldemRandomModel(Model):
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Note: Each agent should be just like RL agent with step and eval_step
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functioning well.
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'''
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return [self.agent for _ in range(self.player_num)]
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return [self.agent for _ in range(self.num_players)]
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@property
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def use_raw(self):
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@ -7,34 +7,34 @@ from .rlcard_wrap import rlcard
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class Tournament(object):
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def __init__(self, game, model_ids, evaluate_num=100):
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def __init__(self, game, model_ids, num_eval_games=100):
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""" Default for two player games
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For Dou Dizhu, the two peasants use the same model
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"""
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self.game = game
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self.model_ids = model_ids
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self.evaluate_num = evaluate_num
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self.num_eval_games = num_eval_games
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# Load the models
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self.models = [rlcard.models.load(model_id) for model_id in model_ids]
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def launch(self):
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""" Currently for two-player game only
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"""
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model_num = len(self.model_ids)
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num_models = len(self.model_ids)
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games_data = []
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payoffs_data = []
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for i in range(model_num):
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for j in range(model_num):
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for i in range(num_models):
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for j in range(num_models):
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if j == i:
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continue
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print(self.game, '-', self.model_ids[i], 'VS', self.model_ids[j])
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if self.game == 'doudizhu':
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agents = [self.models[i].agents[0], self.models[j].agents[1], self.models[j].agents[2]]
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names = [self.model_ids[i], self.model_ids[j], self.model_ids[j]]
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data, payoffs, wins = doudizhu_tournament(self.game, agents, names, self.evaluate_num)
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data, payoffs, wins = doudizhu_tournament(self.game, agents, names, self.num_eval_games)
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elif self.game == 'leduc-holdem':
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agents = [self.models[i].agents[0], self.models[j].agents[1]]
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data, payoffs, wins = leduc_holdem_tournament(self.game, agents, self.evaluate_num)
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data, payoffs, wins = leduc_holdem_tournament(self.game, agents, self.num_eval_games)
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mean_payoff = np.mean(payoffs)
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print('Average payoff:', mean_payoff)
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print()
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@ -59,16 +59,16 @@ class Tournament(object):
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payoffs_data.append(payoff_data)
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return games_data, payoffs_data
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def doudizhu_tournament(game, agents, names, num):
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def doudizhu_tournament(game, agents, names, num_eval_games):
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env = rlcard.make(game, config={'allow_raw_data': True})
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env.set_agents(agents)
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payoffs = []
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json_data = []
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wins = []
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for _ in tqdm(range(num)):
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for _ in tqdm(range(num_eval_games)):
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data = {}
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roles = ['landlord', 'peasant', 'peasant']
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data['playerInfo'] = [{'id': i, 'index': i, 'role': roles[i], 'agentInfo': {'name': names[i]}} for i in range(env.player_num)]
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data['playerInfo'] = [{'id': i, 'index': i, 'role': roles[i], 'agentInfo': {'name': names[i]}} for i in range(env.num_players)]
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state, player_id = env.reset()
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perfect = env.get_perfect_information()
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data['initHands'] = perfect['hand_cards_with_suit']
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@ -77,7 +77,7 @@ def doudizhu_tournament(game, agents, names, num):
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current_hand_cards[i] = current_hand_cards[i].split()
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data['moveHistory'] = []
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while not env.is_over():
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action, probs = env.agents[player_id].eval_step(state)
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action, info = env.agents[player_id].eval_step(state)
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history = {}
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history['playerIdx'] = player_id
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if env.agents[player_id].use_raw:
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@ -85,6 +85,7 @@ def doudizhu_tournament(game, agents, names, num):
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else:
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_action = env._decode_action(action)
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history['move'] = _calculate_doudizhu_move(_action, player_id, current_hand_cards)
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history['info'] = info
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data['moveHistory'].append(history)
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state, player_id = env.step(action, env.agents[player_id].use_raw)
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@ -115,15 +116,15 @@ def _calculate_doudizhu_move(action, player_id, current_hand_cards):
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break
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return ' '.join(cards_with_suit)
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def leduc_holdem_tournament(game, agents, num):
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def leduc_holdem_tournament(game, agents, num_eval_games):
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env = rlcard.make(game, config={'allow_raw_data': True})
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env.set_agents(agents)
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payoffs = []
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json_data = []
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wins = []
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for _ in tqdm(range(num)):
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for _ in tqdm(range(num_eval_games)):
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data = {}
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data['playerInfo'] = [{'id': i, 'index': i} for i in range(env.player_num)]
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data['playerInfo'] = [{'id': i, 'index': i} for i in range(env.num_players)]
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state, player_id = env.reset()
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perfect = env.get_perfect_information()
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data['initHands'] = perfect['hand_cards']
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@ -131,7 +132,7 @@ def leduc_holdem_tournament(game, agents, num):
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round_history = []
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round_id = 0
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while not env.is_over():
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action, probs = env.agents[player_id].eval_step(state)
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action, info = env.agents[player_id].eval_step(state)
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history = {}
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history['playerIdx'] = player_id
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if env.agents[player_id].use_raw:
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@ -139,16 +140,7 @@ def leduc_holdem_tournament(game, agents, num):
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else:
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history['move'] = env._decode_action(action)
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probabilities = []
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for i, a in enumerate(env.actions):
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if len(probs) == 0:
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p = -2
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elif a in state['raw_legal_actions']:
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p = probs[i]
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else:
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p = -1
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probabilities.append({'move':a, 'probability': p})
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history['probabilities'] = probabilities
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history['info'] = info
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round_history.append(history)
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state, player_id = env.step(action, env.agents[player_id].use_raw)
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perfect = env.get_perfect_information()
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@ -102,13 +102,13 @@ def query_agent_payoff(request):
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def launch(request):
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if request.method == 'GET':
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try:
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eval_num = int(request.GET['eval_num'])
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num_eval_games = int(request.GET['num_eval_games'])
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game = request.GET['name']
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except:
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return HttpResponse(json.dumps({'value': -1, 'info': 'parameters error'}))
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MODEL_IDS_ALL = _get_model_ids_all()
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games_data, payoffs_data = Tournament(game, MODEL_IDS_ALL[game], eval_num).launch()
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games_data, payoffs_data = Tournament(game, MODEL_IDS_ALL[game], num_eval_games).launch()
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Game.objects.filter(name=game).delete()
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Payoff.objects.filter(name=game).delete()
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for game_data in games_data:
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