def _create_neural_mcts_player(
game: polygames.Game,
mcts_option: mcts.MctsOption,
num_actor: int,
actor_channel: tube.DataChannel,
model_manager: Optional[polygames.ModelManager] = None,
rnn_state_shape: List[int] = [],
rnn_seqlen: int = 0,
logit_value: bool = False,
) -> mcts.MctsPlayer:
player = mcts.MctsPlayer(mcts_option)
for _ in range(num_actor):
num_actor += 1
actor = polygames.Actor(
actor_channel,
game.get_feat_size(),
game.get_action_size(),
rnn_state_shape,
rnn_seqlen,
logit_value,
True,
True,
model_manager,
)
player.set_actor(actor)
return player
def _create_pure_mcts_player(game: polygames.Game,
mcts_option: mcts.MctsOption,
num_actor: int) -> mcts.MctsPlayer:
"""a player that uses only mcts + random rollout, no neural net"""
player = mcts.MctsPlayer(mcts_option)
for _ in range(num_actor):
actor = polygames.Actor(None, game.get_feat_size(),
game.get_action_size(), False, False, None)
player.add_actor(actor)
return player
def _create_neural_mcts_player(
game: polygames.Game,
mcts_option: mcts.MctsOption,
num_actor: int,
actor_channel: tube.DataChannel,
assembler: Optional[tube.ChannelAssembler] = None,
) -> mcts.MctsPlayer:
player = mcts.MctsPlayer(mcts_option)
for _ in range(num_actor):
num_actor += 1
actor = polygames.Actor(
actor_channel,
game.get_feat_size(),
game.get_action_size(),
True,
True,
assembler,
)
player.add_actor(actor)
return player