def __init__(self, model, encoder):
Agent.__init__(self)
self._model = model
self._encoder = encoder
self._collector = None
self._temperature = 0.0
board = goboard.Board(19, 19)
self.board_ext = goboard.Board_Ext(board)
def __init__(self,
policy_agent,
fast_policy_agent,
value_agent,
lambda_value=0.5,
num_simulations=1000,
depth=50,
rollout_limit=100):
Agent.__init__(self)
self.policy = policy_agent
self.rollout_policy = fast_policy_agent
self.value = value_agent
self.lambda_value = lambda_value
self.num_simulations = num_simulations
self.depth = depth
self.rollout_limit = rollout_limit
self.root = AlphaGoNode()
def __init__(self, model, encoder):
Agent.__init__(self)
self.model = model
self.encoder = encoder
def __init__(self, model, encoder):
Agent.__init__(self)
self._model = model
self._encoder = encoder
self._collector = None
def __init__(self):
Agent.__init__(self)
self.dim = None
self.point_cache = []
def __init__(self, agent, strategy=None):
Agent.__init__(self)
self.agent = agent
self.strategy = strategy if strategy is not None \
else TerminationStrategy()
def __init__(self, max_depth, eval_fn):
Agent.__init__(self)
self.max_depth = max_depth
self.eval_fn = eval_fn
def __init__(self, num_rounds, temperature):
Agent.__init__(self)
self.num_rounds = num_rounds
self.temperature = temperature
def __init__(self, model, encoder):
Agent.__init__(self)
self._model = model # A Keras Sequential model instance
self._encoder = encoder # Implements the Encoder interface
self._collector = None
self._temperature = 0.0
def __init__(self):
Agent.__init__(self)
self.model = nn.DataParallel(Model()).to(device)
checkpoint = torch.load("go_model.pt")
self.model.module.load_state_dict(checkpoint["model_state_dict"])
def __init__(self, model, encoder, print_probs = False):
Agent.__init__(self)
self.model = model
self.encoder = encoder
self.print_probs = print_probs
