def _fast_match(nnet1: NNet, nnet2: NNet) -> int:
game = Game()
while True:
if game.player == 1:
policy = nnet1.prediction(state=game.game_state, player=game.player)[0]
else:
policy = nnet2.prediction(state=game.game_state, player=game.player)[0]
game.make_move(random.choices(range(len(policy)), weights=policy)[0])
if game.has_won(game.game_state, player=game.player * -1):
return game.player * -1
elif game.is_draw(game.game_state):
return 0
def fetch_prediction(self, nnet: NNet, x_noise: float = 0.) -> None:
self.policy, self.nnet_value = nnet.prediction(self.state, player=1)
if not x_noise:
return
d = scipy.stats.dirichlet.rvs([1.0 for _ in range(c.COLUMNS)])[0]
self.policy = (1 - x_noise) * self.policy + 1 * d
