Python QAgent.evaluate_mine示例

def run_model(params):

    # https://stackoverflow.com/questions/11526975/set-random-seed-programwide-in-python
    # https://stackoverflow.com/questions/30517513/global-seed-for-multiple-numpy-imports
    random.seed(params.seed)
    np.random.seed(params.seed)
    # Must be called before Session
    # https://stackoverflow.com/questions/38469632/tensorflow-non-repeatable-results/40247201#40247201
    tf.set_random_seed(params.seed)

    qagent = QAgent(params)
    if params.is_train:
        qagent.fit()
    elif params.eval_mode == 0:
        qagent.evaluate_mine()
    elif params.eval_mode == 1:
        qagent.test_mine()
    elif params.eval_mode == 2:
        for mines in range(1, 13):
            params.mines_min = mines
            params.mines_max = mines
            print("Mines =", mines)
            qagent.test_mine()
            tf.reset_default_graph()
            qagent = QAgent(params)

示例#2

显示文件

文件： train.py 项目： ll550/minesweeper_solver

def train(params):

    # https://stackoverflow.com/questions/11526975/set-random-seed-programwide-in-python
    # https://stackoverflow.com/questions/30517513/global-seed-for-multiple-numpy-imports
    random.seed(params.seed)
    np.random.seed(params.seed)
    # Must be called before Session
    # https://stackoverflow.com/questions/38469632/tensorflow-non-repeatable-results/40247201#40247201
    tf.set_random_seed(params.seed)

    qagent = QAgent(params)
    if params.is_train:
        qagent.fit()
    else:
        qagent.evaluate_mine()