train_deep_cnn.py 文件源码

def __init__(self, natural=False):
        """
        Initialize environment
        """

        # I use array of len 1 to store constants (otherwise there were some errors)
        self.action_space = spaces.Tuple((
            spaces.Box(-5.0, 0.0, 1),  # learning rate
            spaces.Box(-7.0, -2.0, 1),  # decay
            spaces.Box(-5.0, 0.0, 1),  # momentum
            spaces.Box(2, 8, 1),  # batch size
            spaces.Box(-6.0, 1.0, 1),  # l1 reg
            spaces.Box(-6.0, 1.0, 1),  # l2 reg
            spaces.Box(0.0, 1.0, (5, 2)),  # convolutional layer parameters
            spaces.Box(0.0, 1.0, (2, 2)),  # fully connected layer parameters
        ))

        # observation features, in order: num of instances, num of labels,
        # validation accuracy after training with given parameters
        self.observation_space = spaces.Box(-1e5, 1e5, 2)  # validation accuracy

        # Start the first game
        self._reset()