model.py 文件源码

def _build(self,input_shape):
        num_actions = 128
        N = input_shape[0] - num_actions
        x = Input(shape=input_shape)
        pre    = wrap(x,tf.slice(x, [0,0], [-1,N]),name="pre")
        action = wrap(x,tf.slice(x, [0,N], [-1,num_actions]),name="action")

        ys = []
        for i in range(num_actions):
            _x = Input(shape=(N,))
            _y = Sequential([
                flatten,
                *[Sequential([BN(),
                              Dense(self.parameters['layer'],activation=self.parameters['activation']),
                              Dropout(self.parameters['dropout']),])
              for i in range(self.parameters['num_layers']) ],
                Dense(1,activation="sigmoid")
            ])(_x)
            _m = Model(_x,_y,name="action_"+str(i))
            ys.append(_m(pre))

        ys = Concatenate()(ys)
        y  = Dot(-1)([ys,action])

        self.loss = bce
        self.net = Model(x, y)
        self.callbacks.append(GradientEarlyStopping(verbose=1,epoch=50,min_grad=self.parameters['min_grad']))