ActorNetwork.py 文件源码

def create_actor_network(self, state_size,action_dim):
        print("Now we build the model")

        # Batch norm version
        S = Input(shape=[state_size])
        s1 = BatchNormalization()(S)
        s1 = Dense(HIDDEN1_UNITS)(s1)
        s1 = BatchNormalization()(s1)
        s1 = Activation('relu')(s1)
        s1 = Dense(HIDDEN2_UNITS)(s1)
        s1 = BatchNormalization()(s1)
        h1 = Activation('relu')(s1)

        Steering = Dense(1,activation='tanh')(h1)  
        Acceleration = Dense(1,activation='sigmoid')(h1)   
        Brake = Dense(1,activation='sigmoid')(h1)
        # V = merge([Steering,Acceleration,Brake],mode='concat')
        V = layers.concatenate([Steering,Acceleration,Brake])          
        model = Model(inputs=S,outputs=V)
        return model, model.trainable_weights, S