def create_actor_network(self, state_size,action_dim):
print("Now we build the model")
S = Input(shape=[state_size])
h0 = Dense(HIDDEN1_UNITS, activation='relu')(S)
h1 = Dense(HIDDEN2_UNITS, activation='relu')(h0)
Steering = Dense(1,activation='tanh',init=lambda shape, name: normal(shape, scale=1e-4, name=name))(h1)
Acceleration = Dense(1,activation='sigmoid',init=lambda shape, name: normal(shape, scale=1e-4, name=name))(h1)
Brake = Dense(1,activation='sigmoid',init=lambda shape, name: normal(shape, scale=1e-4, name=name))(h1)
V = merge([Steering,Acceleration,Brake],mode='concat')
model = Model(input=S,output=V)
return model, model.trainable_weights, S
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