humancritic_tensorflow.py 文件源码

def _create_model(self,input_data,reuse=False):
        with self.graph.as_default():
            with tf.variable_scope("hp_model"):
                model = input_data
                # Programatically define Layers
                for i in range(self.LAYER_COUNT):
                    layer = slim.fully_connected(model,self.NEURON_SIZE,activation_fn=tf.nn.relu,scope="hp_model_"+str(i),
                        reuse=reuse,weights_initializer=self.initializer)
                    model = layer

                layer = slim.fully_connected(model,1,scope="output",\
                    reuse=reuse,weights_initializer=self.initializer)

                #'''
                model = layer 
                layer = tf.nn.batch_normalization(model,tf.constant(0.0,shape=[1]),\
                    tf.constant(1.0,shape=[1]),None,None,1e-5)
                #'''
                return layer