siamese_lstm_network1.py 文件源码

def buildSiameseNN(self, left_nn, right_nn):
        #construct fully connected layer-extend even more networks
        print(self.nfeatures)
        weights = {
          'out': tf.Variable(tf.random_normal([2*self.nfeatures, self.n_classes],dtype=tf.float64),dtype = tf.float64)
        }
        biases = {
          'out': tf.Variable(tf.random_normal([self.n_classes],dtype=tf.float64),dtype = tf.float64)
        }

        joint_layer = tf.concat([left_nn,right_nn],1)
        print("joint layer-->"+str(joint_layer))
        batch_normalized = self.insertBatchNNLayer(joint_layer,[0],[2*self.nfeatures])        
        batch_normalized = tf.matmul(batch_normalized, weights['out']) + biases['out']
        result = tf.nn.softmax(batch_normalized)
        #add softmax layer
        return result