apn.py 文件源码

def buildEmbedding(self):
        weights = self.embedding_params.get('weights')
        #assert weights
        trainable = self.params.get('embedding_trainable', False)
        if trainable:
            logging.info('Embedding Weights is Trainable!')
        else:
            logging.info('Embedding Weights is Not Trainable!')
        with tf.name_scope('embedding'):
            W = tf.Variable(
                weights,
                name = 'embedding',
                trainable = trainable,
                dtype = tf.float32
            )
            self.tensors['q_embedding'] = tf.nn.embedding_lookup(W, self.tensors['q_input'])
            self.tensors['a_embedding'] = tf.nn.embedding_lookup(W, self.tensors['a_input'])