bidirectional.py 文件源码

def _load_data_graph(self):
        """
        Loads the data graph consisting of the encoder and decoder input placeholders, Label (Target tip summary)
        placeholders and the weights of the hidden layer of the Seq2Seq model.

        :return: None
        """
        # input
        with tf.variable_scope("train_test", reuse=True):
            # review input - Both original and reversed
            self.enc_inp_fwd = [tf.placeholder(tf.int32, shape=(None,), name="input%i" % t)
                                for t in range(self.seq_length)]
            self.enc_inp_bwd = [tf.placeholder(tf.int32, shape=(None,), name="input%i" % t)
                                for t in range(self.seq_length)]
            # desired output
            self.labels = [tf.placeholder(tf.int32, shape=(None,), name="labels%i" % t)
                           for t in range(self.seq_length)]
            # weight of the hidden layer
            self.weights = [tf.ones_like(labels_t, dtype=tf.float32)
                            for labels_t in self.labels]

            # Decoder input: prepend some "GO" token and drop the final
            # token of the encoder input
            self.dec_inp = ([tf.zeros_like(self.labels[0], dtype=np.int32, name="GO")] + self.labels[:-1])