tf.contrib.legacy_seq2seq.basic_rnn_seq2seq 函数 example 最简单实现
函数文档：https://www.tensorflow.org/api_docs/python/tf/contrib/legacy_seq2seq/basic_rnn_seq2seq
import tensorflow as tf import numpy as np steps=10 batch_size=10 input_size=10 encoder_inputs = tf.placeholder("float", [None, steps, input_size]) decoder_inputs = tf.placeholder("float", [None, steps, input_size]) en_input=np.zeros(shape=[steps,batch_size,input_size]) de_input=np.zeros(shape=[steps,batch_size,input_size]) cell=tf.nn.rnn_cell.BasicLSTMCell(10) def get_result(encoder_inputs,decoder_inputs,cell): encoder_inputs=tf.unstack(encoder_inputs,axis=1) decoder_inputs=tf.unstack(decoder_inputs,axis=1) result=tf.contrib.legacy_seq2seq.basic_rnn_seq2seq( encoder_inputs, decoder_inputs, cell, dtype=tf.float32, scope=None ) return result result=get_result(encoder_inputs,decoder_inputs,cell) init=tf.global_variables_initializer() with tf.Session() as sess: sess.run(init) result_value=sess.run(result,feed_dict={encoder_inputs:en_input,decoder_inputs:de_input}) print(result_value)http://www.tensorflownews.com/
