学习莫烦 tesorflow视频,然后敲代码,改了原来有的错误,现在是可以运行的版本了。加了很多注释。
# 参考https://morvanzhou.github.io/tutorials/machine-learning/tensorflow/5-09-RNN3/
修改的错误是:版本问题tf.train.SummaryWriter改为tf.summary.FilterWritwer;
tf.merge_all_summaries()改为tf.summary.merge_all();
错误:crossent = softmax_loss_function(labels=target, logits=logit)
TypeError: ms_error() got an unexpected keyword argument 'labels'
解决:def ms_error(self, labels, logits):
return tf.square(tf.subtract(labels,logits))
完整代码如下
# -*- coding: utf-8 -*-
"""Created on Fri May 25 17:19:53 2018
tensorboard
plt.plot
RNN
LSTM
"""
# google -> http://AOC:6006
#分类使用[(batch_size, output_size)*steps] 中最后一个step的值;
#分类使用或者描述为(batch_size, n_step, output_size)中(batch_size, -1, output_size)
#回归问题中,尽管可能输入和输出维度是1,
#但是可以time_steps=20,即把20个点当成个序列,这时候就要考虑每一步的output,合起来就是20个输出,即一个序列。
#import packages
import tensorflow as tf
import numpy as np
import matplotlib.pyplot as plt
#define hypeparameter
BATCH_START = 0
TIME_STEPS = 20
BATCH_SIZE = 50
INPUT_SIZE = 1
OUTPUT_SIZE = 1
CELL_SIZE = 10
LR = 0.006
BATCH_START_TEST = 0
#fake data
def get_batch():
# class LSTMRNN
class LSTMRNN(object):
if __name__ == '__main__':