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在PTB数据集上使用循环神经网络实现语言建模

运行环境：Windows 10 TensorFlow-gpu 1.11

搭建一个两层深的循环神经网络，每一层有200个LSTM结构，两层神经网络间设置Dropout。

总共训练13个Epoch，权重初始值为0.1，学习速率初始值为1.0，4个Epoch后开始对学习率进行调整，学习衰减率为0.5，batch_size设置为20，num_steps设置为20。

13个Epoch后，在测试集上的perplexity为115.368。

运行方法：首先打开LSTM_RNN.py文件，把第169行的PTB路径设置为自己PTB文件的路径，然后运行python LSTM_RNN.py。

运行过程截图

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