《动手学深度学习》-58深层循环神经网络实现

在此基础上加多几层隐藏层

import torch
from torch import nn
from torch.nn import functional as F
import test_55RNNesay_realize
import d2l
import test_53LanguageModel
import test_55RNNdifficult_realize
batch_size,num_steps=32,35
train_iter,vocab=test_53LanguageModel.load_data_time_machine(batch_size,num_steps)
vocab_size,num_hiddens,num_layers=len(vocab),512,2
num_inputs=vocab_size
lr,num_epochs=0.1,500
device=d2l.try_gpu()
lstm=nn.LSTM(num_inputs,num_hiddens,num_layers)
model=test_55RNNesay_realize.RNNModel(lstm,len(vocab))
model=model.to(d2l.try_gpu())
test_55RNNdifficult_realize.train_ch8(model,train_iter,vocab,lr,num_epochs,device)