pytorch——LSTM

nn.LSTM

在LSTM中，c和h的size是一样的

import  torch
from  torch import nn
import numpy as np

lstm = nn.LSTM(input_size=100, hidden_size=20, num_layers=4)
print(lstm)
x = torch.randn(10,3,100) #3个句子，每个句子10个单词，每个单词encoding成100维的vector
out,(h,c) = lstm(x)
print(out.shape,h.shape,c.shape)

 

nn.LSTMCell

第二种方式，灵活性更大的cell，人为来决定每一次喂数据

单层

import  torch
from  torch import nn
import numpy as np

print('one layer lstm')
cell=nn.LSTMCell(input_size=100, hidden_size=20)
h=torch.zeros(3,20)
c=torch.zeros(3,20)
x = torch.randn(10,3,100)
for xt in x: 
	h,c = cell(xt, [h,c])

print('h.shape: ',h.shape)
print('c.shape: ',c.shape)

双层

import  torch
from  torch import nn
import numpy as np

x = torch.randn(10,3,100)
print('two layer lstm')
cell1=nn.LSTMCell(input_size=100, hidden_size=30)
cell2=nn.LSTMCell(input_size=30, hidden_size=20)
h1=torch. zeros(3,30)
c1=torch. zeros(3,30)
h2=torch. zeros(3,20)
c2=torch. zeros(3,20)
for xt in x: 
	h1,c1=cell1(xt,[h1, c1])
	h2,c2=cell2(h1,[h2, c2])
print('h.shape: ',h2.shape)
print('c.shape: ',c2.shape)