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lstm=nn.LSTM(input_size, hidden_size, num_layers)
x seq_len, batch, input_size
h0 num_layers× \times×num_directions, batch, hidden_size
c0 num_layers× \times×num_directions, batch, hidden_size
output seq_len, batch, num_directions× \times×hidden_size
hn num_layers× \times×num_directions, batch, hidden_size
cn num_layers× \times×num_directions, batch, hidden_size
举个例子：
对句子进行LSTM操作
假设有100个句子（sequence）,每个句子里有7个词，batch_size=64，embedding_size=300
此时，各个参数为：
input_size=embedding_size=300
batch=batch_size=64
seq_len=7
另外设置hidden_size=100, num_layers=1
import torch
import torch.nn as nn
lstm = nn.LSTM(300, 100, 1)
x = torch.randn(7, 64, 300)
h0 = torch.randn(1, 64, 100)
c0 = torch.randn(1, 64, 100)
output, (hn, cn)=lstm(x, (h0, c0))
>>
output.shape torch.Size([7, 64, 100])
hn.shape torch.Size([1, 64, 100])
cn.shape torch.Size([1, 64, 100])
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作者：huxuedan01
来源：CSDN
原文：https://blog.csdn.net/m0_37586991/article/details/88561746
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