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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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