前面介紹了使用pytorch構造cnn網路，這一節介紹點高階的東西lstm。
以及我之前的一篇中文翻譯部落格：
class
torch.nn.lstm
(*args, **kwargs)
class
rnn(nn.module):
def__init__
(self, input_size, hidden_size, num_layers, num_classes):
super(rnn, self).__init__()
self.hidden_size = hidden_size
self.num_layers = num_layers
self.lstm = nn.lstm(input_size, hidden_size, num_layers,
batch_first=true)
self.fc = nn.linear(hidden_size, num_classes) # 2 for bidirection
defforward
(self, x):
# forward propagate rnn
out, _ = self.lstm(x)
# decode hidden state of last time step
out = self.fc(out[:, -1, :])
return out
rnn = rnn(input_size, hidden_size, num_layers, num_classes)
rnn.cuda()
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