使用python3.7 torch 写一个LSTM多对一模型

好的，下面是使用Python 3.7 和 PyTorch 实现一个LSTM多对一模型的代码：

import torch
import torch.nn as nn

class LSTM(nn.Module):
    def __init__(self, input_size, hidden_size, num_layers, output_size):
        super(LSTM, 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, output_size)

    def forward(self, x):
        h0 = torch.zeros(self.num_layers, x.size(0), self.hidden_size)
        c0 = torch.zeros(self.num_layers, x.size(0), self.hidden_size)
        out, _ = self.lstm(x, (h0, c0))
        out = self.fc(out[:, -1, :])
        return out

input_size = 1
hidden_size = 32
num_layers = 1
output_size = 1

model = LSTM(input_size, hidden_size, num_layers, output_size)

在上面的代码中，我们定义了一个`LSTM`类，继承了`nn.Module`，然后在其中实现了LSTM模型的前向传播过程。