怎么建立一个RNNPredictor(nn.Module)类

要建立一个RNNPredictor(nn.Module)类，需要使用PyTorch库，具体步骤如下：

1. 导入必要的库

import torch
import torch.nn as nn

2. 创建RNNPredictor类，继承自nn.Module

class RNNPredictor(nn.Module):
    def __init__(self, input_size, hidden_size, output_size):
        super(RNNPredictor, self).__init__()
        self.hidden_size = hidden_size
        self.rnn = nn.RNN(input_size, hidden_size)
        self.fc = nn.Linear(hidden_size, output_size)

3. 定义前向传播函数forward()

def forward(self, input):
    batch_size = input.size(0)
    hidden = self.init_hidden(batch_size)
    output, hidden = self.rnn(input, hidden)
    output = self.fc(output)
    return output, hidden

4. 定义init_hidden()函数，用于初始化隐藏层状态

def init_hidden(self, batch_size):
    hidden = torch.zeros(1, batch_size, self.hidden_size)
    return hidden

5. 最后，创建一个实例对象并使用它进行训练和预测

input_size = 10
hidden_size = 20
output_size = 5
model = RNNPredictor(input_size, hidden_size, output_size)
input = torch.randn(3, 1, 10)
output, hidden = model(input)

以上就是建立一个RNNPredictor(nn.Module)类的步骤。