请给我修改过后的完整代码

好的，下面是修改后的完整代码：

import torch
import torch.nn as nn

class RNNModel(nn.Module):
    def __init__(self, input_size, hidden_size, num_layers, num_classes):
        super(RNNModel, self).__init__()
        self.hidden_size = hidden_size
        self.num_layers = num_layers
        self.rnn = nn.RNN(input_size, hidden_size, num_layers, batch_first=True)
        self.fc = nn.Linear(hidden_size, num_classes)

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


# 示例数据
batch_size = 32
seq_len = 10
input_size = 5
hidden_size = 20
num_layers = 2
num_classes = 2

x = torch.randn(batch_size, seq_len, input_size)
model = RNNModel(input_size, hidden_size, num_layers, num_classes)
y_pred = model(x)

print("模型输出的形状为：", y_pred.shape)

这个例子中，我使用了随机生成的输入数据 `x`，并使用 `RNNModel` 类定义了一个 RNN 模型，然后将 `x` 传入模型中计算得到输出 `y_pred`。最后打印出 `y_pred` 的形状。