pytorch一维cnn代码

以下是一个简单的一维CNN的PyTorch代码示例：

import torch
import torch.nn as nn

class OneDCNN(nn.Module):
    def __init__(self, input_size, num_classes):
        super(OneDCNN, self).__init__()
        self.layer1 = nn.Sequential(
            nn.Conv1d(input_size, 16, kernel_size=5, stride=1, padding=2),
            nn.BatchNorm1d(16),
            nn.ReLU(),
            nn.MaxPool1d(kernel_size=2, stride=2))
        self.layer2 = nn.Sequential(
            nn.Conv1d(16, 32, kernel_size=5, stride=1, padding=2),
            nn.BatchNorm1d(32),
            nn.ReLU(),
            nn.MaxPool1d(kernel_size=2, stride=2))
        self.fc = nn.Linear(32*int(input_size/4), num_classes)
        
    def forward(self, x):
        out = self.layer1(x)
        out = self.layer2(out)
        out = out.reshape(out.size(0), -1)
        out = self.fc(out)
        return out