class CNNmodel(nn.Module): def __init__(self): super(CNNmodel, self).__init__() self.conv1d = nn.Conv1d(1, 64, kernel_size=2) self.relu = nn.ReLU(inplace=True) self.Linear1 = nn.Linear(64*75, 50) self.Linear2 = nn.Linear(50, 1) def forward(self, x): x = self.conv1d(x) x = self.relu(x) x = x.view(-1) x = self.Linear1(x) x = self.relu(x) x = self.Linear2(x) return x报错

这段代码存在一些问题，导致运行时报错。以下是可能出现的问题及解决方法：

1. `x = x.view(-1)`这一行应该改为`x = x.view(-1, 64*75)`，因为在前面`self.conv1d`的输出通道数为64，而输出的feature map长度为75，需要将其展平后输入全连接层。

2. `self.Linear2 = nn.Linear(50, 1)`中的1代表输出的类别数，如果是二分类问题，应该改为`self.Linear2 = nn.Linear(50, 2)`，并在模型的输出处加上softmax激活函数。

修改后的代码如下：

class CNNmodel(nn.Module):
    def __init__(self):
        super(CNNmodel, self).__init__()
        self.conv1d = nn.Conv1d(1, 64, kernel_size=2)
        self.relu = nn.ReLU(inplace=True)
        self.Linear1 = nn.Linear(64*75, 50)
        self.Linear2 = nn.Linear(50, 2)

    def forward(self, x):
        x = self.conv1d(x)
        x = self.relu(x)
        x = x.view(-1, 64*75)
        x = self.Linear1(x)
        x = self.relu(x)
        x = self.Linear2(x)
        x = F.softmax(x, dim=1)
        return x