AttributeError: 'EEGNet' object has no attribute 'classifier'

对不起，我之前的回答中有一个错误。在GNet模型中，确实没有定义名为'classifier'的属性。我在这里给你修正的代码：

class EEGNet(nn.Module):
    def __init__(self, num_classes):
        super(EEGNet, self).__init__()
        self.firstConv = nn.Sequential(
            nn.Conv2d(1, 16, kernel_size=(1, 51), stride=(1, 1), padding=(0, 25), bias=False),
            nn.BatchNorm2d(16, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True),
            nn.ELU(),
            nn.MaxPool2d(kernel_size=(1, 4), stride=(1, 4), padding=0),
            nn.Dropout(p=0.25)
        )
        self.depthwiseConv = nn.Sequential(
            nn.Conv2d(16, 32, kernel_size=(2, 1), stride=(1, 1), groups=16, bias=False),
            nn.BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True),
            nn.ELU(),
            nn.AvgPool2d(kernel_size=(1, 4), stride=(1, 4), padding=0),
            nn.Dropout(p=0.25)
        )
        self.separableConv = nn.Sequential(
            nn.Conv2d(32, 32, kernel_size=(1, 15), stride=(1, 1), padding=(0, 7), bias=False),
            nn.BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True),
            nn.ELU(),
            nn.AvgPool2d(kernel_size=(1, 8), stride=(1, 8), padding=0),
            nn.Dropout(p=0.25)
        )
        self.fc = nn.Linear(736, num_classes)
   
    def forward(self, x):
        x = self.firstConv(x)
        x = self.depthwiseConv(x)
        x = self.separableConv(x)
        x = x.view(x.size(0), -1)
        x = self.fc(x)
        return x

我将原来的'classifier'更名为'fc'，并将其定义为一个线性层。现在，你可以使用修复后的代码重新运行并实现EEGNet网络。如果还有其他问题，请随时向我提问。对之前的错误表示歉意！