cfg = {
‘VGG11’: [64, ‘M’, 128, ‘M’, 256, 256, ‘M’, 512, 512, ‘M’, 512, 512, ‘M’],
‘VGG13’: [64, 64, ‘M’, 128, 128, ‘M’, 256, 256, ‘M’, 512, 512, ‘M’, 512, 512, ‘M’],
‘VGG16’: [64, 64, ‘M’, 128, 128, ‘M’, 256, 256, 256, ‘M’, 512, 512, 512, ‘M’, 512, 512, 512, ‘M’],
‘VGG19’: [64, 64, ‘M’, 128, 128, ‘M’, 256, 256, 256, 256, ‘M’, 512, 512, 512, 512, ‘M’, 512, 512, 512, 512, ‘M’],
}
class VGG(nn.Module):
def init(self, vgg_name):
super(VGG, self).init()
self.features = self._make_layers(cfg[vgg_name])
self.classifier = nn.Linear(512, 10)
self._initialize_weight()
def forward(self, x):
    out = self.features(x)
    out = out.view(out.size(0), -1)
    out = self.classifier(out)
    return out

def _make_layers(self, cfg):
    layers = []
    in_channels = 3
    for x in cfg:
        if x == 'M':
            layers += [nn.MaxPool2d(kernel_size=2, stride=2)]
        else:
            layers += [nn.Conv2d(in_channels, x, kernel_size=3, padding=1),
                       nn.BatchNorm2d(x),
                       nn.ReLU(inplace=True)]
            in_channels = x
    layers += [nn.AvgPool2d(kernel_size=1, stride=1)]
    return nn.Sequential(*layers)

def _initialize_weight(self):
    for m in self.modules():
        if isinstance(m, nn.Conv2d):
            # xavier is used in VGG's paper
            nn.init.xavier_normal_(m.weight.data)
            if m.bias is not None:
                m.bias.data.zero_()
        elif isinstance(m, nn.BatchNorm2d):
            m.weight.data.fill_(1)
            m.bias.data.zero_()
        elif isinstance(m, nn.Linear):
            m.weight.data.normal_(0, 0.01)
            m.bias.data.zero_()

net = VGG()
net.cuda()
this my code and I got error as:
TypeError                                 Traceback (most recent call last)
 in 
----> 1 net = VGG()
2 net.cuda()
TypeError: init() missing 1 required positional argument: ‘vgg_name’
can anyone help me?