AttributeError: 'ConvNet' object has no attribute 'conv1'

vision
1

I was trying to learn HiddenLayer visualization, but there was an error in the title when the code was running properly, and I found that my code seemed to be fine.


class ConvNet(nn.Module):
    def __init__(self):
        super(ConvNet,self).__init__()
        
        self.convl=nn.Sequential(
            nn.Conv2d(
                in_channels=1,
                out_channels=16,
                kernel_size=3,
                stride=1,
                padding=1,
                ),
            nn.ReLU(),
            nn.AvgPool2d(
                kernel_size=2,
                stride=2,
                ),
            )
        
        self.conv2=nn.Sequential(
            nn.Conv2d(16,32,3,1,1),
            nn.ReLU(),
            nn.MaxPool2d(2,2)
        )
        
        self.fc=nn.Sequential(
            nn.Linear(
                in_features=32*7*7,
                out_features=128,
            ),
            nn.ReLU(),
            nn.Linear(128,64),
            nn.ReLU()
        )
        self.out=nn.Linear(64,10)
    def forward(self,x):
        x=self.conv1(x)
        x=self.conv2(x)
        x=x.view(x.size(0),-1)
        x=self.fc(x)
        output=self.out(x)
        return output
Myconvnet=ConvNet()

import hiddenlayer as hl

hl_graph=hl.build_graph(Myconvnet,torch.zeros([1,1,28,28]))
hl_graph.theme=hl.graph.THEMES["blue"].copy()
hl_graph.save("./deep_learning_data/MyConvnet_h1.png",format="png")

then

~\anaconda3\lib\site-packages\torch\nn\modules\module.py in __getattr__(self, name)
   1206                 return modules[name]
   1207         raise AttributeError("'{}' object has no attribute '{}'".format(
-> 1208             type(self).__name__, name))
   1209 
   1210     def __setattr__(self, name: str, value: Union[Tensor, 'Module']) -> None:

AttributeError: 'ConvNet' object has no attribute 'conv1'
2

Hey, there!
In the __init__ class, you have called using self.convl instead of self.conv1. Seems like a minor typo. Thanks!