def get_pretrained_model()

in captum/insights/attr_vis/example.py [0:0]

• 29 lines of code
• 1 McCabe index (conditional complexity)

def get_pretrained_model():
    class Net(nn.Module):
        def __init__(self) -> None:
            super(Net, self).__init__()
            self.conv1 = nn.Conv2d(3, 6, 5)
            self.pool1 = nn.MaxPool2d(2, 2)
            self.pool2 = nn.MaxPool2d(2, 2)
            self.conv2 = nn.Conv2d(6, 16, 5)
            self.fc1 = nn.Linear(16 * 5 * 5, 120)
            self.fc2 = nn.Linear(120, 84)
            self.fc3 = nn.Linear(84, 10)
            self.relu1 = nn.ReLU()
            self.relu2 = nn.ReLU()
            self.relu3 = nn.ReLU()
            self.relu4 = nn.ReLU()

        def forward(self, x):
            x = self.pool1(self.relu1(self.conv1(x)))
            x = self.pool2(self.relu2(self.conv2(x)))
            x = x.view(-1, 16 * 5 * 5)
            x = self.relu3(self.fc1(x))
            x = self.relu4(self.fc2(x))
            x = self.fc3(x)
            return x

    net = Net()
    pt_path = os.path.abspath(
        os.path.join(os.path.dirname(__file__), "models/cifar_torchvision.pt")
    )
    net.load_state_dict(torch.load(pt_path))
    return net