def __init__()

in models/networks/pretrained_networks.py [0:0]

• 24 lines of code
• 8 McCabe index (conditional complexity)

    def __init__(self, requires_grad=False, pretrained=True):
        super(alexnet, self).__init__()
        alexnet_pretrained_features = models.alexnet(
            pretrained=pretrained
        ).features
        self.slice1 = torch.nn.Sequential()
        self.slice2 = torch.nn.Sequential()
        self.slice3 = torch.nn.Sequential()
        self.slice4 = torch.nn.Sequential()
        self.slice5 = torch.nn.Sequential()
        self.N_slices = 5
        for x in range(2):
            self.slice1.add_module(str(x), alexnet_pretrained_features[x])
        for x in range(2, 5):
            self.slice2.add_module(str(x), alexnet_pretrained_features[x])
        for x in range(5, 8):
            self.slice3.add_module(str(x), alexnet_pretrained_features[x])
        for x in range(8, 10):
            self.slice4.add_module(str(x), alexnet_pretrained_features[x])
        for x in range(10, 12):
            self.slice5.add_module(str(x), alexnet_pretrained_features[x])
        if not requires_grad:
            for param in self.parameters():
                param.requires_grad = False