def __init__()

in evaluations/inception_v3.py [0:0]

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

    def __init__(self):
        super().__init__()
        self.layers = torch.nn.Sequential(
            collections.OrderedDict(
                [
                    ("conv", Conv2dLayer(3, 32, kh=3, kw=3, stride=2)),
                    ("conv_1", Conv2dLayer(32, 32, kh=3, kw=3)),
                    ("conv_2", Conv2dLayer(32, 64, kh=3, kw=3, padding=1)),
                    ("pool0", torch.nn.MaxPool2d(kernel_size=3, stride=2)),
                    ("conv_3", Conv2dLayer(64, 80, kh=1, kw=1)),
                    ("conv_4", Conv2dLayer(80, 192, kh=3, kw=3)),
                    ("pool1", torch.nn.MaxPool2d(kernel_size=3, stride=2)),
                    ("mixed", InceptionA(192, tmp_channels=32)),
                    ("mixed_1", InceptionA(256, tmp_channels=64)),
                    ("mixed_2", InceptionA(288, tmp_channels=64)),
                    ("mixed_3", InceptionB(288)),
                    ("mixed_4", InceptionC(768, tmp_channels=128)),
                    ("mixed_5", InceptionC(768, tmp_channels=160)),
                    ("mixed_6", InceptionC(768, tmp_channels=160)),
                    ("mixed_7", InceptionC(768, tmp_channels=192)),
                    ("mixed_8", InceptionD(768)),
                    ("mixed_9", InceptionE(1280, use_avg_pool=True)),
                    ("mixed_10", InceptionE(2048, use_avg_pool=False)),
                    ("pool2", torch.nn.AvgPool2d(kernel_size=8)),
                ]
            )
        )
        self.output = torch.nn.Linear(2048, 1008)