def __init__()

in models/resnet.py [0:0]


    def __init__(self, in_planes, mid_planes, out_planes, norm, stride=1):
        super(BasicBlock, self).__init__()
        self.conv1 = nn.Conv2d(in_planes, mid_planes, kernel_size=3, stride=stride, padding=1, bias=False)
        self.bn1 = norm(mid_planes)
        self.conv2 = nn.Conv2d(mid_planes, out_planes, kernel_size=3, stride=1, padding=1, bias=False)
        self.bn2 = norm(out_planes)

        self.shortcut = nn.Sequential()
        if stride != 1 or in_planes != out_planes:
            self.shortcut = nn.Sequential(
                nn.Conv2d(in_planes, out_planes, kernel_size=1, stride=stride, bias=False),
                norm(out_planes)
            )