def __init_

def init()

in src/controlnet_aux/pidi/model.py [0:0]
68 lines of code
12 McCabe index (conditional complexity)

    def __init__(self, inplane, pdcs, dil=None, sa=False, convert=False):
        super(PiDiNet, self).__init__()
        self.sa = sa
        if dil is not None:
            assert isinstance(dil, int), 'dil should be an int'
        self.dil = dil

        self.fuseplanes = []

        self.inplane = inplane
        if convert:
            if pdcs[0] == 'rd':
                init_kernel_size = 5
                init_padding = 2
            else:
                init_kernel_size = 3
                init_padding = 1
            self.init_block = nn.Conv2d(3, self.inplane,
                    kernel_size=init_kernel_size, padding=init_padding, bias=False)
            block_class = PDCBlock_converted
        else:
            self.init_block = Conv2d(pdcs[0], 3, self.inplane, kernel_size=3, padding=1)
            block_class = PDCBlock

        self.block1_1 = block_class(pdcs[1], self.inplane, self.inplane)
        self.block1_2 = block_class(pdcs[2], self.inplane, self.inplane)
        self.block1_3 = block_class(pdcs[3], self.inplane, self.inplane)
        self.fuseplanes.append(self.inplane) # C

        inplane = self.inplane
        self.inplane = self.inplane * 2
        self.block2_1 = block_class(pdcs[4], inplane, self.inplane, stride=2)
        self.block2_2 = block_class(pdcs[5], self.inplane, self.inplane)
        self.block2_3 = block_class(pdcs[6], self.inplane, self.inplane)
        self.block2_4 = block_class(pdcs[7], self.inplane, self.inplane)
        self.fuseplanes.append(self.inplane) # 2C

        inplane = self.inplane
        self.inplane = self.inplane * 2
        self.block3_1 = block_class(pdcs[8], inplane, self.inplane, stride=2)
        self.block3_2 = block_class(pdcs[9], self.inplane, self.inplane)
        self.block3_3 = block_class(pdcs[10], self.inplane, self.inplane)
        self.block3_4 = block_class(pdcs[11], self.inplane, self.inplane)
        self.fuseplanes.append(self.inplane) # 4C

        self.block4_1 = block_class(pdcs[12], self.inplane, self.inplane, stride=2)
        self.block4_2 = block_class(pdcs[13], self.inplane, self.inplane)
        self.block4_3 = block_class(pdcs[14], self.inplane, self.inplane)
        self.block4_4 = block_class(pdcs[15], self.inplane, self.inplane)
        self.fuseplanes.append(self.inplane) # 4C

        self.conv_reduces = nn.ModuleList()
        if self.sa and self.dil is not None:
            self.attentions = nn.ModuleList()
            self.dilations = nn.ModuleList()
            for i in range(4):
                self.dilations.append(CDCM(self.fuseplanes[i], self.dil))
                self.attentions.append(CSAM(self.dil))
                self.conv_reduces.append(MapReduce(self.dil))
        elif self.sa:
            self.attentions = nn.ModuleList()
            for i in range(4):
                self.attentions.append(CSAM(self.fuseplanes[i]))
                self.conv_reduces.append(MapReduce(self.fuseplanes[i]))
        elif self.dil is not None:
            self.dilations = nn.ModuleList()
            for i in range(4):
                self.dilations.append(CDCM(self.fuseplanes[i], self.dil))
                self.conv_reduces.append(MapReduce(self.dil))
        else:
            for i in range(4):
                self.conv_reduces.append(MapReduce(self.fuseplanes[i]))

        self.classifier = nn.Conv2d(4, 1, kernel_size=1) # has bias
        nn.init.constant_(self.classifier.weight, 0.25)
        nn.init.constant_(self.classifier.bias, 0)
def __init__()

def init()
