def __init_

def init()

in lib/model/HGFilters.py [0:0]
41 lines of code
11 McCabe index (conditional complexity)

    def __init__(self, stack, depth, in_ch, last_ch, norm='batch', down_type='conv64', use_sigmoid=True):
        super(HGFilter, self).__init__()
        self.n_stack = stack
        self.use_sigmoid = use_sigmoid
        self.depth = depth
        self.last_ch = last_ch
        self.norm = norm
        self.down_type = down_type

        self.conv1 = nn.Conv2d(in_ch, 64, kernel_size=7, stride=2, padding=3)

        last_ch = self.last_ch

        if self.norm == 'batch':
            self.bn1 = nn.BatchNorm2d(64)
        elif self.norm == 'group':
            self.bn1 = nn.GroupNorm(32, 64)

        if self.down_type == 'conv64':
            self.conv2 = ConvBlock(64, 64, self.norm)
            self.down_conv2 = nn.Conv2d(64, 128, kernel_size=3, stride=2, padding=1)
        elif self.down_type == 'conv128':
            self.conv2 = ConvBlock(128, 128, self.norm)
            self.down_conv2 = nn.Conv2d(128, 128, kernel_size=3, stride=2, padding=1)
        elif self.down_type == 'ave_pool' or self.down_type == 'no_down':
            self.conv2 = ConvBlock(64, 128, self.norm)
        
        self.conv3 = ConvBlock(128, 128, self.norm)
        self.conv4 = ConvBlock(128, 256, self.norm)
        
        # start stacking
        for stack in range(self.n_stack):
            self.add_module('m' + str(stack), HourGlass(self.depth, 256, self.norm))

            self.add_module('top_m_' + str(stack), ConvBlock(256, 256, self.norm))
            self.add_module('conv_last' + str(stack),
                            nn.Conv2d(256, 256, kernel_size=1, stride=1, padding=0))
            if self.norm == 'batch':
                self.add_module('bn_end' + str(stack), nn.BatchNorm2d(256))
            elif self.norm == 'group':
                self.add_module('bn_end' + str(stack), nn.GroupNorm(32, 256))
            
            self.add_module('l' + str(stack),
                            nn.Conv2d(256, last_ch, 
                            kernel_size=1, stride=1, padding=0))
            
            if stack < self.n_stack - 1:
                self.add_module(
                    'bl' + str(stack), nn.Conv2d(256, 256, kernel_size=1, stride=1, padding=0))
                self.add_module(
                    'al' + str(stack), nn.Conv2d(last_ch, 256, kernel_size=1, stride=1, padding=0))
def __init__()

def init()
