(self, in_channels, out_channels,
                 kernel_size, stride, padding=0,
                 dilation=1, deformable_groups=2,
                 groups=None, bias=True)
groups and bias are two dummy args which have no effect
groups and bias are two dummy args which have no effect
groups and bias are two dummy args which have no effect
def __init__(self, in_channels, out_channels,
                 kernel_size, stride, padding=0,
                 dilation=1, deformable_groups=2,
                 groups=None, bias=True):
        """
        groups and bias are two dummy args which have no effect
        """
        super(DCN, self).__init__(in_channels, out_channels,
                                  kernel_size, stride, padding, dilation, deformable_groups)

        channels_ = self.deformable_groups * 3 * self.kernel_size[0] * self.kernel_size[1]
        self.conv_offset_mask = nn.Conv2d(self.in_channels,
                                          channels_,
                                          kernel_size=self.kernel_size,
                                          stride=self.stride,
                                          padding=self.padding,
                                          bias=True)
        self.init_offset()
def __init__ ( self , in_channels , out_channels , kernel_size , stride , padding = 0 , dilation = 1 , deformable_groups = 2 , groups = None , bias = True ) : super ( DCN , self ) . __init__ ( in_channels , out_channels , kernel_size , stride , padding , dilation , deformable_groups ) channels_ = self . deformable_groups * 3 * self . kernel_size [ 0 ] * self . kernel_size [ 1 ] self . conv_offset_mask = nn . Conv2d ( self . in_channels , channels_ , kernel_size = self . kernel_size , stride = self . stride , padding = self . padding , bias = True ) self . init_offset ( )