def METHOD_NAME(self):
    """Initialize bbox regression conv layers of the head."""
    self.reg_convs = nn.ModuleList()
    for i in range(self.stacked_convs):
        chn = self.in_channels if i == 0 else self.feat_channels
        if self.dcn_on_last_conv and i == self.stacked_convs - 1:
            conv_cfg = dict(type='DCNv2')
        else:
            conv_cfg = self.conv_cfg
        self.reg_convs.append(
            ConvModule(
                chn,
                self.feat_channels,
                3,
                stride=1,
                padding=1,
                conv_cfg=conv_cfg,
                norm_cfg=self.norm_cfg,
                bias=self.conv_bias))