docstr: Initialize classification conv layers of the head.
docstr_tok: ["Initialize","classification","conv","layers","of","the","head","."]
code: def _init_cls_convs(self):
      """Initialize classification conv layers of the head."""
      self.cls_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.cls_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,
              )
          )
  
file_path: mmocr/projects/ABCNet/abcnet/model/abcnet_det_head.py
imports: import torch.nn
  from mmcv.cnn import ConvModule, Scale
  from mmdet.models.utils import multi_apply
  from mmocr.models.textdet.heads.base import BaseTextDetHead
  from mmocr.registry import MODELS
label_desc: Use image node_id 3 for calling the ABCNetDetHead obj's underlying member method code with example usage: obj._init_cls_convs() without return types