code: def __init__(self, inp, oup, groups=2):
      super(GroupConv, self).__init__()
      self.inp = inp
      self.oup = oup
      self.groups = groups
      self.conv = nn.Sequential(
          nn.Conv2D(
              inp, oup, 1, 1, 0, bias_attr=False, groups=self.groups[0]
          ),
          nn.BatchNorm2D(oup),
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import paddle
  import paddle.nn
  from ppocr.modeling.backbones.det_mobilenet_v3 import make_divisible
label_desc: Use image node_id 1 to create a new GroupConv object from inherited base classes: nn with example: obj = GroupConv(inp, oup, groups)