code: def _add_conv(
      out,
      channels=1,
      kernel=1,
      stride=1,
      pad=0,
      num_group=1,
      active=True,
      relu6=False,
      norm_layer=BatchNorm,
      norm_kwargs=None,
  ):
      out.add(
          nn.Conv2D(
              channels,
              kernel,
              stride,
              pad,
              groups=num_group,
              use_bias=False,
          )
      )
      out.add(
          norm_layer(
              scale=True, **({} if norm_kwargs is None else norm_kwargs)
          )
      )
      if active:
          out.add(ReLU6() if relu6 else nn.Activation("relu"))
  
imports: from mxnet.gluon import nn
  from mxnet.gluon.nn import BatchNorm
  from mxnet.context import cpu
  from mxnet.gluon.block import HybridBlock
  from ..nn import ReLU6
label_desc: Use image node_id 1 for calling a global function with example usage: _add_conv(out, channels, kernel, stride, pad, num_group, active, relu6, norm_layer, norm_kwargs) without return types