code: def _make_basic_conv(
      in_channels,
      channels,
      norm_layer=BatchNorm,
      norm_kwargs=None,
      **kwargs,
  ):
      out = nn.HybridSequential(prefix="")
      out.add(
          nn.Conv3D(
              in_channels=in_channels,
              channels=channels,
              use_bias=False,
              **kwargs,
          )
      )
      out.add(
          norm_layer(
              in_channels=channels,
              epsilon=0.001,
              **({} if norm_kwargs is None else norm_kwargs),
          )
      )
      out.add(nn.Activation("relu"))
      return out
  
imports: from mxnet import nd
  from mxnet import init
  from mxnet.context import cpu
  from mxnet.gluon.block import HybridBlock
  from mxnet.gluon import nn
  from mxnet.gluon.nn import BatchNorm
  from mxnet.gluon.contrib.nn import HybridConcurrent
  from gluoncv.model_zoo.googlenet import googlenet
label_desc: Use image node_id 1 for calling a global function with example usage: _make_basic_conv(in_channels, channels, norm_layer, norm_kwargs) and returns: out