code: def _make_transition(num_output_features, norm_layer, norm_kwargs):
      out = nn.HybridSequential(prefix="")
      out.add(
          norm_layer(**({} if norm_kwargs is None else norm_kwargs))
      )
      out.add(nn.Activation("relu"))
      out.add(
          nn.Conv2D(num_output_features, kernel_size=1, use_bias=False)
      )
      out.add(nn.AvgPool2D(pool_size=2, strides=2))
      return out
  
file_path: gluon-cv/gluoncv/model_zoo/densenet.py
imports: 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, Identity
label_desc: Use image node_id 3 for calling a global function with example usage: _make_transition(num_output_features, norm_layer, norm_kwargs) and returns: out