code: def _make_B(prefix, norm_layer, norm_kwargs):
      out = HybridConcurrent(axis=1, prefix=prefix)
      with out.name_scope():
          out.add(
              _make_branch(
                  None,
                  norm_layer,
                  norm_kwargs,
                  (288, 384, 3, 2, (1, 0, 0)),
              )
          )
          out.add(
              _make_branch(
                  None,
                  norm_layer,
                  norm_kwargs,
                  (288, 64, 1, None, None),
                  (64, 96, 3, None, 1),
                  (96, 96, 3, 2, (1, 0, 0)),
              )
          )
          out.add(_make_branch("max", norm_layer, norm_kwargs))
      return out
  
file_path: gluon-cv/gluoncv/model_zoo/action_recognition/i3d_inceptionv3.py
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.inception import inception_v3
label_desc: Use image node_id 4 for calling a global function with example usage: _make_B(prefix, norm_layer, norm_kwargs) and returns: out