code: def bn_folding_lenet(
      image, test=False, channel_last=False, name="bn-folding-graph-ref"
  ):
      h = PF.convolution(
          image,
          16,
          (5, 5),
          (1, 1),
          with_bias=True,
          channel_last=channel_last,
          name="conv1",
      )
      h = F.max_pooling(h, (2, 2), channel_last=channel_last)
      h = F.relu(h)
  
      h = PF.convolution(
          h,
          16,
          (5, 5),
          (1, 1),
          with_bias=True,
          channel_last=channel_last,
          name="conv2",
      )
      h = F.max_pooling(h, (2, 2), channel_last=channel_last)
      h = F.relu(h)
  
      h = PF.affine(h, 10, with_bias=True, name="fc1")
      h = F.relu(h)
  
      pred = PF.affine(h, 10, with_bias=True, name="fc2")
      return pred
  
file_path: nnabla/python/test/utils/test_graph_converters/ref_graphs/lenets.py
imports: from __future__ import absolute_import
  import nnabla
  import nnabla.functions
  import nnabla.parametric_functions
  from nnabla.parameter import get_parameter_or_create
  from .helper import get_channel_axes
label_desc: Use image node_id 4 for calling a global function with example usage: bn_folding_lenet(image, test, channel_last, name) and returns: pred