code: def _convert_upsample(net, node, graph, err):
      mode = node.attrs["mode"]
      node_name = node.name
      if mode == "nearest":
          caffe_params = net.params[node_name][0].data
          weights = np.ones(caffe_params.shape).astype("float32")
          np.copyto(
              net.params[node_name][0].data,
              weights,
              casting="same_kind",
          )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from __future__ import unicode_literals
  import numpy
  from ._graph import Node, Graph
label_desc: Use image node_id 12 for calling a global function with example usage: _convert_upsample(net, node, graph, err) without return types