code: def _convert_upsample(node, graph, err):
      factor = int(node.attrs["height_scale"])
      node_name = node.name
      input_name = str(node.inputs[0])
      output_name = str(node.outputs[0])
      # input_shape = graph.shape_dict[input_name]
      # channels = input_shape[1]
      channels = graph.channel_dims[input_name]
      pad = int(math.ceil((factor - 1) / 2.0))
      # layer = myf("Deconvolution", node_name, [input_name], [output_name],
      #             kernel_size=2 * factor - factor % 2,
      #             stride=factor, group=channels,
      #             pad = pad, num_output=channels, bias_term = False)
      mode = node.attrs["mode"]
      # https://github.com/pytorch/pytorch/issues/6900
      if mode == "bilinear":
          layer = myf(
              "Deconvolution",
              node_name,
              [input_name],
              [output_name],
              convolution_param=dict(
                  num_output=channels,
                  kernel_size=2 * factor - factor % 2,
                  stride=factor,
                  pad=pad,
                  group=channels,
                  bias_term=False,
                  weight_filler=dict(type="bilinear_upsampling"),
              ),
          )
      else:
          layer = myf(
              "Deconvolution",
              node_name,
              [input_name],
              [output_name],
              convolution_param=dict(
                  num_output=channels,
                  kernel_size=factor,
                  stride=factor,
                  group=channels,
                  bias_term=False,
              ),
          )
  
      graph.channel_dims[output_name] = graph.channel_dims[input_name]
      return layer
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from __future__ import unicode_literals
  from caffe import params
  import math
  import numpy
  from ._graph import Node, Graph
  from MyCaffe import Function
label_desc: Use image node_id 14 for calling a global function with example usage: _convert_upsample(node, graph, err) and returns: layer