code: def convert_Dstack(
      func, opset_version, input_names, output_names, context
  ):
      gb = onnx_helper.GraphBuilder()
      input0_ndim = len(func.inputs[0].shape)
      inputs = input_names
      if input0_ndim == 0:
          inputs = [
              gb.op("Unsqueeze", [name], axes=[0, 1, 2])
              for name in input_names
          ]
      elif input0_ndim == 1:
          inputs = [
              gb.op("Unsqueeze", [name], axes=[0, 2])
              for name in input_names
          ]
      elif input0_ndim == 2:
          inputs = [
              gb.op("Unsqueeze", [name], axes=[2])
              for name in input_names
          ]
      gb.op_output_named("Concat", inputs, output_names, axis=2)
      return gb.nodes()
  
imports: import warnings
  import chainer
  import numpy
  import onnx
  from onnx.mapping import NP_TYPE_TO_TENSOR_TYPE
  from onnx_chainer.functions.opset_version import support
  from onnx_chainer import onnx_helper
label_desc: Use image node_id 25 for calling a global function with example usage: convert_Dstack(func, opset_version, input_names, output_names, context) and returns: gb