code: def convert_Reshape(
      func, opset_version, input_names, output_names, context
  ):
      if opset_version == 1:
          return (
              onnx_helper.make_node(
                  "Reshape", input_names, output_names, shape=func.shape
              ),
          )
      elif opset_version == 5:
          if hasattr(func, "shape"):
              # if the function has shape parameter, means not dynamic
              assert len(input_names) == 1
              shape_name = context.add_const(
                  np.asarray(list(func.shape), dtype=np.int64), "shape"
              )
              input_names.append(shape_name)
          else:
              if len(input_names) != 2:
                  raise ValueError(
                      "shape must be set as parameter or 2nd input"
                  )
  
          return (
              onnx_helper.make_node(
                  "Reshape",
                  input_names,
                  output_names,
              ),
          )
  
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 11 for calling a global function with example usage: convert_Reshape(func, opset_version, input_names, output_names, context) and returns: onnx_helper, onnx_helper