code: def convert_Clip(
      func, opset_version, input_names, output_names, context
  ):
      if opset_version == 1:
          return (
              onnx_helper.make_node(
                  "Clip",
                  input_names,
                  output_names,
                  max=func.x_max,
                  min=func.x_min,
                  consumed_inputs=[1],
              ),
          )
      elif opset_version == 6:
          return (
              onnx_helper.make_node(
                  "Clip",
                  input_names,
                  output_names,
                  max=func.x_max,
                  min=func.x_min,
              ),
          )
      elif opset_version == 11:
          min_name = context.add_const(
              np.array(func.x_min, dtype=np.float32), "x_min"
          )
          max_name = context.add_const(
              np.array(func.x_max, dtype=np.float32), "x_max"
          )
          input_names.extend([min_name, max_name])
          return (
              onnx_helper.make_node("Clip", input_names, output_names),
          )
  
imports: import numpy
  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 17 for calling a global function with example usage: convert_Clip(func, opset_version, input_names, output_names, context) and returns: onnx_helper, onnx_helper, onnx_helper