code: def convert_tile(node, **kwargs):
      
      name, input_nodes, attrs = get_inputs(node, kwargs)
  
      reps_list = convert_string_to_list(attrs["reps"])
  
      initializer = kwargs["initializer"]
      reps_shape_np = np.array(reps_list, dtype='int64')
      data_type = onnx.mapping.NP_TYPE_TO_TENSOR_TYPE[reps_shape_np.dtype]
      dims = np.shape(reps_shape_np)
  
      output_shape_name = "reps_attr_tensor" + str(kwargs["idx"])
      tensor_node = onnx.helper.make_tensor_value_info(output_shape_name, data_type, dims)
  
      initializer.append(
          onnx.helper.make_tensor(
              name=output_shape_name,
              data_type=data_type,
              dims=dims,
              vals=reps_list,
              raw=False,
          )
      )
  
      input_nodes.append(output_shape_name)
      tile_node = onnx.helper.make_node(
          "Tile",
          input_nodes,
          [name],
          name=name
      )
  
      return [tensor_node, tile_node]
docs: Map MXNet's Tile operator attributes to onnx's Tile
      operator and return the created node.