code: def add_paddings_tensor_from_arg(self, op):
      padding_value_arg = ConverterUtil.get_arg(
          op, MaceKeyword.mace_paddings_str
      )
      padding_value_tensor = self._model.tensors.add()
      padding_value_tensor.name = op.name + "/padding:0"
      padding_value_tensor.data_type = mace_pb2.DT_INT32
      mace_check(
          len(padding_value_arg.ints) % 2 == 0,
          op.name + ": the rank of paddings should be even",
      )
      padding_value_tensor.dims.extend(
          [int(len(padding_value_arg.ints) / 2), 2]
      )
      padding_value_tensor.int32_data.extend(padding_value_arg.ints)
      op.input.extend([padding_value_tensor.name])
  
imports: import copy
  import numpy
  from enum import Enum
  from operator import mul
  from py_proto import mace_pb2
  from transform import base_converter
  from transform.base_converter import ConverterUtil
  from transform.base_converter import EltwiseType
  from transform.base_converter import MaceKeyword
  from transform.base_converter import MaceOp
  from transform.base_converter import PaddingMode
  from transform.base_converter import PadType
  from transform.base_converter import PoolingType
  from transform.base_converter import ReduceType
  from transform.base_converter import DataFormat
  from transform.base_converter import FrameworkType
  from utils.util import mace_check
label_desc: Use image node_id 9 for calling the ApuConverter obj's underlying member method code with example usage: obj.add_paddings_tensor_from_arg(op) without return types