code: def ensure_bias_vector(self):
      for _op in self._model.op:
          ensure_input = -1
          if (
              _op.type == MaceOp.Conv2D.name
              or _op.type == MaceOp.DepthwiseConv2d.name
              or _op.type == MaceOp.FullyConnected.name
          ):
              ensure_input = 3
          if _op.type == MaceOp.Deconv2D.name:
              ensure_input = 4
          if ensure_input == -1 or len(_op.input) != ensure_input - 1:
              continue
  
          tensor = self._model.tensors.add()
          tensor.name = _op.name + "/add/bias_add"
          tensor.dims.extend([_op.output_shape[0].dims[-1]])
          if (
              _op.output_type[0] == mace_pb2.DT_UINT8
              or _op.output_type[0] == mace_pb2.DT_INT16
          ):
              tensor.data_type = mace_pb2.DT_INT32
              input_name = _op.input[0]
              for input_op in self._model.op:
                  if input_op.output[0] == input_name:
                      scale_input = input_op.quantize_info[0].scale
                      break
              filter_name = _op.input[1]
              for filter_tensor in self._model.tensors:
                  if filter_tensor.name == filter_name:
                      scale_filter = filter_tensor.scale
                      break
              tensor.scale = scale_input * scale_filter
              tensor.zero_point = 0
              tensor.quantized = True
              tensor.int32_data.extend([0] * tensor.dims[0])
          elif _op.output_type[0] == mace_pb2.DT_FLOAT:
              tensor.data_type = mace_pb2.DT_FLOAT
              tensor.float_data.extend([0.0] * tensor.dims[0])
          _op.input.extend([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 17 for calling the ApuConverter obj's underlying member method code with example usage: obj.ensure_bias_vector() without return types