code: def test_op_plus_gradient_accumulation(device_id, precision):
      dt_precision = PRECISION_TO_TYPE[precision]
  
      value = AA([[1]], dtype=dt_precision)
  
      from cntk import times_transpose, Axis
  
      a = C.input_variable(
          shape=(1,), dtype=dt_precision, needs_gradient=True, name="a"
      )
  
      input_op = a + a
  
      expected_forward = AA([[2]], dtype=dt_precision)
      expected_backward = {a: [[2]], a: [[2]]}
  
      forward_input = {a: value}
  
      unittest_helper(
          input_op,
          forward_input,
          expected_forward,
          expected_backward,
          device_id=device_id,
          precision=precision,
      )
  
imports: from __future__ import division
  import numpy
  import pytest
  import cntk
  from .ops_test_utils import unittest_helper, _test_unary_op, _test_binary_op, AA, precision, PRECISION_TO_TYPE, cntk_device
  from cntk.internal import sanitize_dtype_cntk
  from cntk.internal.utils import _ones_like, eval
label_desc: Use image node_id 3 for calling a global function with example usage: test_op_plus_gradient_accumulation(device_id, precision) without return types