code: def testMultiUseInputAutoGenSumDevice(self):
      parallel_tag = "parallelize:shard_by_1"
      split_op_device_option_clear_auto_gen_sum = core.DeviceOption(
          caffe2_pb2.CPU,
          extra_info=[
              parallel_tag,
              "{}:1".format(IR.ONLY_KEEP_IS_AUTO_GEN_SUM_OPS_TAG),
          ],
      )
      split_op_device_option_no_clear_auto_gen_sum = core.DeviceOption(
          caffe2_pb2.CPU, extra_info=[parallel_tag]
      )
      operators_clear_auto_gen_sum = [
          CreateOperator(
              "Direct",
              "in",
              "hidden1",
              device_option=split_op_device_option_clear_auto_gen_sum,
          ),
          CreateOperator(
              "Direct",
              "in",
              "hidden2",
              device_option=split_op_device_option_clear_auto_gen_sum,
          ),
          CreateOperator("Direct", ["hidden1", "hidden2"], "out"),
      ]
      (
          gradients_clear_auto_gen_sum,
          _,
      ) = GradientRegistry.GetBackwardPass(
          operators_clear_auto_gen_sum, {"out": "out_grad"}
      )
      self.assertEqual(gradients_clear_auto_gen_sum[-1].type, "Sum")
      self.assertNotIn(
          parallel_tag,
          gradients_clear_auto_gen_sum[-1].device_option.extra_info,
      )
  
      operators_no_clear_auto_gen_sum = [
          CreateOperator(
              "Direct",
              "in",
              "hidden1",
              device_option=split_op_device_option_no_clear_auto_gen_sum,
          ),
          CreateOperator(
              "Direct",
              "in",
              "hidden2",
              device_option=split_op_device_option_no_clear_auto_gen_sum,
          ),
          CreateOperator("Direct", ["hidden1", "hidden2"], "out"),
      ]
      (
          gradients_no_clear_auto_gen_sum,
          _,
      ) = GradientRegistry.GetBackwardPass(
          operators_no_clear_auto_gen_sum, {"out": "out_grad"}
      )
      self.assertEqual(gradients_clear_auto_gen_sum[-1].type, "Sum")
      self.assertIn(
          parallel_tag,
          gradients_no_clear_auto_gen_sum[-1].device_option.extra_info,
      )
  
imports: from hypothesis import given, settings
  import hypothesis.strategies
  import unittest
  from caffe2.proto import caffe2_pb2
  from caffe2.python import core, test_util, workspace
  from caffe2.python.core import CreateOperator, GradientRegistry, IR
  import numpy
label_desc: Use image node_id 16 for calling the TestGradientCalculation obj's underlying member method code with example usage: obj.testMultiUseInputAutoGenSumDevice() without return types