private void addOperations(PreparedStatement statement, long testId, String version, MeasuredOperationList operations) throws SQLException {
        for (MeasuredOperation operation : operations) {
            statement.setLong(1, testId);
            statement.setString(2, version);
            statement.setBigDecimal(3, operation.getTotalTime().toUnits(Duration.MILLI_SECONDS).getValue());
            statement.addBatch();
        }
    }

  return flib_def;
}

Node* MakeCall(Graph* graph, const string& callee_name, const string& node_name,
               Status* status) {
  NodeDef call_node;
  call_node.set_name(node_name);
  call_node.set_op(callee_name);
  return graph->AddNode(call_node, status);
}

TEST(ResourceOperationSafetyAnalysisTest, CallRead) {
  Scope root = Scope::NewRootScope().ExitOnError();

  FunctionDefLibrary flib_def =

	if err != nil {
		ptestErr = &PackageError{
			ImportStack: stk.Copy(),
			Err:         err,
		}
		incomplete = true
		embedErr := err.(*EmbedError)
		ptestErr.setPos(p.Internal.Build.TestEmbedPatternPos[embedErr.Pattern])
	}
	stk.Pop()

	stk.Push(p.ImportPath + "_test")
	pxtestNeedsPtest := false
	var pxtestIncomplete bool
	rawXTestImports := str.StringList(p.XTestImports)

		for i, v := range check.Args {
			if v != end {
				continue
			}

			check.SetArg(i, start)
			goto replacedEnd
		}
		panic(fmt.Sprintf("unreachable, ind: %v, start: %v, end: %v", ind, start, end))
	replacedEnd:

		for i, v := range ind.Args {
			if v != start {
				continue
			}

			ind.SetArg(i, end)
			goto replacedStart
		}

    const absl::flat_hash_map<absl::string_view, int>& histogram) {
  for (const auto& pair : histogram) {
    XlaAutoClusteringSummary::OpAndCount* new_entry = result->Add();
    new_entry->set_op(std::string(pair.first));
    new_entry->set_count(pair.second);
  }

  absl::c_sort(*result, [](const XlaAutoClusteringSummary::OpAndCount& a,
                           const XlaAutoClusteringSummary::OpAndCount& b) {

    TF_ASSIGN_OR_RETURN(auto tf_name,
                        GetTensorFlowOpName(inst->getName().getStringRef()));
    op_name.append(tf_name);
  }

  node_def->set_name(name.str());
  node_def->set_op(std::string(op_name.str()));

  // Update NodeDef constructed out of an MLIR Case/If/While op to map it to
  // either TensorFlow StatelessX or X op depending on the additional attribute.

	for _, b := range f.Blocks {
		for _, v := range b.Values {
			for i, a := range v.Args {
				if a.Op == OpSPanchored || opcodeTable[a.Op].nilCheck {
					v.SetArg(i, a.Args[0])
				}
			}
		}
		for i, c := range b.ControlValues() {
			if c.Op == OpSPanchored || opcodeTable[c.Op].nilCheck {
				b.ReplaceControl(i, c.Args[0])
			}
		}
	}

}

func (v *Value) AddArgs(a ...*Value) {
	if v.Args == nil {
		v.resetArgs() // use argstorage
	}
	v.Args = append(v.Args, a...)
	for _, x := range a {
		x.Uses++
	}
}
func (v *Value) SetArg(i int, w *Value) {
	v.Args[i].Uses--
	v.Args[i] = w
	w.Uses++
}
func (v *Value) SetArgs1(a *Value) {
	v.resetArgs()
	v.AddArg(a)
}
func (v *Value) SetArgs2(a, b *Value) {
	v.resetArgs()

                    foo = objectFactory.directoryProperty()
                }

                @OutputDirectory
                DirectoryProperty getFoo() { return foo }

                void setFoo(File foo) { throw RuntimeException("") }

                @TaskAction
                void produce() { print("Producer ran") }
            }

            abstract class Consumer extends DefaultTask {

  const int num_inputs = input_shapes->num_items;
  NodeDef node_def;
  tensorflow::ImmediateExecutionOperation* op = tensorflow::unwrap(tfe_op);
  node_def.set_name(op->Name());
  node_def.set_op(op->Name());
  for (int i = 0; i < num_inputs; ++i) {
    node_def.add_input("dummy_input");
  }
  OperationFromInterface(op)->Attrs().FillAttrValueMap(node_def.mutable_attr());