y = variables.Variable(1.0, name='y')
  updates = control_flow_ops.no_op()
  for _ in range(3):
    with ops.control_dependencies([updates]):
      x_val = x.read_value() + y
      updates = x.assign_sub(0.1 * x_val)

  array_ops.identity(updates, name='result')


def write_graph(build_graph, out_dir):
  """Build a graph using build_graph and write it out."""
  g = ops.Graph()
  with g.as_default():

  void AssignAdd(TFE_Context* context, TFE_TensorHandle* value,
                 TF_Status* status);

 private:
  // Helper for running any single-argument assignment ops (Assign, AssignAdd,
  // AssignSub, ...).
  void GeneralAssignment(const char* op_name, TFE_Context* context,
                         TFE_TensorHandle* value, TF_Status* status);

  // The a handle for the resource-dtype tensor pointing to the variable's

Clustered nodes: 2385
Unclustered nodes: 4221
Number of clusters: 30

unclustered size 4221
 Add 17
 AddN 1
 All 1
 ApplyAdam 38
 Assert 7
 Assign 47
 AssignAdd 2
 AssignSub 2
 BroadcastGradientArgs 44
 Cast 38
 ConcatV2 3
 Const 875
 ControlTrigger 5
 Enter 874
 Equal 4
 Exit 69
 ExpandDims 9
 Fill 5
 FloorMod 1
 GreaterEqual 7
 Identity 113
 IsVariableInitialized 1
 IteratorGetNext 1