code: def test_multiple_ops(self):
      k = 1
  
      row_size = 100
      num_rows = 10
  
      row = np.arange(row_size, dtype=np.float32)
      db1 = np.stack(
          list(self._rng.permutation(row) for _ in range(num_rows))
      )
      db2 = np.stack(
          list(self._rng.permutation(row) for _ in range(num_rows))
      )
  
      @function(jit_compile=True)
      def ann(db1, db2):
          result1 = nn_ops.approx_max_k(db1, k, aggregate_to_topk=True)
          result2 = nn_ops.approx_max_k(db2, k, aggregate_to_topk=True)
          return (result1, result2)
  
      with ops.device("/device:TPU:0"):
          db1_op = variables.Variable(db1)
          db2_op = variables.Variable(db2)
          result1, result2 = ann(db1_op, db2_op)
  
      gt = np.argsort(-db1)[:, :k]
      ann_recall = self.compute_recall(result1[1].numpy(), gt)
      self.assertGreaterEqual(ann_recall, 0.95)
  
      gt = np.argsort(-db2)[:, :k]
      ann_recall = self.compute_recall(result2[1].numpy(), gt)
      self.assertGreaterEqual(ann_recall, 0.95)
  
imports: import itertools
  from absl.testing import parameterized
  import numpy
  from tensorflow.python.eager import backprop
  from tensorflow.python.eager import test
  from tensorflow.python.eager.def_function import function
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import nn_ops
  from tensorflow.python.ops import variables
label_desc: Use image node_id 9 for calling the ApproxTopkTest obj's underlying member method code with example usage: obj.test_multiple_ops() and returns: result1,  result2