code: def testDatasetMapHealthyResults(self):
      check_numerics_callback.enable_check_numerics()
  
      tensor = constant_op.constant(
          [0.5, 1.0, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0, 4.5, 5.0]
      )
  
      def map_fn(x):
          return math_ops.log(math_ops.square(x) + 1)
  
      dataset = (
          dataset_ops.Dataset.from_tensor_slices(tensor)
          .batch(2)
          .map(map_fn)
      )
  
      @def_function.function
      def get_batches():
          iterator = iter(dataset)
          return [next(iterator), next(iterator)]
  
      batches = self.evaluate(get_batches())
      self.assertLen(batches, 2)
      self.assertAllClose(batches[0], np.log([1.25, 2]))
      self.assertAllClose(batches[1], np.log([3.25, 5]))
  
imports: import re
  import numpy
  from tensorflow.python.data.ops import dataset_ops
  from tensorflow.python.debug.lib import check_numerics_callback
  from tensorflow.python.eager import backprop
  from tensorflow.python.eager import context
  from tensorflow.python.eager import def_function
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_grad
  from tensorflow.python.ops import custom_gradient
  from tensorflow.python.ops import gen_nn_ops
  from tensorflow.python.ops import gradient_checker_v2
  from tensorflow.python.ops import math_grad
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import variables
  from tensorflow.python.platform import googletest
  from tensorflow.python.platform import test
label_desc: Use image node_id 4 for calling the CheckNumericsCallbackTest obj's underlying member method code with example usage: obj.testDatasetMapHealthyResults() and returns: math_ops, list