code: def testErrorsInInterleaveFn(self):
      def map_py_fn(x):
          if x == 5:
              raise ValueError()
          return x
  
      def interleave_fn(x):
          dataset = dataset_ops.Dataset.from_tensors(x)
          y = script_ops.py_func(map_py_fn, [x], x.dtype)
          dataset = dataset.repeat(y)
          return dataset
  
      def dataset_fn(
          input_values,
          cycle_length,
          block_length,
          sloppy,
          buffer_output_elements,
          prefetch_input_elements,
      ):
          return (
              dataset_ops.Dataset.from_tensor_slices(input_values)
              .repeat(self.repeat_count)
              .apply(
                  interleave_ops.parallel_interleave(
                      interleave_fn,
                      cycle_length,
                      block_length,
                      sloppy,
                      buffer_output_elements,
                      prefetch_input_elements,
                  )
              )
          )
  
      next_element = self.getNext(
          dataset_fn(
              input_values=np.int64([4, 5, 6]),
              cycle_length=2,
              block_length=1,
              sloppy=False,
              buffer_output_elements=1,
              prefetch_input_elements=0,
          )
      )
      for i, expected_element in enumerate(
          self._interleave(
              [[4] * 4, [5], [6] * 6] * self.repeat_count, 2, 1
          )
      ):
          if expected_element == 5:
              with self.assertRaises(errors.InvalidArgumentError):
                  self.evaluate(next_element())
          else:
              actual_element = self.evaluate(next_element())
              self.assertEqual(
                  expected_element,
                  actual_element,
                  "At index %s: %s expected, got: %s"
                  % (i, expected_element, actual_element),
              )
      with self.assertRaises(errors.OutOfRangeError):
          self.evaluate(next_element())
  
imports: import itertools
  import math
  import threading
  import time
  from absl.testing import parameterized
  import numpy
  from tensorflow.python.data.experimental.ops import interleave_ops
  from tensorflow.python.data.experimental.ops import testing
  from tensorflow.python.data.kernel_tests import checkpoint_test_base
  from tensorflow.python.data.kernel_tests import test_base
  from tensorflow.python.data.ops import dataset_ops
  from tensorflow.python.data.ops import options
  from tensorflow.python.framework import combinations
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import sparse_tensor
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import script_ops
  from tensorflow.python.ops import sparse_ops
  from tensorflow.python.platform import test
label_desc: Use image node_id 12 for calling the ParallelInterleaveTest obj's underlying member method code with example usage: obj.testErrorsInInterleaveFn() and returns: x, dataset, dataset_ops