code: def testTooManyReaders(self, sloppy=False):
      def interleave_fn(x):
          dataset = dataset_ops.Dataset.from_tensors(x)
          dataset = dataset.repeat(math_ops.cast(x, dtype=dtypes.int64))
          return dataset
  
      dataset = dataset_ops.Dataset.from_tensor_slices([4, 5, 6])
      dataset = dataset.repeat(self.repeat_count)
      dataset = dataset.apply(
          interleave_ops.parallel_interleave(
              interleave_fn,
              cycle_length=16,
              block_length=2,
              sloppy=sloppy,
          )
      )
      get_next = self.getNext(dataset)
      output_values = []
      for _ in range(30):
          output_values.append(self.evaluate(get_next()))
  
      expected_values = self._interleave(
          [[4] * 4, [5] * 5, [6] * 6] * self.repeat_count, 1, 2
      )
      self.assertCountEqual(output_values, expected_values)
  
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 9 for calling the ParallelInterleaveTest obj's underlying member method code with example usage: obj.testTooManyReaders(sloppy) and returns: dataset