code: def testInterleaveDataset(
      self, input_values, cycle_length, block_length, num_parallel_calls
  ):
      count = 2
      dataset = (
          dataset_ops.Dataset.from_tensor_slices(input_values)
          .repeat(count)
          .interleave(
              lambda x: dataset_ops.Dataset.from_tensors(x).repeat(x),
              cycle_length,
              block_length,
              num_parallel_calls,
          )
      )
      expected_output = [
          element
          for element in _interleave(
              _repeat(input_values, count),
              cycle_length,
              block_length,
              num_parallel_calls,
          )
      ]
      self.assertDatasetProduces(dataset, expected_output)
  
imports: import multiprocessing
  import os
  from absl.testing import parameterized
  import numpy
  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 errors
  from tensorflow.python.framework import sparse_tensor
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import sparse_ops
  from tensorflow.python.platform import test
label_desc: Use image node_id 2 for calling the InterleaveTest obj's underlying member method code with example usage: obj.testInterleaveDataset(input_values, cycle_length, block_length, num_parallel_calls) without return types