code: def test_text_line_dataset(self, use_function, use_control_flow):
      self._set_seed()
      with test_util.deterministic_ops():
  
          def write_nums_to_file(filename, numbers):
              path = os.path.join(self.get_temp_dir(), filename)
              with open(path, "w") as f:
                  f.write("\n".join(str(n) for n in numbers))
              return path
  
          f1 = write_nums_to_file("f1", (1, 2, 3))
          f2 = write_nums_to_file("f2", (4, 5, 6))
          f3 = write_nums_to_file("f3", (7, 8, 9))
  
          if use_control_flow:
  
              def interleave_fn(filename):
                  # Test function that uses control flow. The True branch is never taken
                  concat = string_ops.string_join([filename, "abc"])
                  return cond.cond(
                      math_ops.equal(filename, "abc"),
                      lambda: reader_ops.TextLineDataset(concat),
                      lambda: reader_ops.TextLineDataset(filename),
                  )
  
          else:
  
              def interleave_fn(filename):
                  return reader_ops.TextLineDataset(filename)
  
          if use_function:
              interleave_fn = def_function.function(interleave_fn)
  
          dataset = dataset_ops.Dataset.from_tensor_slices([f1, f2, f3])
          dataset = dataset.apply(
              testing.assert_next(["ParallelInterleave"])
          )
          dataset = dataset.interleave(
              interleave_fn, cycle_length=3, num_parallel_calls=3
          )
  
          self.assertDatasetProduces(
              dataset,
              expected_output=[
                  "1",
                  "4",
                  "7",
                  "2",
                  "5",
                  "8",
                  "3",
                  "6",
                  "9",
              ],
          )
  
imports: import os
  import time
  from absl.testing import parameterized
  import numpy
  from tensorflow.python.compat import v2_compat
  from tensorflow.python.data.experimental.ops import batching
  from tensorflow.python.data.experimental.ops import interleave_ops
  from tensorflow.python.data.experimental.ops import testing
  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.data.ops import readers
  from tensorflow.python.eager import def_function
  from tensorflow.python.framework import combinations
  from tensorflow.python.framework import config
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import random_seed
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import cond
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import random_ops
  from tensorflow.python.ops import script_ops
  from tensorflow.python.ops import string_ops
  from tensorflow.python.ops import variables
  from tensorflow.python.platform import test
label_desc: Use image node_id 10 for calling the MakeDeterministicTest obj's underlying member method code with example usage: obj.test_text_line_dataset(use_function, use_control_flow) and returns: path, cond, reader_ops