message: refactor ParallelInterleaveBenchmark
diff: @@ -90,8 +90,13 @@ class ParallelInterleaveBenchmark(benchmark_base.DatasetBenchmarkBase):
  num_parallel_calls=None):
  dataset = dataset_ops.Dataset.range(1).repeat()
  interleave_fn = _make_fake_dataset_fn(initial_delay, remainder_delay)
  - return self.apply_interleave(interleave_version, dataset, interleave_fn,
  - cycle_length, num_parallel_calls)
  + return self.apply_interleave(
  + interleave_version=interleave_version,
  + dataset=dataset,
  + interleave_fn=interleave_fn,
  + cycle_length=cycle_length,
  + num_parallel_calls=num_parallel_calls
  + )
  def _benchmark(self,
  interleave_version,
  @@ -103,8 +108,13 @@ class ParallelInterleaveBenchmark(benchmark_base.DatasetBenchmarkBase):
  num_parallel_calls=None,
  attach_stats_aggregator=False,
  name=None):
  - dataset = self.make_dataset(interleave_version, initial_delay_us,
  - remainder_delay_us, cycle_length, num_parallel_calls)
  + dataset = self.make_dataset(
  + interleave_version=interleave_version,
  + initial_delay=initial_delay_us,
  + remainder_delay=remainder_delay_us,
  + cycle_length=cycle_length,
  + num_parallel_calls=num_parallel_calls
  + )
  if attach_stats_aggregator:
  aggregator = stats_aggregator.StatsAggregator()
  opts = dataset_ops.Options()
  @@ -122,7 +132,7 @@ class ParallelInterleaveBenchmark(benchmark_base.DatasetBenchmarkBase):
  def benchmark_remote_file_simulation(self):
  for version in [EXPERIMENTAL_PARALLEL, CORE_PARALLEL]:
  self._benchmark(
  - version,
  + interleave_version=version,
  initial_delay_us=100 * 1000,
  remainder_delay_us=1000,
  num_elements=5000,
  @@ -131,14 +141,17 @@ class ParallelInterleaveBenchmark(benchmark_base.DatasetBenchmarkBase):
  def benchmark_fast_input(self):
  for version in [EXPERIMENTAL_PARALLEL, CORE_PARALLEL]:
  self._benchmark(
  - version, num_elements=200000, name="fast_input_" + version)
  + interleave_version=version,
  + num_elements=200000,
  + name="fast_input_" + version
  + )
  # Measure the overhead of parallel interleaves compared to non-parallel
  # interleave.
  def benchmark_single_cycle(self):
  for version in [NON_PARALLEL, EXPERIMENTAL_PARALLEL, CORE_PARALLEL]:
  self._benchmark(
  - version,
  + interleave_version=version,
  cycle_length=1,
  num_elements=200000,
  name="single_cycle_" + version)
  @@ -147,7 +160,7 @@ class ParallelInterleaveBenchmark(benchmark_base.DatasetBenchmarkBase):
  # cannot be compared here because it sets num_parallel_calls = cycle_length.
  def benchmark_single_parallel_call(self):
  self._benchmark(
  - CORE_PARALLEL,
  + interleave_version=CORE_PARALLEL,
  num_elements=200000,
  num_parallel_calls=1,
  name="single_parallel_call_" + CORE_PARALLEL)
  @@ -155,14 +168,14 @@ class ParallelInterleaveBenchmark(benchmark_base.DatasetBenchmarkBase):
  def benchmark_long_cycle(self):
  for version in [EXPERIMENTAL_PARALLEL, CORE_PARALLEL]:
  self._benchmark(
  - version,
  + interleave_version=version,
  cycle_length=1000,
  num_elements=100000,
  name="long_cycle_" + version)
  def benchmark_stats(self):
  self._benchmark(
  - CORE_PARALLEL,
  + interleave_version=CORE_PARALLEL,
  cycle_length=50,
  num_elements=1000,
  name="stats",
  