message: rename op_or_dataset to iterable
diff: @@ -31,14 +31,14 @@ from tensorflow.python.platform import test
  class DatasetBenchmarkBase(test.Benchmark):
  """Base class for dataset benchmarks."""
  - def _run_eager_benchmark(self, op_or_dataset, iters, warmup):
  + def _run_eager_benchmark(self, iterable, iters, warmup):
  """Benchmark in eager mode.
  Runs the op `iters` times. In each iteration, the benchmark measures
  the time it takes to go execute the op.
  Args:
  - op_or_dataset: The tf op or tf.data Dataset to benchmark.
  + iterable: The tf op or tf.data Dataset to benchmark.
  iters: Number of times to repeat the timing.
  warmup: If true, warms up the session caches by running an untimed run.
  @@ -54,10 +54,10 @@ class DatasetBenchmarkBase(test.Benchmark):
  for _ in range(iters):
  if warmup:
  - iterator = iter(op_or_dataset)
  + iterator = iter(iterable)
  next(iterator)
  - iterator = iter(op_or_dataset)
  + iterator = iter(iterable)
  start = time.time()
  next(iterator)
  end = time.time()
  @@ -65,7 +65,7 @@ class DatasetBenchmarkBase(test.Benchmark):
  return np.median(deltas)
  def _run_graph_benchmark(self,
  - op_or_dataset,
  + iterable,
  iters,
  warmup,
  session_config,
  @@ -76,7 +76,7 @@ class DatasetBenchmarkBase(test.Benchmark):
  the time it takes to go execute the op.
  Args:
  - op_or_dataset: The tf op or tf.data Dataset to benchmark.
  + iterable: The tf op or tf.data Dataset to benchmark.
  iters: Number of times to repeat the timing.
  warmup: If true, warms up the session caches by running an untimed run.
  session_config: A ConfigProto protocol buffer with configuration options
  @@ -95,11 +95,11 @@ class DatasetBenchmarkBase(test.Benchmark):
  "Graph mode benchmarking is not supported in eager mode.")
  if is_dataset:
  - iterator = dataset_ops.make_initializable_iterator(dataset)
  + iterator = dataset_ops.make_initializable_iterator(iterable)
  next_element = iterator.get_next()
  op = nest.flatten(next_element)[0].op
  else:
  - op = op_or_dataset
  + op = iterable
  for _ in range(iters):
  with session.Session(config=session_config) as sess:
  @@ -142,13 +142,13 @@ class DatasetBenchmarkBase(test.Benchmark):
  if context.executing_eagerly():
  return self._run_eager_benchmark(
  - op_or_dataset=op,
  + iterable=op,
  iters=iters,
  warmup=warmup
  )
  return self._run_graph_benchmark(
  - op_or_dataset=op,
  + iterable=op,
  iters=iters,
  warmup=warmup,
  session_config=session_config,
  @@ -200,14 +200,14 @@ class DatasetBenchmarkBase(test.Benchmark):
  if context.executing_eagerly():
  median_duration = self._run_eager_benchmark(
  - op_or_dataset=dataset,
  + iterable=dataset,
  iters=iters,
  warmup=warmup
  )
  return median_duration / float(num_elements)
  median_duration = self._run_graph_benchmark(
  - op_or_dataset=dataset,
  + iterable=dataset,
  iters=iters,
  warmup=warmup,
  session_config=session_config
  