message: Correct the logging message as (very likely) we will support queue-based input
  pipeline.
diff: @@ -946,23 +946,14 @@ class _InputPipeline(object):
  # user code, so, log a warning.
  if ops.get_default_graph().get_collection(ops.GraphKeys.QUEUE_RUNNERS):
  err_msg = ('Input pipeline contains one or more QueueRunners. '
  - 'These are not supported via TPUEstimator. You must convert '
  - 'your input pipeline to use `tf.data` instead (see '
  + 'It could be slow and not scalable. Please consider '
  + 'converting your input pipeline to use `tf.data` instead (see '
  'https://www.tensorflow.org/programmers_guide/datasets for '
  'instructions.')
  if _WRAP_INPUT_FN_INTO_WHILE_LOOP:
  raise RuntimeError(err_msg)
  else:
  logging.warn(err_msg)
  - elif ops.get_default_graph().get_collection(ops.GraphKeys.SUMMARIES):
  - # Queue Runner has summary Ops by default. So here we use elif to do
  - # necessary checks for Dataset input pipeline only.
  - err_msg = ('Input pipeline contains `tf.summary` operations. '
  - 'These are not currently supported.')
  - if _WRAP_INPUT_FN_INTO_WHILE_LOOP:
  - raise RuntimeError(err_msg)
  - else:
  - logging.warn(err_msg)
  class _ModelFnWrapper(object):
  