message: Reflow comments to avoid being too long.
diff: @@ -1086,8 +1086,8 @@ def maybe_batch_join(tensors_list, keep_input, batch_size, capacity=32,
  added to the queue or not. If it is a scalar and evaluates `True`, then
  `tensors` are all added to the queue. If it is a vector and `enqueue_many`
  is `True`, then each example is added to the queue only if the
  - corresponding value in `keep_input` is `True`. This tensor essentially acts
  - as a filtering mechanism.
  + corresponding value in `keep_input` is `True`. This tensor essentially
  + acts as a filtering mechanism.
  batch_size: An integer. The new batch size pulled from the queue.
  capacity: An integer. The maximum number of elements in the queue.
  enqueue_many: Whether each tensor in `tensor_list_list` is a single
  @@ -1237,8 +1237,8 @@ def maybe_shuffle_batch(tensors, batch_size, capacity, min_after_dequeue,
  added to the queue or not. If it is a scalar and evaluates `True`, then
  `tensors` are all added to the queue. If it is a vector and `enqueue_many`
  is `True`, then each example is added to the queue only if the
  - corresponding value in `keep_input` is `True`. This tensor essentially acts
  - as a filtering mechanism.
  + corresponding value in `keep_input` is `True`. This tensor essentially
  + acts as a filtering mechanism.
  num_threads: The number of threads enqueuing `tensor_list`.
  seed: Seed for the random shuffling within the queue.
  enqueue_many: Whether each tensor in `tensor_list` is a single example.
  @@ -1379,8 +1379,8 @@ def maybe_shuffle_batch_join(tensors_list, batch_size, capacity,
  added to the queue or not. If it is a scalar and evaluates `True`, then
  `tensors` are all added to the queue. If it is a vector and `enqueue_many`
  is `True`, then each example is added to the queue only if the
  - corresponding value in `keep_input` is `True`. This tensor essentially acts
  - as a filtering mechanism.
  + corresponding value in `keep_input` is `True`. This tensor essentially
  + acts as a filtering mechanism.
  seed: Seed for the random shuffling within the queue.
  enqueue_many: Whether each tensor in `tensor_list_list` is a single
  example.
  