# Copyright 2018 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""Experimental API for controlling threading in `tf.data` pipelines."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function

from tensorflow.python.data.ops import dataset_ops
from tensorflow.python.ops import gen_experimental_dataset_ops


class _SleepDataset(dataset_ops.UnaryUnchangedStructureDataset):
  """A `Dataset` that sleeps before producing each upstream element."""

  def __init__(self, input_dataset, sleep_microseconds):
    super(_SleepDataset, self).__init__(input_dataset)
    self._input_dataset = input_dataset
    self._sleep_microseconds = sleep_microseconds

  def _as_variant_tensor(self):
    return gen_experimental_dataset_ops.experimental_sleep_dataset(
        self._input_dataset._as_variant_tensor(),  # pylint: disable=protected-access
        self._sleep_microseconds,
        **dataset_ops.flat_structure(self))


def sleep(sleep_microseconds):
  """Sleeps for `sleep_microseconds` before producing each input element.

  Args:
    sleep_microseconds: The number of microseconds to sleep before producing an
      input element.

  Returns:
    A `Dataset` transformation function, which can be passed to
    `tf.data.Dataset.apply`.
  """

  def _apply_fn(dataset):
    return _SleepDataset(dataset, sleep_microseconds)

  return _apply_fn
