1 files changed, 5 insertions, 51 deletions
diff --git a/tensorflow/contrib/data/python/ops/shuffle_ops.py b/tensorflow/contrib/data/python/ops/shuffle_ops.py
index 985d1d87d0..329b34fdfe 100644
--- a/tensorflow/contrib/data/python/ops/shuffle_ops.py
+++ b/tensorflow/contrib/data/python/ops/shuffle_ops.py
@@ -17,54 +17,12 @@ 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.data.util import random_seed
-from tensorflow.python.framework import constant_op
-from tensorflow.python.framework import dtypes
-from tensorflow.python.framework import ops
-from tensorflow.python.ops import gen_dataset_ops
-
-
-class _ShuffleAndRepeatDataset(dataset_ops.UnaryDataset):
-  """A `Dataset` that fuses `shuffle` and `repeat`."""
-
-  def __init__(self, input_dataset, buffer_size, count=None, seed=None):
-    super(_ShuffleAndRepeatDataset, self).__init__(input_dataset)
-    self._input_dataset = input_dataset
-    self._buffer_size = ops.convert_to_tensor(
-        buffer_size, dtype=dtypes.int64, name="buffer_size")
-    if count is None:
-      self._count = constant_op.constant(-1, dtype=dtypes.int64, name="count")
-    else:
-      self._count = ops.convert_to_tensor(
-          count, dtype=dtypes.int64, name="count")
-    self._seed, self._seed2 = random_seed.get_seed(seed)
-
-  def _as_variant_tensor(self):
-    # pylint: disable=protected-access
-    input_resource = self._input_dataset._as_variant_tensor()
-    return gen_dataset_ops.shuffle_and_repeat_dataset(
-        input_resource,
-        buffer_size=self._buffer_size,
-        count=self._count,
-        seed=self._seed,
-        seed2=self._seed2,
-        **dataset_ops.flat_structure(self))
-    # pylint: enable=protected-access
-
-  @property
-  def output_classes(self):
-    return self._input_dataset.output_classes
-
-  @property
-  def output_shapes(self):
-    return self._input_dataset.output_shapes
-
-  @property
-  def output_types(self):
-    return self._input_dataset.output_types
+from tensorflow.python.data.experimental.ops import shuffle_ops
+from tensorflow.python.util import deprecation
 
 
+@deprecation.deprecated(None,
+                        "Use `tf.data.experimental.shuffle_and_repeat(...)`.")
 def shuffle_and_repeat(buffer_size, count=None, seed=None):
   """Shuffles and repeats a Dataset returning a new permutation for each epoch.
 
@@ -93,8 +51,4 @@ def shuffle_and_repeat(buffer_size, count=None, seed=None):
     A `Dataset` transformation function, which can be passed to
     `tf.data.Dataset.apply`.
   """
-
-  def _apply_fn(dataset):  # pylint: disable=missing-docstring
-    return _ShuffleAndRepeatDataset(dataset, buffer_size, count, seed)
-
-  return _apply_fn
+  return shuffle_ops.shuffle_and_repeat(buffer_size, count, seed)