[tf.data] Remove deprecated `tf.contrib.data.Iterator` alias.

This change removes the following class:
* `tf.contrib.data.Iterator`.

IF THIS BREAKS YOU: Replace `tf.contrib.data.Iterator` with `tf.data.Iterator`
when explicitly constructing an iterator. The API for the resulting object is
identical.

PiperOrigin-RevId: 185024771

5 files changed, 59 insertions, 777 deletions

diff --git a/tensorflow/contrib/data/__init__.py b/tensorflow/contrib/data/__init__.py
index 22de13b558..21db1044b0 100644
--- a/tensorflow/contrib/data/__init__.py
+++ b/tensorflow/contrib/data/__init__.py
@@ -22,7 +22,6 @@ See the @{$datasets$Importing Data} Programmer's Guide for an overview.
 
 @@Dataset
 @@Counter
-@@Iterator
 
 @@batch_and_drop_remainder
 @@dense_to_sparse_batch
@@ -68,7 +67,6 @@ from tensorflow.contrib.data.python.ops.readers import SqlDataset
 from tensorflow.contrib.data.python.ops.resampling import rejection_resample
 from tensorflow.contrib.data.python.ops.scan_ops import scan
 from tensorflow.contrib.data.python.ops.shuffle_ops import shuffle_and_repeat
-from tensorflow.python.data.ops.iterator_ops import Iterator
 # pylint: enable=unused-import
 
 from tensorflow.python.util.all_util import remove_undocumented
diff --git a/tensorflow/contrib/data/python/kernel_tests/BUILD b/tensorflow/contrib/data/python/kernel_tests/BUILD
index 3ee82933bc..f58872f2a8 100644
--- a/tensorflow/contrib/data/python/kernel_tests/BUILD
+++ b/tensorflow/contrib/data/python/kernel_tests/BUILD
@@ -208,59 +208,19 @@ py_test(
 )
 
 tf_py_test(
-    name = "iterator_ops_cluster_test",
+    name = "get_single_element_test",
     size = "small",
-    srcs = ["iterator_ops_cluster_test.py"],
-    additional_deps = [
-        "//tensorflow/contrib/data/python/ops:dataset_ops",
-        "//tensorflow/core:protos_all_py",
-        "//tensorflow/python:array_ops",
-        "//tensorflow/python:client_testlib",
-        "//tensorflow/python:dtypes",
-        "//tensorflow/python:errors",
-        "//tensorflow/python:framework_ops",
-        "//tensorflow/python:framework_test_lib",
-        "//tensorflow/python:function",
-        "//tensorflow/python:functional_ops",
-        "//tensorflow/python:session",
-        "//tensorflow/python/data/ops:iterator_ops",
-    ],
-    grpc_enabled = True,
-    tags = [
-        "no_windows",
-        "oss_serial",
-    ],
-)
-
-tf_py_test(
-    name = "iterator_ops_test",
-    size = "small",
-    srcs = ["iterator_ops_test.py"],
+    srcs = ["get_single_element_test.py"],
     additional_deps = [
         "//third_party/py/numpy",
         "//tensorflow/contrib/data/python/ops:dataset_ops",
-        "//tensorflow/contrib/data/python/ops:readers",
-        "//tensorflow/core:protos_all_py",
         "//tensorflow/python:array_ops",
         "//tensorflow/python:client_testlib",
         "//tensorflow/python:constant_op",
-        "//tensorflow/python:dataset_ops_gen",
         "//tensorflow/python:dtypes",
         "//tensorflow/python:errors",
-        "//tensorflow/python:framework_ops",
         "//tensorflow/python:framework_test_lib",
-        "//tensorflow/python:function",
-        "//tensorflow/python:functional_ops",
-        "//tensorflow/python:gradients",
-        "//tensorflow/python:io_ops",
-        "//tensorflow/python:math_ops",
-        "//tensorflow/python:parsing_ops",
-        "//tensorflow/python:script_ops",
-        "//tensorflow/python:session",
-        "//tensorflow/python:training",
-        "//tensorflow/python/data/ops:iterator_ops",
     ],
-    grpc_enabled = True,
 )
 
 py_test(
diff --git a/tensorflow/contrib/data/python/kernel_tests/get_single_element_test.py b/tensorflow/contrib/data/python/kernel_tests/get_single_element_test.py
new file mode 100644
index 0000000000..03d30bd100
--- /dev/null
+++ b/tensorflow/contrib/data/python/kernel_tests/get_single_element_test.py
@@ -0,0 +1,57 @@
+# Copyright 2017 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.
+# ==============================================================================
+"""Tests for the experimental input pipeline ops."""
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
+from tensorflow.contrib.data.python.ops import dataset_ops
+from tensorflow.python.framework import constant_op
+from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import errors
+from tensorflow.python.ops import array_ops
+from tensorflow.python.platform import test
+
+
+class GetSingleElementTest(test.TestCase):
+
+  def testGetSingleElement(self):
+    skip_value = array_ops.placeholder(dtypes.int64, shape=[])
+    take_value = array_ops.placeholder_with_default(
+        constant_op.constant(1, dtype=dtypes.int64), shape=[])
+
+    dataset = (dataset_ops.Dataset.range(100)
+               .skip(skip_value)
+               .map(lambda x: x * x)
+               .take(take_value))
+
+    element = dataset_ops.get_single_element(dataset)
+
+    with self.test_session() as sess:
+      self.assertEqual(0, sess.run(element, feed_dict={skip_value: 0}))
+      self.assertEqual(25, sess.run(element, feed_dict={skip_value: 5}))
+      self.assertEqual(100, sess.run(element, feed_dict={skip_value: 10}))
+
+      with self.assertRaisesRegexp(errors.InvalidArgumentError,
+                                   "Dataset was empty."):
+        sess.run(element, feed_dict={skip_value: 100})
+
+      with self.assertRaisesRegexp(errors.InvalidArgumentError,
+                                   "Dataset had more than one element."):
+        sess.run(element, feed_dict={skip_value: 0, take_value: 2})
+
+
+if __name__ == "__main__":
+  test.main()
diff --git a/tensorflow/contrib/data/python/kernel_tests/iterator_ops_cluster_test.py b/tensorflow/contrib/data/python/kernel_tests/iterator_ops_cluster_test.py
deleted file mode 100644
index 02379d064d..0000000000
--- a/tensorflow/contrib/data/python/kernel_tests/iterator_ops_cluster_test.py
+++ /dev/null
@@ -1,108 +0,0 @@
-# Copyright 2017 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.
-# ==============================================================================
-"""Tests for the experimental input pipeline ops that need test_util."""
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
-
-from tensorflow.contrib.data.python.ops import dataset_ops
-from tensorflow.core.protobuf import config_pb2
-from tensorflow.python.client import session
-from tensorflow.python.data.ops import iterator_ops
-from tensorflow.python.framework import dtypes
-from tensorflow.python.framework import errors
-from tensorflow.python.framework import function
-from tensorflow.python.framework import ops
-from tensorflow.python.framework import test_util
-from tensorflow.python.ops import array_ops
-from tensorflow.python.ops import functional_ops
-from tensorflow.python.platform import test
-
-
-class IteratorClusterTest(test.TestCase):
-
-  def testRemoteIteratorWithoutRemoteCallFail(self):
-    worker_config = config_pb2.ConfigProto()
-    worker_config.device_count["CPU"] = 2
-    worker, _ = test_util.create_local_cluster(
-        1, 1, worker_config=worker_config)
-
-    with ops.device("/job:worker/replica:0/task:0/cpu:1"):
-      dataset_3 = dataset_ops.Dataset.from_tensor_slices([1, 2, 3])
-      iterator_3 = dataset_3.make_one_shot_iterator()
-      iterator_3_handle = iterator_3.string_handle()
-
-    with ops.device("/job:worker/replica:0/task:0/cpu:0"):
-      remote_it = iterator_ops.Iterator.from_string_handle(
-          iterator_3_handle, dataset_3.output_types, dataset_3.output_shapes)
-      get_next_op = remote_it.get_next()
-
-    with session.Session(worker[0].target) as sess:
-      with self.assertRaises(errors.InvalidArgumentError):
-        sess.run(get_next_op)
-
-  def _testRemoteIteratorHelper(self, device0, device1, target):
-    with ops.device(device1):
-      dataset_3 = dataset_ops.Dataset.from_tensor_slices([1, 2, 3])
-      iterator_3 = dataset_3.make_one_shot_iterator()
-      iterator_3_handle = iterator_3.string_handle()
-
-    @function.Defun(dtypes.string)
-    def _remote_fn(h):
-      remote_iterator = iterator_ops.Iterator.from_string_handle(
-          h, dataset_3.output_types, dataset_3.output_shapes)
-      return remote_iterator.get_next()
-
-    with ops.device(device0):
-      target_placeholder = array_ops.placeholder(dtypes.string, shape=[])
-      remote_op = functional_ops.remote_call(
-          args=[iterator_3_handle],
-          Tout=[dtypes.int32],
-          f=_remote_fn,
-          target=target_placeholder)
-
-    with session.Session(target) as sess:
-      elem = sess.run(remote_op, feed_dict={target_placeholder: device1})
-      self.assertEqual(elem, [1])
-      # Fails when target is cpu:0 where the resource is not located.
-      with self.assertRaises(errors.InvalidArgumentError):
-        sess.run(remote_op, feed_dict={target_placeholder: device0})
-      elem = sess.run(iterator_3.get_next())
-      self.assertEqual(elem, [2])
-      elem = sess.run(remote_op, feed_dict={target_placeholder: device1})
-      self.assertEqual(elem, [3])
-      with self.assertRaises(errors.OutOfRangeError):
-        sess.run(remote_op, feed_dict={target_placeholder: device1})
-
-  def testRemoteIteratorUsingRemoteCallOp(self):
-    worker_config = config_pb2.ConfigProto()
-    worker_config.device_count["CPU"] = 2
-    worker, _ = test_util.create_local_cluster(
-        1, 1, worker_config=worker_config)
-
-    self._testRemoteIteratorHelper("/job:worker/replica:0/task:0/cpu:0",
-                                   "/job:worker/replica:0/task:0/cpu:1",
-                                   worker[0].target)
-
-  def testRemoteIteratorUsingRemoteCallOpCrossProcess(self):
-    workers, _ = test_util.create_local_cluster(2, 1)
-
-    self._testRemoteIteratorHelper("/job:worker/replica:0/task:0/cpu:0",
-                                   "/job:worker/replica:0/task:1/cpu:0",
-                                   workers[0].target)
-
-
-if __name__ == "__main__":
-  test.main()
diff --git a/tensorflow/contrib/data/python/kernel_tests/iterator_ops_test.py b/tensorflow/contrib/data/python/kernel_tests/iterator_ops_test.py
deleted file mode 100644
index 9d11865dda..0000000000
--- a/tensorflow/contrib/data/python/kernel_tests/iterator_ops_test.py
+++ /dev/null
@@ -1,625 +0,0 @@
-# Copyright 2017 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.
-# ==============================================================================
-"""Tests for the experimental input pipeline ops."""
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
-
-import os
-import numpy as np
-
-from tensorflow.contrib.data.python.ops import dataset_ops
-from tensorflow.core.protobuf import config_pb2
-from tensorflow.python.client import session
-from tensorflow.python.data.ops import iterator_ops
-from tensorflow.python.data.ops import readers
-from tensorflow.python.framework import constant_op
-from tensorflow.python.framework import dtypes
-from tensorflow.python.framework import errors
-from tensorflow.python.framework import function
-from tensorflow.python.framework import ops
-from tensorflow.python.framework import test_util
-from tensorflow.python.ops import array_ops
-from tensorflow.python.ops import functional_ops
-from tensorflow.python.ops import gen_dataset_ops
-from tensorflow.python.ops import gradients_impl
-from tensorflow.python.ops import io_ops
-from tensorflow.python.ops import math_ops
-from tensorflow.python.ops import parsing_ops
-from tensorflow.python.ops import script_ops
-from tensorflow.python.platform import test
-from tensorflow.python.training import server_lib
-
-
-class IteratorTest(test.TestCase):
-
-  def testAttemptingGradientsRaiseExceptions(self):
-    component = constant_op.constant([1])
-    side = constant_op.constant(0)
-    add = lambda x: x + side
-    dataset = dataset_ops.Dataset.from_tensor_slices(component).map(add)
-    value = dataset.make_one_shot_iterator().get_next()
-    with self.assertRaisesRegexp(LookupError, "No gradient defined"):
-      gradients_impl.gradients(value, component)
-    with self.assertRaisesRegexp(LookupError, "No gradient defined"):
-      gradients_impl.gradients(value, side)
-    with self.assertRaisesRegexp(LookupError, "No gradient defined"):
-      gradients_impl.gradients(value, [component, side])
-
-  def testOneShotIterator(self):
-    components = (np.arange(7),
-                  np.array([[1, 2, 3]]) * np.arange(7)[:, np.newaxis],
-                  np.array(37.0) * np.arange(7))
-
-    def _map_fn(x, y, z):
-      return math_ops.square(x), math_ops.square(y), math_ops.square(z)
-
-    iterator = (dataset_ops.Dataset.from_tensor_slices(components).map(_map_fn)
-                .repeat(14).make_one_shot_iterator())
-    get_next = iterator.get_next()
-
-    self.assertEqual([c.shape[1:] for c in components],
-                     [t.shape for t in get_next])
-
-    with self.test_session() as sess:
-      for _ in range(14):
-        for i in range(7):
-          result = sess.run(get_next)
-          for component, result_component in zip(components, result):
-            self.assertAllEqual(component[i]**2, result_component)
-      with self.assertRaises(errors.OutOfRangeError):
-        sess.run(get_next)
-
-  def testOneShotIteratorCaptureByValue(self):
-    components = (np.arange(7),
-                  np.array([[1, 2, 3]]) * np.arange(7)[:, np.newaxis],
-                  np.array(37.0) * np.arange(7))
-    tensor_components = tuple([ops.convert_to_tensor(c) for c in components])
-
-    def _map_fn(x, y, z):
-      return math_ops.square(x), math_ops.square(y), math_ops.square(z)
-
-    iterator = (dataset_ops.Dataset.from_tensor_slices(tensor_components)
-                .map(_map_fn).repeat(14).make_one_shot_iterator())
-    get_next = iterator.get_next()
-
-    self.assertEqual([c.shape[1:] for c in components],
-                     [t.shape for t in get_next])
-
-    with self.test_session() as sess:
-      for _ in range(14):
-        for i in range(7):
-          result = sess.run(get_next)
-          for component, result_component in zip(components, result):
-            self.assertAllEqual(component[i]**2, result_component)
-      with self.assertRaises(errors.OutOfRangeError):
-        sess.run(get_next)
-
-  def testOneShotIteratorInsideContainer(self):
-    components = (np.arange(7),
-                  np.array([[1, 2, 3]]) * np.arange(7)[:, np.newaxis],
-                  np.array(37.0) * np.arange(7))
-
-    def within_container():
-      def _map_fn(x, y, z):
-        return math_ops.square(x), math_ops.square(y), math_ops.square(z)
-      iterator = (dataset_ops.Dataset.from_tensor_slices(components)
-                  .map(_map_fn).repeat(14).make_one_shot_iterator())
-      return iterator.get_next()
-
-    server = server_lib.Server.create_local_server()
-
-    # Create two iterators within unique containers, and run them to
-    # make sure that the resources aren't shared.
-    #
-    # The test below would fail if cname were the same across both
-    # sessions.
-    for i in range(2):
-      with session.Session(server.target) as sess:
-        cname = "iteration%d" % i
-        with ops.container(cname):
-          get_next = within_container()
-
-        for _ in range(14):
-          for i in range(7):
-            result = sess.run(get_next)
-            for component, result_component in zip(components, result):
-              self.assertAllEqual(component[i]**2, result_component)
-        with self.assertRaises(errors.OutOfRangeError):
-          sess.run(get_next)
-
-  def testOneShotIteratorNonBlocking(self):
-    dataset = dataset_ops.Dataset.from_tensors([1, 2, 3]).map(lambda x: x * x)
-    iterator = dataset.make_one_shot_iterator()
-    next_element = iterator.get_next()
-
-    # Create a session with a single thread to ensure that the
-    # one-shot iterator initializer does not deadlock.
-    config = config_pb2.ConfigProto(inter_op_parallelism_threads=1,
-                                    use_per_session_threads=True)
-    with session.Session(config=config) as sess:
-      self.assertAllEqual([1, 4, 9], sess.run(next_element))
-      with self.assertRaises(errors.OutOfRangeError):
-        sess.run(next_element)
-
-    # Test with multiple threads invoking the one-shot iterator concurrently.
-    with session.Session(config=config) as sess:
-      results = []
-      def consumer_thread():
-        try:
-          results.append(sess.run(next_element))
-        except errors.OutOfRangeError:
-          results.append(None)
-
-      num_threads = 8
-      threads = [
-          self.checkedThread(consumer_thread) for _ in range(num_threads)]
-      for t in threads:
-        t.start()
-      for t in threads:
-        t.join()
-
-      self.assertEqual(num_threads, len(results))
-      self.assertEqual(num_threads - 1,
-                       len([None for r in results if r is None]))
-      self.assertAllEqual([[1, 4, 9]], [r for r in results if r is not None])
-
-  def testOneShotIteratorInitializerFails(self):
-    # Define a dataset whose initialization will always fail.
-    dataset = dataset_ops.Dataset.from_tensors(
-        array_ops.check_numerics(
-            constant_op.constant(1.0) / constant_op.constant(0.0), "oops"))
-    iterator = dataset.make_one_shot_iterator()
-    next_element = iterator.get_next()
-
-    with self.test_session() as sess:
-      with self.assertRaisesRegexp(errors.InvalidArgumentError, "oops"):
-        sess.run(next_element)
-
-      # Test that subsequent attempts to use the iterator also fail.
-      with self.assertRaisesRegexp(errors.InvalidArgumentError, "oops"):
-        sess.run(next_element)
-
-    with self.test_session() as sess:
-      def consumer_thread():
-        with self.assertRaisesRegexp(errors.InvalidArgumentError, "oops"):
-          sess.run(next_element)
-
-      num_threads = 8
-      threads = [
-          self.checkedThread(consumer_thread) for _ in range(num_threads)]
-      for t in threads:
-        t.start()
-      for t in threads:
-        t.join()
-
-  def testSimpleSharedResource(self):
-    components = (
-        np.array(1, dtype=np.int64),
-        np.array([1, 2, 3], dtype=np.int64),
-        np.array(37.0, dtype=np.float64)
-    )
-
-    server = server_lib.Server.create_local_server()
-
-    # Create two non-overlapping sessions that share the same iterator
-    # resource on the same server, and verify that an action of the
-    # first session (initializing the iterator) is visible in the
-    # second session.
-    with ops.Graph().as_default():
-      iterator = (dataset_ops.Dataset.from_tensors(components)
-                  .map(lambda x, y, z: (x, y, z)).make_initializable_iterator(
-                      shared_name="shared_iterator"))
-      init_op = iterator.initializer
-      get_next = iterator.get_next()
-
-      with session.Session(server.target) as sess:
-        sess.run(init_op)
-        results = sess.run(get_next)
-        for component, result_component in zip(components, results):
-          self.assertAllEqual(component, result_component)
-        with self.assertRaises(errors.OutOfRangeError):
-          sess.run(get_next)
-
-        # Re-initialize the iterator in the first session.
-        sess.run(init_op)
-
-    with ops.Graph().as_default():
-      # Re-define the iterator manually, without defining any of the
-      # functions in this graph, to ensure that we are not
-      # accidentally redefining functions with the same names in the
-      # new graph.
-      iterator = iterator_ops.Iterator.from_structure(
-          shared_name="shared_iterator",
-          output_types=(dtypes.int64, dtypes.int64, dtypes.float64),
-          output_shapes=([], [3], []))
-      get_next = iterator.get_next()
-
-      with session.Session(server.target) as sess:
-        # Use the iterator without re-initializing in the second session.
-        results = sess.run(get_next)
-        for component, result_component in zip(components, results):
-          self.assertAllEqual(component, result_component)
-        with self.assertRaises(errors.OutOfRangeError):
-          sess.run(get_next)
-
-  def testNotInitializedError(self):
-    components = (np.array(1), np.array([1, 2, 3]), np.array(37.0))
-    iterator = (dataset_ops.Dataset.from_tensors(components)
-                .make_initializable_iterator())
-    get_next = iterator.get_next()
-
-    with self.test_session() as sess:
-      with self.assertRaisesRegexp(errors.FailedPreconditionError,
-                                   "iterator has not been initialized"):
-        sess.run(get_next)
-
-  def testReinitializableIterator(self):
-    dataset_3 = dataset_ops.Dataset.from_tensors(
-        constant_op.constant([1, 2, 3]))
-    dataset_4 = dataset_ops.Dataset.from_tensors(
-        constant_op.constant([4, 5, 6, 7]))
-    iterator = iterator_ops.Iterator.from_structure(dataset_3.output_types,
-                                                    [None])
-
-    dataset_3_init_op = iterator.make_initializer(dataset_3)
-    dataset_4_init_op = iterator.make_initializer(dataset_4)
-    get_next = iterator.get_next()
-
-    self.assertEqual(dataset_3.output_types, iterator.output_types)
-    self.assertEqual(dataset_4.output_types, iterator.output_types)
-    self.assertEqual([None], iterator.output_shapes.as_list())
-
-    with self.test_session() as sess:
-      # The iterator is initially uninitialized.
-      with self.assertRaises(errors.FailedPreconditionError):
-        sess.run(get_next)
-
-      # Initialize with one dataset.
-      sess.run(dataset_3_init_op)
-      self.assertAllEqual([1, 2, 3], sess.run(get_next))
-      with self.assertRaises(errors.OutOfRangeError):
-        sess.run(get_next)
-
-      # Initialize with a different dataset.
-      sess.run(dataset_4_init_op)
-      self.assertAllEqual([4, 5, 6, 7], sess.run(get_next))
-      with self.assertRaises(errors.OutOfRangeError):
-        sess.run(get_next)
-
-      # Reinitialize with the first dataset.
-      sess.run(dataset_3_init_op)
-      self.assertAllEqual([1, 2, 3], sess.run(get_next))
-      with self.assertRaises(errors.OutOfRangeError):
-        sess.run(get_next)
-
-  def testReinitializableIteratorStaticErrors(self):
-    # Non-matching structure for types and shapes.
-    with self.assertRaises(TypeError):
-      iterator = iterator_ops.Iterator.from_structure((dtypes.int64,
-                                                       dtypes.float64), [None])
-
-    # Test validation of dataset argument.
-    iterator = iterator_ops.Iterator.from_structure((dtypes.int64,
-                                                     dtypes.float64))
-
-    # Incompatible structure.
-    with self.assertRaises(ValueError):
-      iterator.make_initializer(
-          dataset_ops.Dataset.from_tensors(((constant_op.constant(
-              [1, 2, 3], dtype=dtypes.int64),), (constant_op.constant(
-                  [4., 5., 6., 7.], dtype=dtypes.float64),))))
-
-    # Incompatible types.
-    with self.assertRaises(TypeError):
-      iterator.make_initializer(
-          dataset_ops.Dataset.from_tensors((constant_op.constant(
-              [1, 2, 3], dtype=dtypes.int32), constant_op.constant(
-                  [4., 5., 6., 7.], dtype=dtypes.float32))))
-
-    # Incompatible shapes.
-    iterator = iterator_ops.Iterator.from_structure(
-        (dtypes.int64, dtypes.float64), ([None], []))
-    with self.assertRaises(TypeError):
-      iterator.make_initializer(
-          dataset_ops.Dataset.from_tensors((constant_op.constant(
-              [1, 2, 3], dtype=dtypes.int64), constant_op.constant(
-                  [4., 5., 6., 7.], dtype=dtypes.float64))))
-
-  def testIteratorStringHandle(self):
-    dataset_3 = dataset_ops.Dataset.from_tensor_slices([1, 2, 3])
-    dataset_4 = dataset_ops.Dataset.from_tensor_slices([10, 20, 30, 40])
-
-    iterator_3 = dataset_3.make_one_shot_iterator()
-    iterator_4 = dataset_4.make_one_shot_iterator()
-
-    handle_placeholder = array_ops.placeholder(dtypes.string, shape=[])
-    feedable_iterator = iterator_ops.Iterator.from_string_handle(
-        handle_placeholder, dataset_3.output_types, dataset_3.output_shapes)
-    next_element = feedable_iterator.get_next()
-
-    self.assertEqual(dataset_3.output_types, feedable_iterator.output_types)
-    self.assertEqual(dataset_4.output_types, feedable_iterator.output_types)
-    self.assertEqual([], feedable_iterator.output_shapes)
-
-    with self.test_session() as sess:
-      iterator_3_handle = sess.run(iterator_3.string_handle())
-      iterator_4_handle = sess.run(iterator_4.string_handle())
-
-      self.assertEqual(
-          10, sess.run(next_element,
-                       feed_dict={handle_placeholder: iterator_4_handle}))
-      self.assertEqual(
-          1, sess.run(next_element,
-                      feed_dict={handle_placeholder: iterator_3_handle}))
-      self.assertEqual(
-          20, sess.run(next_element,
-                       feed_dict={handle_placeholder: iterator_4_handle}))
-      self.assertEqual(
-          2, sess.run(next_element,
-                      feed_dict={handle_placeholder: iterator_3_handle}))
-      self.assertEqual(
-          30, sess.run(next_element,
-                       feed_dict={handle_placeholder: iterator_4_handle}))
-      self.assertEqual(
-          3, sess.run(next_element,
-                      feed_dict={handle_placeholder: iterator_3_handle}))
-      self.assertEqual(
-          40, sess.run(next_element,
-                       feed_dict={handle_placeholder: iterator_4_handle}))
-      with self.assertRaises(errors.OutOfRangeError):
-        sess.run(next_element,
-                 feed_dict={handle_placeholder: iterator_3_handle})
-      with self.assertRaises(errors.OutOfRangeError):
-        sess.run(next_element,
-                 feed_dict={handle_placeholder: iterator_4_handle})
-
-  def testIteratorStringHandleError(self):
-    dataset_int_scalar = (dataset_ops.Dataset.from_tensor_slices([1, 2,
-                                                                  3]).repeat())
-    dataset_float_vector = (dataset_ops.Dataset.from_tensors([1.0, 2.0, 3.0]))
-
-    handle_placeholder = array_ops.placeholder(dtypes.string, shape=[])
-
-    feedable_int_scalar = iterator_ops.Iterator.from_string_handle(
-        handle_placeholder, dtypes.int32, [])
-    feedable_int_vector = iterator_ops.Iterator.from_string_handle(
-        handle_placeholder, dtypes.int32, [None])
-    feedable_int_any = iterator_ops.Iterator.from_string_handle(
-        handle_placeholder, dtypes.int32)
-
-    with self.test_session() as sess:
-      handle_int_scalar = sess.run(
-          dataset_int_scalar.make_one_shot_iterator().string_handle())
-      handle_float_vector = sess.run(
-          dataset_float_vector.make_one_shot_iterator().string_handle())
-
-      self.assertEqual(1,
-                       sess.run(
-                           feedable_int_scalar.get_next(),
-                           feed_dict={handle_placeholder: handle_int_scalar}))
-
-      self.assertEqual(2,
-                       sess.run(
-                           feedable_int_any.get_next(),
-                           feed_dict={handle_placeholder: handle_int_scalar}))
-
-      with self.assertRaises(errors.InvalidArgumentError):
-        print(sess.run(
-            feedable_int_vector.get_next(),
-            feed_dict={handle_placeholder: handle_int_scalar}))
-
-      with self.assertRaises(errors.InvalidArgumentError):
-        print(sess.run(
-            feedable_int_vector.get_next(),
-            feed_dict={handle_placeholder: handle_float_vector}))
-
-  def testRemoteIteratorUsingRemoteCallOpDirectSession(self):
-    worker_config = config_pb2.ConfigProto()
-    worker_config.device_count["CPU"] = 3
-
-    with ops.device("/job:localhost/replica:0/task:0/cpu:1"):
-      dataset_3 = dataset_ops.Dataset.from_tensor_slices([1, 2, 3])
-      iterator_3 = dataset_3.make_one_shot_iterator()
-      iterator_3_handle = iterator_3.string_handle()
-
-    @function.Defun(dtypes.string)
-    def _remote_fn(h):
-      remote_iterator = iterator_ops.Iterator.from_string_handle(
-          h, dataset_3.output_types, dataset_3.output_shapes)
-      return remote_iterator.get_next()
-
-    with ops.device("/job:localhost/replica:0/task:0/cpu:0"):
-      target_placeholder = array_ops.placeholder(dtypes.string, shape=[])
-      remote_op = functional_ops.remote_call(
-          args=[iterator_3_handle],
-          Tout=[dtypes.int32],
-          f=_remote_fn,
-          target=target_placeholder)
-
-    with self.test_session(config=worker_config) as sess:
-      elem = sess.run(
-          remote_op,
-          feed_dict={
-              target_placeholder: "/job:localhost/replica:0/task:0/cpu:1"
-          })
-      self.assertEqual(elem, [1])
-      # Fails when target is cpu:2 where the resource is not located.
-      with self.assertRaises(errors.InvalidArgumentError):
-        sess.run(
-            remote_op,
-            feed_dict={
-                target_placeholder: "/job:localhost/replica:0/task:0/cpu:2"
-            })
-      elem = sess.run(
-          remote_op,
-          feed_dict={
-              target_placeholder: "/job:localhost/replica:0/task:0/cpu:1"
-          })
-      self.assertEqual(elem, [2])
-      elem = sess.run(
-          remote_op,
-          feed_dict={
-              target_placeholder: "/job:localhost/replica:0/task:0/cpu:1"
-          })
-      self.assertEqual(elem, [3])
-      with self.assertRaises(errors.OutOfRangeError):
-        sess.run(
-            remote_op,
-            feed_dict={
-                target_placeholder: "/job:localhost/replica:0/task:0/cpu:1"
-            })
-
-  def testRemoteIteratorUsingRemoteCallOpDirectSessionGPUCPU(self):
-    if not test_util.is_gpu_available():
-      self.skipTest("No GPU available")
-
-    with ops.device("/job:localhost/replica:0/task:0/cpu:0"):
-      dataset_3 = dataset_ops.Dataset.from_tensor_slices([1, 2, 3])
-      iterator_3 = dataset_3.make_one_shot_iterator()
-      iterator_3_handle = iterator_3.string_handle()
-
-    def _encode_raw(byte_array):
-      return bytes(bytearray(byte_array))
-
-    @function.Defun(dtypes.uint8)
-    def _remote_fn(h):
-      handle = script_ops.py_func(_encode_raw, [h], dtypes.string)
-      remote_iterator = iterator_ops.Iterator.from_string_handle(
-          handle, dataset_3.output_types, dataset_3.output_shapes)
-      return remote_iterator.get_next()
-
-    with ops.device("/job:localhost/replica:0/task:0/device:GPU:0"):
-      target_placeholder = array_ops.placeholder(dtypes.string, shape=[])
-      iterator_3_handle_uint8 = parsing_ops.decode_raw(
-          bytes=iterator_3_handle, out_type=dtypes.uint8)
-      remote_op = functional_ops.remote_call(
-          args=[iterator_3_handle_uint8],
-          Tout=[dtypes.int32],
-          f=_remote_fn,
-          target=target_placeholder)
-
-    with self.test_session() as sess:
-      elem = sess.run(
-          remote_op,
-          feed_dict={
-              target_placeholder: "/job:localhost/replica:0/task:0/cpu:0"
-          })
-      self.assertEqual(elem, [1])
-      elem = sess.run(
-          remote_op,
-          feed_dict={
-              target_placeholder: "/job:localhost/replica:0/task:0/cpu:0"
-          })
-      self.assertEqual(elem, [2])
-      elem = sess.run(
-          remote_op,
-          feed_dict={
-              target_placeholder: "/job:localhost/replica:0/task:0/cpu:0"
-          })
-      self.assertEqual(elem, [3])
-      with self.assertRaises(errors.OutOfRangeError):
-        sess.run(
-            remote_op,
-            feed_dict={
-                target_placeholder: "/job:localhost/replica:0/task:0/cpu:0"
-            })
-
-  def testIncorrectIteratorRestore(self):
-
-    def _path():
-      return os.path.join(self.get_temp_dir(), "iterator")
-
-    def _save_op(iterator_resource):
-      iterator_state_variant = gen_dataset_ops.serialize_iterator(
-          iterator_resource)
-      save_op = io_ops.write_file(
-          _path(), parsing_ops.serialize_tensor(iterator_state_variant))
-      return save_op
-
-    def _restore_op(iterator_resource):
-      iterator_state_variant = parsing_ops.parse_tensor(
-          io_ops.read_file(_path()), dtypes.variant)
-      restore_op = gen_dataset_ops.deserialize_iterator(iterator_resource,
-                                                        iterator_state_variant)
-      return restore_op
-
-    def _build_range_dataset_graph():
-      start = 1
-      stop = 10
-      iterator = dataset_ops.Dataset.range(start,
-                                           stop).make_initializable_iterator()
-      init_op = iterator.initializer
-      get_next = iterator.get_next()
-      save_op = _save_op(iterator._iterator_resource)
-      restore_op = _restore_op(iterator._iterator_resource)
-      return init_op, get_next, save_op, restore_op
-
-    def _build_reader_dataset_graph():
-      filenames = ["test"]  # Does not exist but we don't care in this test.
-      iterator = readers.FixedLengthRecordDataset(
-          filenames, 1, 0, 0).make_initializable_iterator()
-      init_op = iterator.initializer
-      get_next_op = iterator.get_next()
-      save_op = _save_op(iterator._iterator_resource)
-      restore_op = _restore_op(iterator._iterator_resource)
-      return init_op, get_next_op, save_op, restore_op
-
-    # Saving iterator for RangeDataset graph.
-    with ops.Graph().as_default() as g:
-      init_op, _, save_op, _ = _build_range_dataset_graph()
-      with self.test_session(graph=g) as sess:
-        sess.run(init_op)
-        sess.run(save_op)
-
-    # Attempt to restore the saved iterator into an IteratorResource of
-    # incompatible type. An iterator of RangeDataset has output type int64,
-    # while an iterator of FixedLengthRecordDataset has output type string.
-    # So an InvalidArgumentError should be raised by
-    # IteratorResource::set_iterator.
-    with ops.Graph().as_default() as g:
-      _, _, _, restore_op = _build_reader_dataset_graph()
-      with self.test_session(graph=g) as sess:
-        with self.assertRaises(errors.InvalidArgumentError):
-          sess.run(restore_op)
-
-  def testToSingleElement(self):
-    skip_value = array_ops.placeholder(dtypes.int64, shape=[])
-    take_value = array_ops.placeholder_with_default(
-        constant_op.constant(1, dtype=dtypes.int64), shape=[])
-
-    dataset = (dataset_ops.Dataset.range(100)
-               .skip(skip_value)
-               .map(lambda x: x * x)
-               .take(take_value))
-
-    element = dataset_ops.get_single_element(dataset)
-
-    with self.test_session() as sess:
-      self.assertEqual(0, sess.run(element, feed_dict={skip_value: 0}))
-      self.assertEqual(25, sess.run(element, feed_dict={skip_value: 5}))
-      self.assertEqual(100, sess.run(element, feed_dict={skip_value: 10}))
-
-      with self.assertRaisesRegexp(errors.InvalidArgumentError,
-                                   "Dataset was empty."):
-        sess.run(element, feed_dict={skip_value: 100})
-
-      with self.assertRaisesRegexp(errors.InvalidArgumentError,
-                                   "Dataset had more than one element."):
-        sess.run(element, feed_dict={skip_value: 0, take_value: 2})
-
-
-if __name__ == "__main__":
-  test.main()