Rename SyncReplicasOptimizerV2 to SyncReplicasOptimizer

Change: 141904790

7 files changed, 29 insertions, 29 deletions

diff --git a/tensorflow/contrib/slim/python/slim/learning.py b/tensorflow/contrib/slim/python/slim/learning.py
index ca131cfb7c..fc2a6d0fe6 100644
--- a/tensorflow/contrib/slim/python/slim/learning.py
+++ b/tensorflow/contrib/slim/python/slim/learning.py
@@ -699,7 +699,7 @@ def train(train_op,
             data_flow_ops.initialize_all_tables())
 
       if sync_optimizer is not None and isinstance(
-          sync_optimizer, sync_replicas_optimizer.SyncReplicasOptimizerV2):
+          sync_optimizer, sync_replicas_optimizer.SyncReplicasOptimizer):
         with ops.control_dependencies([local_init_op] if local_init_op is
                                       not None else []):
           if is_chief:
@@ -720,11 +720,9 @@ def train(train_op,
 
     if is_chief and sync_optimizer is not None:
       if not isinstance(sync_optimizer,
-                        (sync_replicas_optimizer.SyncReplicasOptimizer,
-                         sync_replicas_optimizer.SyncReplicasOptimizerV2)):
+                        (sync_replicas_optimizer.SyncReplicasOptimizer)):
         raise ValueError(
-            '`sync_optimizer` must be a tf.train.SyncReplicasOptimizer or '
-            'tf.train.SyncReplicasOptimizerV2.')
+            '`sync_optimizer` must be a tf.train.SyncReplicasOptimizer.')
 
       # Need to create these BEFORE the supervisor finalizes the graph:
       init_tokens_op = sync_optimizer.get_init_tokens_op()
diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard9/tf.train.SyncReplicasOptimizerV2.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard9/tf.train.SyncReplicasOptimizerV2.md
index 10660f6bcf..d8ff888955 100644
--- a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard9/tf.train.SyncReplicasOptimizerV2.md
+++ b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard9/tf.train.SyncReplicasOptimizerV2.md
@@ -58,8 +58,8 @@ opt = GradientDescentOptimizer(learning_rate=0.1)
 # Note that if you want to have 2 backup replicas, you can change
 # total_num_replicas=52 and make sure this number matches how many physical
 # replicas you started in your job.
-opt = tf.SyncReplicasOptimizerV2(opt, replicas_to_aggregate=50,
-                                 total_num_replicas=50)
+opt = tf.SyncReplicasOptimizer(opt, replicas_to_aggregate=50,
+                               total_num_replicas=50)
 
 # Some models have startup_delays to help stabilize the model but when using
 # sync_replicas training, set it to 0.
@@ -107,7 +107,7 @@ if is_chief and FLAGS.sync_replicas:
 
 - - -
 
-#### `tf.train.SyncReplicasOptimizerV2.__init__(opt, replicas_to_aggregate, total_num_replicas=None, variable_averages=None, variables_to_average=None, use_locking=False, name='sync_replicas')` {#SyncReplicasOptimizerV2.__init__}
+#### `tf.train.SyncReplicasOptimizer.__init__(opt, replicas_to_aggregate, total_num_replicas=None, variable_averages=None, variables_to_average=None, use_locking=False, name='sync_replicas')` {#SyncReplicasOptimizer.__init__}
 
 Construct a sync_replicas optimizer.
 
@@ -135,7 +135,7 @@ Construct a sync_replicas optimizer.
 
 - - -
 
-#### `tf.train.SyncReplicasOptimizerV2.compute_gradients(*args, **kwargs)` {#SyncReplicasOptimizerV2.compute_gradients}
+#### `tf.train.SyncReplicasOptimizer.compute_gradients(*args, **kwargs)` {#SyncReplicasOptimizer.compute_gradients}
 
 Compute gradients of "loss" for the variables in "var_list".
 
@@ -158,7 +158,7 @@ gradients can hurt the gradients from other replicas.
 
 - - -
 
-#### `tf.train.SyncReplicasOptimizerV2.apply_gradients(grads_and_vars, global_step=None, name=None)` {#SyncReplicasOptimizerV2.apply_gradients}
+#### `tf.train.SyncReplicasOptimizer.apply_gradients(grads_and_vars, global_step=None, name=None)` {#SyncReplicasOptimizer.apply_gradients}
 
 Apply gradients to variables.
 
@@ -191,7 +191,7 @@ apply_gradients() from the real optimizer.
 
 - - -
 
-#### `tf.train.SyncReplicasOptimizerV2.get_chief_queue_runner()` {#SyncReplicasOptimizerV2.get_chief_queue_runner}
+#### `tf.train.SyncReplicasOptimizer.get_chief_queue_runner()` {#SyncReplicasOptimizer.get_chief_queue_runner}
 
 Returns the QueueRunner for the chief to execute.
 
@@ -213,7 +213,7 @@ actually generates this queuerunner.
 
 - - -
 
-#### `tf.train.SyncReplicasOptimizerV2.get_init_tokens_op(num_tokens=-1)` {#SyncReplicasOptimizerV2.get_init_tokens_op}
+#### `tf.train.SyncReplicasOptimizer.get_init_tokens_op(num_tokens=-1)` {#SyncReplicasOptimizer.get_init_tokens_op}
 
 Returns the op to fill the sync_token_queue with the tokens.
 
@@ -244,7 +244,7 @@ variable update. Make sure:
 #### Other Methods
 - - -
 
-#### `tf.train.SyncReplicasOptimizerV2.get_slot(*args, **kwargs)` {#SyncReplicasOptimizerV2.get_slot}
+#### `tf.train.SyncReplicasOptimizer.get_slot(*args, **kwargs)` {#SyncReplicasOptimizer.get_slot}
 
 Return a slot named "name" created for "var" by the Optimizer.
 
@@ -263,7 +263,7 @@ This simply wraps the get_slot() from the actual optimizer.
 
 - - -
 
-#### `tf.train.SyncReplicasOptimizerV2.get_slot_names(*args, **kwargs)` {#SyncReplicasOptimizerV2.get_slot_names}
+#### `tf.train.SyncReplicasOptimizer.get_slot_names(*args, **kwargs)` {#SyncReplicasOptimizer.get_slot_names}
 
 Return a list of the names of slots created by the `Optimizer`.
 
diff --git a/tensorflow/g3doc/api_docs/python/index.md b/tensorflow/g3doc/api_docs/python/index.md
index a474460723..5065da8be5 100644
--- a/tensorflow/g3doc/api_docs/python/index.md
+++ b/tensorflow/g3doc/api_docs/python/index.md
@@ -660,7 +660,7 @@
   * [`summary_iterator`](../../api_docs/python/train.md#summary_iterator)
   * [`SummarySaverHook`](../../api_docs/python/train.md#SummarySaverHook)
   * [`Supervisor`](../../api_docs/python/train.md#Supervisor)
-  * [`SyncReplicasOptimizerV2`](../../api_docs/python/train.md#SyncReplicasOptimizerV2)
+  * [`SyncReplicasOptimizer`](../../api_docs/python/train.md#SyncReplicasOptimizer)
   * [`WorkerSessionCreator`](../../api_docs/python/train.md#WorkerSessionCreator)
   * [`write_graph`](../../api_docs/python/train.md#write_graph)
 
diff --git a/tensorflow/g3doc/api_docs/python/train.md b/tensorflow/g3doc/api_docs/python/train.md
index 88ae6e3f26..19e6116e08 100644
--- a/tensorflow/g3doc/api_docs/python/train.md
+++ b/tensorflow/g3doc/api_docs/python/train.md
@@ -5350,7 +5350,7 @@ Called when the thread stops.
 ## Other Functions and Classes
 - - -
 
-### `class tf.train.SyncReplicasOptimizerV2` {#SyncReplicasOptimizerV2}
+### `class tf.train.SyncReplicasOptimizer` {#SyncReplicasOptimizer}
 
 Class to synchronize, aggregate gradients and pass them to the optimizer.
 
@@ -5412,8 +5412,8 @@ opt = GradientDescentOptimizer(learning_rate=0.1)
 # Note that if you want to have 2 backup replicas, you can change
 # total_num_replicas=52 and make sure this number matches how many physical
 # replicas you started in your job.
-opt = tf.SyncReplicasOptimizerV2(opt, replicas_to_aggregate=50,
-                                 total_num_replicas=50)
+opt = tf.SyncReplicasOptimizer(opt, replicas_to_aggregate=50,
+                               total_num_replicas=50)
 
 # Some models have startup_delays to help stabilize the model but when using
 # sync_replicas training, set it to 0.
@@ -5461,7 +5461,7 @@ if is_chief and FLAGS.sync_replicas:
 
 - - -
 
-#### `tf.train.SyncReplicasOptimizerV2.__init__(opt, replicas_to_aggregate, total_num_replicas=None, variable_averages=None, variables_to_average=None, use_locking=False, name='sync_replicas')` {#SyncReplicasOptimizerV2.__init__}
+#### `tf.train.SyncReplicasOptimizer.__init__(opt, replicas_to_aggregate, total_num_replicas=None, variable_averages=None, variables_to_average=None, use_locking=False, name='sync_replicas')` {#SyncReplicasOptimizer.__init__}
 
 Construct a sync_replicas optimizer.
 
@@ -5489,7 +5489,7 @@ Construct a sync_replicas optimizer.
 
 - - -
 
-#### `tf.train.SyncReplicasOptimizerV2.compute_gradients(*args, **kwargs)` {#SyncReplicasOptimizerV2.compute_gradients}
+#### `tf.train.SyncReplicasOptimizer.compute_gradients(*args, **kwargs)` {#SyncReplicasOptimizer.compute_gradients}
 
 Compute gradients of "loss" for the variables in "var_list".
 
@@ -5512,7 +5512,7 @@ gradients can hurt the gradients from other replicas.
 
 - - -
 
-#### `tf.train.SyncReplicasOptimizerV2.apply_gradients(grads_and_vars, global_step=None, name=None)` {#SyncReplicasOptimizerV2.apply_gradients}
+#### `tf.train.SyncReplicasOptimizer.apply_gradients(grads_and_vars, global_step=None, name=None)` {#SyncReplicasOptimizer.apply_gradients}
 
 Apply gradients to variables.
 
@@ -5545,7 +5545,7 @@ apply_gradients() from the real optimizer.
 
 - - -
 
-#### `tf.train.SyncReplicasOptimizerV2.get_chief_queue_runner()` {#SyncReplicasOptimizerV2.get_chief_queue_runner}
+#### `tf.train.SyncReplicasOptimizer.get_chief_queue_runner()` {#SyncReplicasOptimizer.get_chief_queue_runner}
 
 Returns the QueueRunner for the chief to execute.
 
@@ -5567,7 +5567,7 @@ actually generates this queuerunner.
 
 - - -
 
-#### `tf.train.SyncReplicasOptimizerV2.get_init_tokens_op(num_tokens=-1)` {#SyncReplicasOptimizerV2.get_init_tokens_op}
+#### `tf.train.SyncReplicasOptimizer.get_init_tokens_op(num_tokens=-1)` {#SyncReplicasOptimizer.get_init_tokens_op}
 
 Returns the op to fill the sync_token_queue with the tokens.
 
@@ -5598,7 +5598,7 @@ variable update. Make sure:
 #### Other Methods
 - - -
 
-#### `tf.train.SyncReplicasOptimizerV2.get_slot(*args, **kwargs)` {#SyncReplicasOptimizerV2.get_slot}
+#### `tf.train.SyncReplicasOptimizer.get_slot(*args, **kwargs)` {#SyncReplicasOptimizer.get_slot}
 
 Return a slot named "name" created for "var" by the Optimizer.
 
@@ -5617,7 +5617,7 @@ This simply wraps the get_slot() from the actual optimizer.
 
 - - -
 
-#### `tf.train.SyncReplicasOptimizerV2.get_slot_names(*args, **kwargs)` {#SyncReplicasOptimizerV2.get_slot_names}
+#### `tf.train.SyncReplicasOptimizer.get_slot_names(*args, **kwargs)` {#SyncReplicasOptimizer.get_slot_names}
 
 Return a list of the names of slots created by the `Optimizer`.
 
diff --git a/tensorflow/python/training/sync_replicas_optimizer_test.py b/tensorflow/python/training/sync_replicas_optimizer_test.py
index b9e612bb71..4ffe3a3ee9 100644
--- a/tensorflow/python/training/sync_replicas_optimizer_test.py
+++ b/tensorflow/python/training/sync_replicas_optimizer_test.py
@@ -70,7 +70,7 @@ def get_workers(num_workers, replicas_to_aggregate, workers):
             tf.constant([1]),
             tf.constant([2, 1]))
         sgd_opt = tf.train.GradientDescentOptimizer(2.0)
-        sync_rep_opt = tf.train.SyncReplicasOptimizerV2(
+        sync_rep_opt = tf.train.SyncReplicasOptimizer(
             sgd_opt, replicas_to_aggregate=replicas_to_aggregate,
             total_num_replicas=num_workers)
         train_op = [sync_rep_opt.apply_gradients(
@@ -111,7 +111,7 @@ def get_workers(num_workers, replicas_to_aggregate, workers):
   return sessions, graphs, train_ops
 
 
-class SyncReplicasOptimizerV2Test(tf.test.TestCase):
+class SyncReplicasOptimizerTest(tf.test.TestCase):
 
   def _run(self, train_op, sess):
     sess.run(train_op)
diff --git a/tensorflow/python/training/training.py b/tensorflow/python/training/training.py
index b84d248fd3..63063ab361 100644
--- a/tensorflow/python/training/training.py
+++ b/tensorflow/python/training/training.py
@@ -167,7 +167,9 @@ from tensorflow.python.training.optimizer import Optimizer
 from tensorflow.python.training.rmsprop import RMSPropOptimizer
 from tensorflow.python.training.gradient_descent import GradientDescentOptimizer
 from tensorflow.python.training.proximal_gradient_descent import ProximalGradientDescentOptimizer
+# TODO(xpan): Remove SyncReplicasOptimizerV2 once all users are migrated.
 from tensorflow.python.training.sync_replicas_optimizer import SyncReplicasOptimizerV2
+from tensorflow.python.training.sync_replicas_optimizer import SyncReplicasOptimizerV2 as SyncReplicasOptimizer
 
 # Utility classes for training.
 from tensorflow.python.training.coordinator import Coordinator
@@ -255,7 +257,7 @@ _allowed_symbols = [
     # TODO(drpng): document these. The reference in howtos/distributed does
     # not link.
     "SyncReplicasOptimizerV2",
-
+    "SyncReplicasOptimizer",
     # Protobufs:
     "BytesList",          # from example_pb2.
     "ClusterDef",
diff --git a/tensorflow/tools/dist_test/python/mnist_replica.py b/tensorflow/tools/dist_test/python/mnist_replica.py
index fb51705fe0..7e68258b0a 100644
--- a/tensorflow/tools/dist_test/python/mnist_replica.py
+++ b/tensorflow/tools/dist_test/python/mnist_replica.py
@@ -177,7 +177,7 @@ def main(unused_argv):
       else:
         replicas_to_aggregate = FLAGS.replicas_to_aggregate
 
-      opt = tf.train.SyncReplicasOptimizerV2(
+      opt = tf.train.SyncReplicasOptimizer(
           opt,
           replicas_to_aggregate=replicas_to_aggregate,
           total_num_replicas=num_workers,