Expose tf.distribute.MirroredStrategy.

RELNOTES:
tf.distribute.MirroredStrategy is now part of core TensorFlow. It is an updated version of tf.contrib.distribute.MirroredStrategy. It can be used for distributing training to multiple GPUs in Keras, Estimator, or directly.
It is an implementation of the tf.distribute.Strategy API, which is also now in core TensorFlow. This API has been updated based on the public design review https://github.com/tensorflow/community/blob/master/rfcs/20181016-replicator.md.
Other distribution strategies will be moved to core TF in future releases.
PiperOrigin-RevId: 224097441

tensorflow/python/BUILD

@@ -145,6 +145,7 @@ py_library(
         "//tensorflow/lite/python:lite",
         "//tensorflow/python/compat",
         "//tensorflow/python/data",
+        "//tensorflow/python/distribute",
         "//tensorflow/python/distribute:estimator_training",
         "//tensorflow/python/eager:def_function",
         "//tensorflow/python/feature_column:feature_column_py",

tensorflow/python/__init__.py

@@ -78,6 +78,7 @@ from tensorflow.python.ops import initializers_ns as initializers
 
 # Bring in subpackages.
 from tensorflow.python import data
+from tensorflow.python import distribute
 from tensorflow.python import keras
 from tensorflow.python.feature_column import feature_column_lib as feature_column
 from tensorflow.python.layers import layers

tensorflow/python/distribute/BUILD

@@ -103,6 +103,18 @@ cuda_py_test(
     ],
 )
 
+py_library(
+    name = "distribute",
+    srcs = [
+        "__init__.py",
+    ],
+    srcs_version = "PY2AND3",
+    deps = [
+        ":distribute_lib",
+        ":mirrored_strategy",
+    ],
+)
+
 py_library(
     name = "distribute_lib",
     srcs = [

tensorflow/python/distribute/__init__.py

@@ -0,0 +1,25 @@
+# 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.
+# ==============================================================================
+"""Distribution Strategy library."""
+
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
+# pylint: disable=unused-import
+from tensorflow.python.distribute import distribute_lib
+from tensorflow.python.distribute import distribution_strategy_context
+from tensorflow.python.distribute import mirrored_strategy
+# pylint: enable=unused-import

tensorflow/python/distribute/mirrored_strategy.py

@@ -43,6 +43,7 @@ from tensorflow.python.ops import control_flow_ops
 from tensorflow.python.ops import variable_scope
 from tensorflow.python.training import coordinator
 from tensorflow.python.util import nest
+from tensorflow.python.util.tf_export import tf_export
 
 
 # TODO(josh11b): Replace asserts in this file with if ...: raise ...
@@ -422,6 +423,7 @@ def all_local_devices(num_gpus=None):
           ("/device:CPU:0",))
 
 
+@tf_export("distribute.MirroredStrategy")
 class MirroredStrategy(distribute_lib.DistributionStrategy):
   """Mirrors vars to distribute across multiple devices and machines.
 

tensorflow/tools/api/golden/v1/tensorflow.distribute.-mirrored-strategy.pbtxt

@@ -0,0 +1,138 @@
+path: "tensorflow.distribute.MirroredStrategy"
+tf_class {
+  is_instance: "<class \'tensorflow.python.distribute.mirrored_strategy.MirroredStrategy\'>"
+  is_instance: "<class \'tensorflow.python.distribute.distribute_lib.DistributionStrategy\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "between_graph"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "extended"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "num_replicas_in_sync"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "parameter_devices"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "require_static_shapes"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "should_checkpoint"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "should_init"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "should_save_summary"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "worker_devices"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'devices\', \'cross_device_ops\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "batch_reduce"
+    argspec: "args=[\'self\', \'aggregation\', \'value_destination_pairs\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "broadcast"
+    argspec: "args=[\'self\', \'tensor\', \'destinations\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "call_for_each_replica"
+    argspec: "args=[\'self\', \'fn\'], varargs=args, keywords=kwargs, defaults=None"
+  }
+  member_method {
+    name: "colocate_vars_with"
+    argspec: "args=[\'self\', \'colocate_with_variable\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "configure"
+    argspec: "args=[\'self\', \'session_config\', \'cluster_spec\', \'task_type\', \'task_id\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "distribute_dataset"
+    argspec: "args=[\'self\', \'dataset_fn\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "experimental_finalize"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "experimental_initialize"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "finalize"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "group"
+    argspec: "args=[\'self\', \'value\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "initialize"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "make_dataset_iterator"
+    argspec: "args=[\'self\', \'dataset\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "make_input_fn_iterator"
+    argspec: "args=[\'self\', \'input_fn\', \'replication_mode\'], varargs=None, keywords=None, defaults=[\'InputReplicationMode.PER_WORKER\'], "
+  }
+  member_method {
+    name: "non_slot_devices"
+    argspec: "args=[\'self\', \'var_list\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "read_var"
+    argspec: "args=[\'self\', \'v\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "reduce"
+    argspec: "args=[\'self\', \'reduce_op\', \'value\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "run_steps_on_dataset"
+    argspec: "args=[\'self\', \'fn\', \'iterator\', \'iterations\', \'initial_loop_values\'], varargs=None, keywords=None, defaults=[\'1\', \'None\'], "
+  }
+  member_method {
+    name: "scope"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "unwrap"
+    argspec: "args=[\'self\', \'value\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "update"
+    argspec: "args=[\'self\', \'var\', \'fn\'], varargs=args, keywords=kwargs, defaults=None"
+  }
+  member_method {
+    name: "update_config_proto"
+    argspec: "args=[\'self\', \'config_proto\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "update_non_slot"
+    argspec: "args=[\'self\', \'colocate_with\', \'fn\'], varargs=args, keywords=kwargs, defaults=None"
+  }
+  member_method {
+    name: "value_container"
+    argspec: "args=[\'self\', \'value\'], varargs=None, keywords=None, defaults=None"
+  }
+}

tensorflow/tools/api/golden/v1/tensorflow.distribute.pbtxt

@@ -8,6 +8,10 @@ tf_module {
     name: "InputReplicationMode"
     mtype: "<class \'enum.EnumMeta\'>"
   }
+  member {
+    name: "MirroredStrategy"
+    mtype: "<type \'type\'>"
+  }
   member {
     name: "ReduceOp"
     mtype: "<class \'enum.EnumMeta\'>"

tensorflow/tools/api/golden/v2/tensorflow.distribute.-mirrored-strategy.pbtxt

@@ -0,0 +1,138 @@
+path: "tensorflow.distribute.MirroredStrategy"
+tf_class {
+  is_instance: "<class \'tensorflow.python.distribute.mirrored_strategy.MirroredStrategy\'>"
+  is_instance: "<class \'tensorflow.python.distribute.distribute_lib.DistributionStrategy\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "between_graph"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "extended"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "num_replicas_in_sync"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "parameter_devices"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "require_static_shapes"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "should_checkpoint"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "should_init"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "should_save_summary"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "worker_devices"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'devices\', \'cross_device_ops\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "batch_reduce"
+    argspec: "args=[\'self\', \'aggregation\', \'value_destination_pairs\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "broadcast"
+    argspec: "args=[\'self\', \'tensor\', \'destinations\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "call_for_each_replica"
+    argspec: "args=[\'self\', \'fn\'], varargs=args, keywords=kwargs, defaults=None"
+  }
+  member_method {
+    name: "colocate_vars_with"
+    argspec: "args=[\'self\', \'colocate_with_variable\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "configure"
+    argspec: "args=[\'self\', \'session_config\', \'cluster_spec\', \'task_type\', \'task_id\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "distribute_dataset"
+    argspec: "args=[\'self\', \'dataset_fn\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "experimental_finalize"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "experimental_initialize"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "finalize"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "group"
+    argspec: "args=[\'self\', \'value\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "initialize"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "make_dataset_iterator"
+    argspec: "args=[\'self\', \'dataset\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "make_input_fn_iterator"
+    argspec: "args=[\'self\', \'input_fn\', \'replication_mode\'], varargs=None, keywords=None, defaults=[\'InputReplicationMode.PER_WORKER\'], "
+  }
+  member_method {
+    name: "non_slot_devices"
+    argspec: "args=[\'self\', \'var_list\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "read_var"
+    argspec: "args=[\'self\', \'v\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "reduce"
+    argspec: "args=[\'self\', \'reduce_op\', \'value\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "run_steps_on_dataset"
+    argspec: "args=[\'self\', \'fn\', \'iterator\', \'iterations\', \'initial_loop_values\'], varargs=None, keywords=None, defaults=[\'1\', \'None\'], "
+  }
+  member_method {
+    name: "scope"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "unwrap"
+    argspec: "args=[\'self\', \'value\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "update"
+    argspec: "args=[\'self\', \'var\', \'fn\'], varargs=args, keywords=kwargs, defaults=None"
+  }
+  member_method {
+    name: "update_config_proto"
+    argspec: "args=[\'self\', \'config_proto\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "update_non_slot"
+    argspec: "args=[\'self\', \'colocate_with\', \'fn\'], varargs=args, keywords=kwargs, defaults=None"
+  }
+  member_method {
+    name: "value_container"
+    argspec: "args=[\'self\', \'value\'], varargs=None, keywords=None, defaults=None"
+  }
+}

tensorflow/tools/api/golden/v2/tensorflow.distribute.pbtxt

@@ -8,6 +8,10 @@ tf_module {
     name: "InputReplicationMode"
     mtype: "<class \'enum.EnumMeta\'>"
   }
+  member {
+    name: "MirroredStrategy"
+    mtype: "<type \'type\'>"
+  }
   member {
     name: "ReduceOp"
     mtype: "<class \'enum.EnumMeta\'>"