Add sdca ops to tf.train.

This adds:
  * tf.train.sdca_optimizer
  * tf.train.sdca_fprint
  * tf.train.sdca_shrink_l1
which were previously documented, and prior to 1.0, in tf.sdca.
In 1.0, they were absent from tf.sdca, so this does not break
compatibility.

The module tf.sdca is removed.
Change: 153176548

tensorflow/contrib/linear_optimizer/python/kernel_tests/sdca_ops_test.py

@@ -1058,7 +1058,7 @@ class SdcaFprintTest(SdcaModelTest):
   def testFprint(self):
     with self._single_threaded_test_session():
       in_data = constant_op.constant(['abc', 'very looooooong string', 'def'])
-      out_data = gen_sdca_ops._sdca_fprint(in_data)
+      out_data = gen_sdca_ops.sdca_fprint(in_data)
       self.assertAllEqual([[4143508125394299908, -6879828354153669051],
                            [5849691694103072671, -4874542629849009556],
                            [603227410218889250, 8762207001949257490]],

tensorflow/contrib/linear_optimizer/python/ops/sdca_ops.py

@@ -307,7 +307,7 @@ class SdcaModel(object):
           sparse_features_values.append(sf.feature_values)
 
       # pylint: disable=protected-access
-      example_ids_hashed = gen_sdca_ops._sdca_fprint(
+      example_ids_hashed = gen_sdca_ops.sdca_fprint(
           internal_convert_to_tensor(self._examples['example_ids']))
       # pylint: enable=protected-access
       example_state_data = self._hashtable.lookup(example_ids_hashed)
@@ -328,7 +328,7 @@ class SdcaModel(object):
           sparse_weights.append(array_ops.gather(w, sparse_indices[-1]))
 
       # pylint: disable=protected-access
-      esu, sfw, dfw = gen_sdca_ops._sdca_optimizer(
+      esu, sfw, dfw = gen_sdca_ops.sdca_optimizer(
           sparse_example_indices,
           sparse_feature_indices,
           sparse_features_values,
@@ -390,7 +390,7 @@ class SdcaModel(object):
           with ops.device(var.device):
             # pylint: disable=protected-access
             update_ops.append(
-                gen_sdca_ops._sdca_shrink_l1(
+                gen_sdca_ops.sdca_shrink_l1(
                     self._convert_n_to_tensor(
                         [var], as_ref=True),
                     l1=self._symmetric_l1_regularization(),

tensorflow/python/BUILD

@@ -60,7 +60,6 @@ py_library(
         ":nn",
         ":platform",
         ":script_ops",
-        ":sdca_ops",
         ":session_ops",
         ":sets",
         ":sparse_ops",
@@ -2270,6 +2269,7 @@ py_library(
         ":random_ops",
         ":resource_variable_ops",
         ":resources",
+        ":sdca_ops",
         ":sparse_ops",
         ":state_ops",
         ":string_ops",

tensorflow/python/__init__.py

@@ -80,7 +80,6 @@ from tensorflow.python.layers import layers
 from tensorflow.python.ops import image_ops as image
 from tensorflow.python.ops import metrics
 from tensorflow.python.ops import nn
-from tensorflow.python.ops import sdca_ops as sdca
 from tensorflow.python.ops import sets
 from tensorflow.python.ops import spectral_ops as spectral
 from tensorflow.python.ops.losses import losses
@@ -225,7 +224,6 @@ _allowed_symbols.extend([
     'python_io',
     'resource_loader',
     'saved_model',
-    'sdca',
     'sets',
     'spectral',
     'summary',

tensorflow/python/ops/hidden_ops.txt

@@ -301,9 +301,6 @@ PyFunc
 PyFuncStateless
 
 # sdca_ops
-SdcaFprint
-SdcaOptimizer
-SdcaShrinkL1
 
 # state_ops
 Variable

tensorflow/python/training/training.py

@@ -95,10 +95,14 @@ from __future__ import print_function
 import sys as _sys
 
 from tensorflow.python.ops import io_ops as _io_ops
+from tensorflow.python.ops import sdca_ops as _sdca_ops
 from tensorflow.python.ops import state_ops as _state_ops
 from tensorflow.python.util.all_util import remove_undocumented
 
 # pylint: disable=g-bad-import-order,unused-import
+from tensorflow.python.ops.sdca_ops import sdca_optimizer
+from tensorflow.python.ops.sdca_ops import sdca_fprint
+from tensorflow.python.ops.sdca_ops import sdca_shrink_l1
 from tensorflow.python.training.adadelta import AdadeltaOptimizer
 from tensorflow.python.training.adagrad import AdagradOptimizer
 from tensorflow.python.training.adagrad_da import AdagradDAOptimizer
@@ -224,4 +228,4 @@ _allowed_symbols = [
 # * Input methods in tf.train are documented in io_ops.
 # * Saver methods in tf.train are documented in state_ops.
 remove_undocumented(__name__, _allowed_symbols,
-                    [_sys.modules[__name__], _io_ops, _state_ops])
+                    [_sys.modules[__name__], _io_ops, _sdca_ops, _state_ops])

tensorflow/tools/api/golden/tensorflow.pbtxt

@@ -420,10 +420,6 @@ tf_module {
     name: "saved_model"
     mtype: "<type \'module\'>"
   }
-  member {
-    name: "sdca"
-    mtype: "<type \'module\'>"
-  }
   member {
     name: "sets"
     mtype: "<type \'module\'>"

tensorflow/tools/api/golden/tensorflow.sdca.pbtxt

@@ -1,3 +0,0 @@
-path: "tensorflow.sdca"
-tf_module {
-}

tensorflow/tools/api/golden/tensorflow.train.pbtxt

@@ -360,6 +360,18 @@ tf_module {
     name: "replica_device_setter"
     argspec: "args=[\'ps_tasks\', \'ps_device\', \'worker_device\', \'merge_devices\', \'cluster\', \'ps_ops\', \'ps_strategy\'], varargs=None, keywords=None, defaults=[\'0\', \'/job:ps\', \'/job:worker\', \'True\', \'None\', \'None\', \'None\'], "
   }
+  member_method {
+    name: "sdca_fprint"
+    argspec: "args=[\'input\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "sdca_optimizer"
+    argspec: "args=[\'sparse_example_indices\', \'sparse_feature_indices\', \'sparse_feature_values\', \'dense_features\', \'example_weights\', \'example_labels\', \'sparse_indices\', \'sparse_weights\', \'dense_weights\', \'example_state_data\', \'loss_type\', \'l1\', \'l2\', \'num_loss_partitions\', \'num_inner_iterations\', \'adaptative\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "sdca_shrink_l1"
+    argspec: "args=[\'weights\', \'l1\', \'l2\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "shuffle_batch"
     argspec: "args=[\'tensors\', \'batch_size\', \'capacity\', \'min_after_dequeue\', \'num_threads\', \'seed\', \'enqueue_many\', \'shapes\', \'allow_smaller_final_batch\', \'shared_name\', \'name\'], varargs=None, keywords=None, defaults=[\'1\', \'None\', \'False\', \'None\', \'False\', \'None\', \'None\'], "