Automated rollback of commit 5f822d694af6e4aa57fe8a426032a91dc61e30d6

PiperOrigin-RevId: 215239710

3 files changed, 16 insertions, 23 deletions

diff --git a/tensorflow/contrib/factorization/BUILD b/tensorflow/contrib/factorization/BUILD
index 510f292508..e344d7a23b 100644
--- a/tensorflow/contrib/factorization/BUILD
+++ b/tensorflow/contrib/factorization/BUILD
@@ -154,8 +154,6 @@ tf_py_test(
     ],
     tags = [
         "no_pip",  # b/38283730
-        "noasan",  # b/116875897
-        "nomsan",
         "notsan",  # Flaky: b/30756419
     ],
 )
@@ -179,11 +177,7 @@ tf_py_test(
         "//tensorflow/python:random_seed",
         "//tensorflow/python:variables",
     ],
-    tags = [
-        "noasan",  # b/116875897
-        "nomsan",
-        "notsan",  # b/62863147
-    ],
+    tags = ["notsan"],  # b/62863147
 )
 
 py_library(
@@ -282,7 +276,6 @@ tf_py_test(
         "manual",
         "noasan",  # times out b/63678675
         "nomsan",
-        "notsan",  # b/116875897
     ],
 )
 
diff --git a/tensorflow/contrib/factorization/python/ops/gmm_ops.py b/tensorflow/contrib/factorization/python/ops/gmm_ops.py
index e076631bc1..d365ad1117 100644
--- a/tensorflow/contrib/factorization/python/ops/gmm_ops.py
+++ b/tensorflow/contrib/factorization/python/ops/gmm_ops.py
@@ -154,10 +154,10 @@ class GmmAlgorithm(object):
   def _create_variables(self):
     """Initializes GMM algorithm."""
     init_value = array_ops.constant([], dtype=dtypes.float32)
-    self._means = variables.Variable(init_value,
-                                     name=self.CLUSTERS_VARIABLE,
-                                     validate_shape=False)
-    self._covs = variables.Variable(
+    self._means = variables.VariableV1(init_value,
+                                       name=self.CLUSTERS_VARIABLE,
+                                       validate_shape=False)
+    self._covs = variables.VariableV1(
         init_value, name=self.CLUSTERS_COVS_VARIABLE, validate_shape=False)
     # Mixture weights, representing the probability that a randomly
     # selected unobservable data (in EM terms) was generated by component k.
@@ -165,9 +165,9 @@ class GmmAlgorithm(object):
         array_ops.tile([1.0 / self._num_classes], [self._num_classes]),
         name=self.CLUSTERS_WEIGHT,
         validate_shape=False)
-    self._cluster_centers_initialized = variables.Variable(False,
-                                                           dtype=dtypes.bool,
-                                                           name='initialized')
+    self._cluster_centers_initialized = variables.VariableV1(False,
+                                                             dtype=dtypes.bool,
+                                                             name='initialized')
 
   def _initialize_variables(self, data, initial_means=None):
     """Initializes variables.
diff --git a/tensorflow/contrib/factorization/python/ops/wals_test.py b/tensorflow/contrib/factorization/python/ops/wals_test.py
index 9bdbd05015..75d577f429 100644
--- a/tensorflow/contrib/factorization/python/ops/wals_test.py
+++ b/tensorflow/contrib/factorization/python/ops/wals_test.py
@@ -420,13 +420,13 @@ class WALSMatrixFactorizationUnsupportedTest(test.TestCase):
 class SweepHookTest(test.TestCase):
 
   def test_sweeps(self):
-    is_row_sweep_var = variables.Variable(True)
-    is_sweep_done_var = variables.Variable(False)
-    init_done = variables.Variable(False)
-    row_prep_done = variables.Variable(False)
-    col_prep_done = variables.Variable(False)
-    row_train_done = variables.Variable(False)
-    col_train_done = variables.Variable(False)
+    is_row_sweep_var = variables.VariableV1(True)
+    is_sweep_done_var = variables.VariableV1(False)
+    init_done = variables.VariableV1(False)
+    row_prep_done = variables.VariableV1(False)
+    col_prep_done = variables.VariableV1(False)
+    row_train_done = variables.VariableV1(False)
+    col_train_done = variables.VariableV1(False)
 
     init_op = state_ops.assign(init_done, True)
     row_prep_op = state_ops.assign(row_prep_done, True)
@@ -486,7 +486,7 @@ class StopAtSweepHookTest(test.TestCase):
 
   def test_stop(self):
     hook = wals_lib._StopAtSweepHook(last_sweep=10)
-    completed_sweeps = variables.Variable(
+    completed_sweeps = variables.VariableV1(
         8, name=wals_lib.WALSMatrixFactorization.COMPLETED_SWEEPS)
     train_op = state_ops.assign_add(completed_sweeps, 1)
     hook.begin()