:

Fixing compat due to conditional accumulator changes.\

PiperOrigin-RevId: 260979763

tensorflow/python/BUILD

@@ -5116,7 +5116,6 @@ tf_py_test(
     grpc_enabled = True,
     tags = [
         "no_oss",  # Test flaky due to port collisions.
-        "nofwdcompat",  # b/137641346
         "notsan",  # data race due to b/62910646
         "oss_serial",
     ],

tensorflow/python/kernel_tests/BUILD

@@ -271,7 +271,6 @@ tf_py_test(
         "//tensorflow/python:state_ops",
         "//tensorflow/python:variables",
     ],
-    tags = ["nofwdcompat"],  # b/137641346
 )
 
 tf_py_test(
@@ -984,7 +983,6 @@ tf_py_test(
         "//tensorflow/python:errors",
         "//tensorflow/python:framework_for_generated_wrappers",
     ],
-    tags = ["nofwdcompat"],  # b/137641346
 )
 
 tf_py_test(

tensorflow/python/kernel_tests/conditional_accumulator_test.py

@@ -39,47 +39,12 @@ from tensorflow.python.platform import test
 
 class ConditionalAccumulatorTest(test.TestCase):
 
-  def testConstructor(self):
-    with ops.Graph().as_default():
-      q = data_flow_ops.ConditionalAccumulator(dtypes_lib.float32, name="Q")
-    self.assertTrue(isinstance(q.accumulator_ref, ops.Tensor))
-    self.assertProtoEquals(
-        """
-      name:'Q' op:'ConditionalAccumulator'
-      attr { key: 'dtype' value { type: DT_FLOAT } }
-      attr { key: 'shape' value { shape { unknown_rank: true} } }
-      attr { key: 'container' value { s: '' } }
-      attr { key: 'shared_name' value { s: '' } }
-      attr { key: 'reduction_type' value {s: 'MEAN'} }
-      """, q.accumulator_ref.op.node_def)
-
   def testConstructorWithInvalidArg(self):
     with ops.Graph().as_default():
       with self.assertRaises(ValueError):
         data_flow_ops.ConditionalAccumulator(
             dtypes_lib.float32, name="Q", reduction_type="Invalid")
 
-  def testConstructorWithShape(self):
-    with ops.Graph().as_default():
-      q = data_flow_ops.ConditionalAccumulator(
-          dtypes_lib.float32,
-          name="Q",
-          shape=tensor_shape.TensorShape([1, 5, 2, 8]))
-    self.assertTrue(isinstance(q.accumulator_ref, ops.Tensor))
-    self.assertProtoEquals(
-        """
-      name:'Q' op:'ConditionalAccumulator'
-      attr { key: 'dtype' value { type: DT_FLOAT } }
-      attr { key: 'shape' value { shape { dim {size: 1 }
-                                          dim {size: 5 }
-                                          dim {size: 2 }
-                                          dim {size: 8 }
-      } } }
-      attr { key: 'container' value { s: '' } }
-      attr { key: 'shared_name' value { s: '' } }
-      attr { key: 'reduction_type' value {s: 'MEAN'} }
-      """, q.accumulator_ref.op.node_def)
-
   @test_util.run_deprecated_v1
   def testAccumulatorSizeEmpty(self):
     with self.cached_session():

tensorflow/python/ops/data_flow_ops.py

@@ -1518,6 +1518,40 @@ class SparseConditionalAccumulator(ConditionalAccumulatorBase):
         values=return_val.values,
         dense_shape=return_val.shape)
 
+  # SparseConditionalAccumulator is not switched to resource. Use old kernels.
+  def num_accumulated(self, name=None):
+    """Number of gradients that have currently been aggregated in accumulator.
+
+    Args:
+      name: Optional name for the operation.
+
+    Returns:
+      Number of accumulated gradients currently in accumulator.
+    """
+    if name is None:
+      name = "%s_NumAccumulated" % self._name
+
+    return gen_data_flow_ops.accumulator_num_accumulated(
+        self._accumulator_ref, name=name)
+
+  def set_global_step(self, new_global_step, name=None):
+    """Sets the global time step of the accumulator.
+
+    The operation logs a warning if we attempt to set to a time step that is
+    lower than the accumulator's own time step.
+
+    Args:
+      new_global_step: Value of new time step. Can be a variable or a constant
+      name: Optional name for the operation.
+
+    Returns:
+      Operation that sets the accumulator's time step.
+    """
+    return gen_data_flow_ops.accumulator_set_global_step(
+        self._accumulator_ref,
+        math_ops.cast(ops.convert_to_tensor(new_global_step), _dtypes.int64),
+        name=name)
+
 
 class BaseStagingArea(object):
   """Base class for Staging Areas."""