diff --git a/tensorflow/python/distribute/tpu_strategy_test.py b/tensorflow/python/distribute/tpu_strategy_test.py
index bec96e4eece..4b88ae7134a 100644
--- a/tensorflow/python/distribute/tpu_strategy_test.py
+++ b/tensorflow/python/distribute/tpu_strategy_test.py
@@ -137,7 +137,7 @@ class TPUStrategyTest(test.TestCase):
       def computation():
         return random_ops.random_gamma([10], [0.5, 1.5])
 
-      return strategy.experimental_run_v2(computation)
+      return strategy.run(computation)
 
     with self.assertRaisesRegexp(errors.InvalidArgumentError,
                                  "TPU compilation failed"):
@@ -149,7 +149,7 @@ class TPUStrategyTest(test.TestCase):
       def computation():
         return random_ops.random_normal([10])
 
-      return strategy.experimental_run_v2(computation)
+      return strategy.run(computation)
 
     good_run()
 
diff --git a/tensorflow/python/tpu/tpu.py b/tensorflow/python/tpu/tpu.py
index 5c3a61d5d8d..fe8fac794db 100644
--- a/tensorflow/python/tpu/tpu.py
+++ b/tensorflow/python/tpu/tpu.py
@@ -223,7 +223,7 @@ def tpu_replicated_input_resolver(op, resource_reads, resource_writes):
       return False
   # Replace tensors in `resource_inputs` which are outputs of TPUReplicatedInput
   # with the actual replicated inputs. This allows ACD to correct add control
-  # deps when there are multiple calls to `experimental_run_v2` in a
+  # deps when there are multiple calls to `run` in a
   # `tf.function`.
   def replace_with_unreplicated_resources(resource_inputs):
     """Replaces handles in `resource_inputs` with their unreplicated inputs."""
diff --git a/tensorflow/python/training/experimental/loss_scaling_gradient_tape.py b/tensorflow/python/training/experimental/loss_scaling_gradient_tape.py
index a2502b8a43f..730f3bef9bc 100644
--- a/tensorflow/python/training/experimental/loss_scaling_gradient_tape.py
+++ b/tensorflow/python/training/experimental/loss_scaling_gradient_tape.py
@@ -40,7 +40,7 @@ def _convert_to_per_replicas(distribution, values):
   Returns:
     `values`, but each element has been converted to a PerReplica value.
   """
-  return distribution.experimental_run_v2(
+  return distribution.run(
       lambda values: [array_ops.identity(v) for v in values],
       args=(values,)
   )