Change default value of use_experimental_api to False.

PiperOrigin-RevId: 367105004

official/modeling/performance.py

@@ -14,19 +14,19 @@
 
 """Functions and classes related to training performance."""
 
+from absl import logging
 import tensorflow as tf
 
 
-# TODO(b/181616568): Switch default value of `use_experimental_api` in both
-# of these functions to False.
-
-
 def configure_optimizer(optimizer,
                         use_float16=False,
                         use_graph_rewrite=False,
                         loss_scale='dynamic',
-                        use_experimental_api=True):
+                        use_experimental_api=False):
   """Configures optimizer object with performance options."""
+  if use_experimental_api:
+    logging.warning('Passing use_experimental_api=True is deprecated. The '
+                    'argument will be removed in the future.')
   if use_float16:
     # TODO(b/171936854): Move all methods to non-experimental api.
     if use_experimental_api:
@@ -53,8 +53,11 @@ def configure_optimizer(optimizer,
 
 
 def set_mixed_precision_policy(dtype, loss_scale=None,
-                               use_experimental_api=True):
+                               use_experimental_api=False):
   """Sets mix precision policy."""
+  if use_experimental_api:
+    logging.warning('Passing use_experimental_api=True is deprecated. The '
+                    'argument will be removed in the future.')
   assert use_experimental_api or loss_scale is None, (
       'loss_scale cannot be specified if use_experimental_api is False. If the '
       'non-experimental API is used, specify the loss scaling configuration '

official/vision/beta/projects/simclr/tasks/simclr.py

@@ -91,7 +91,8 @@ class SimCLRPretrainTask(base_task.Task):
       optimizer = performance.configure_optimizer(
           optimizer,
           use_float16=runtime_config.mixed_precision_dtype == 'float16',
-          loss_scale=runtime_config.loss_scale)
+          loss_scale=runtime_config.loss_scale,
+          use_experimental_api=True)
 
     return optimizer
 
@@ -396,7 +397,8 @@ class SimCLRFinetuneTask(base_task.Task):
       optimizer = performance.configure_optimizer(
           optimizer,
           use_float16=runtime_config.mixed_precision_dtype == 'float16',
-          loss_scale=runtime_config.loss_scale)
+          loss_scale=runtime_config.loss_scale,
+          use_experimental_api=True)
 
     return optimizer
 

official/vision/beta/projects/simclr/train.py

@@ -60,7 +60,8 @@ def main(_):
   # dtype is float16
   if params.runtime.mixed_precision_dtype:
     performance.set_mixed_precision_policy(params.runtime.mixed_precision_dtype,
-                                           params.runtime.loss_scale)
+                                           params.runtime.loss_scale,
+                                           use_experimental_api=True)
   distribution_strategy = distribute_utils.get_distribution_strategy(
       distribution_strategy=params.runtime.distribution_strategy,
       all_reduce_alg=params.runtime.all_reduce_alg,

official/vision/beta/projects/yt8m/train.py

@@ -47,7 +47,8 @@ def main(_):
   # dtype is float16
   if params.runtime.mixed_precision_dtype:
     performance.set_mixed_precision_policy(params.runtime.mixed_precision_dtype,
-                                           params.runtime.loss_scale)
+                                           params.runtime.loss_scale,
+                                           use_experimental_api=True)
   distribution_strategy = distribute_utils.get_distribution_strategy(
       distribution_strategy=params.runtime.distribution_strategy,
       all_reduce_alg=params.runtime.all_reduce_alg,