MultiProcessRunner: symbol replacement: barrier->get_barrier

PiperOrigin-RevId: 335901962
Change-Id: I55ac18bb4a6ac52ca22ac06c329d02f4fdfe083c

tensorflow/python/distribute/multi_process_runner.py

@@ -1145,11 +1145,12 @@ def run(fn,
 _barrier = None
 
 
-def barrier():
+def get_barrier():
   if _barrier is None:
     raise ValueError(
-        'barrier is not defined. It is likely because you are calling barrier()'
+        'barrier is not defined. It is likely because you are calling '
-        'in the main process. barrier() can only be called in the subprocesses.'
+        'get_barrier() in the main process. get_barrier() can only be called '
+        'in the subprocesses.'
     )
   return _barrier
 

tensorflow/python/distribute/multi_process_runner_test.py

@@ -54,7 +54,7 @@ def fn_that_returns_args_and_kwargs(*args, **kwargs):
 
 
 def fn_with_barrier():
-  return multi_process_runner.barrier()
+  return multi_process_runner.get_barrier()
 
 
 def fn_that_returns_pid():
@@ -296,7 +296,7 @@ class MultiProcessRunnerTest(test.TestCase):
 
   def test_barrier_called_in_main_process(self):
     with self.assertRaises(ValueError):
-      multi_process_runner.barrier()
+      multi_process_runner.get_barrier()
 
   def test_stdout_available_when_timeout(self):
 

tensorflow/python/distribute/multi_worker_continuous_run_test.py

@@ -74,7 +74,7 @@ class MultiWorkerContinuousRunTest(test.TestCase, parameterized.TestCase):
     def worker_step_fn(worker_id):
       strategy = collective_all_reduce_strategy.CollectiveAllReduceStrategy()
       # Make sure the processeses are in sync after updating the cluster
-      multi_process_runner.barrier().wait()
+      multi_process_runner.get_barrier().wait()
 
       @def_function.function
       def run_reduce():
@@ -107,7 +107,7 @@ class MultiWorkerContinuousRunTest(test.TestCase, parameterized.TestCase):
     def worker_step_fn(worker_id, num_dims):
       strategy = collective_all_reduce_strategy.CollectiveAllReduceStrategy()
       # Make sure the processeses are in sync after updating the cluster
-      multi_process_runner.barrier().wait()
+      multi_process_runner.get_barrier().wait()
       tensor_shape = [2] * num_dims
 
       def variable_fn():

tensorflow/python/distribute/strategy_combinations.py

@@ -124,10 +124,10 @@ def _get_multi_worker_mirrored_creator(required_gpus):
     # collectives may hang if any worker launches collectives before the chief
     # creates the strategy.
     try:
-      multi_process_runner.barrier().wait()
+      multi_process_runner.get_barrier().wait()
     except ValueError:
       # If the creator is called in the main process,
-      # multi_process_runner.barrier() raises ValueError, which is safe to
+      # multi_process_runner.get_barrier() raises ValueError, which is safe to
       # ignore.
       pass
     return strategy

tensorflow/python/keras/distribute/multi_worker_callback_tf2_test.py

@@ -204,7 +204,7 @@ class KerasCallbackMultiProcessTest(parameterized.TestCase, test.TestCase):
         if 'Interrupting!' not in str(e):
           raise
 
-      multi_process_runner.barrier().wait()
+      multi_process_runner.get_barrier().wait()
       backup_filepath = os.path.join(bar_dir, 'checkpoint')
       test_obj.assertTrue(file_io.file_exists_v2(backup_filepath))
       test_obj.assertTrue(file_io.file_exists_v2(saving_filepath))
@@ -218,7 +218,7 @@ class KerasCallbackMultiProcessTest(parameterized.TestCase, test.TestCase):
               callbacks.BackupAndRestore(backup_dir=bar_dir),
               AssertCallback()
           ])
-      multi_process_runner.barrier().wait()
+      multi_process_runner.get_barrier().wait()
       test_obj.assertFalse(file_io.file_exists_v2(backup_filepath))
       test_obj.assertTrue(file_io.file_exists_v2(saving_filepath))
 
@@ -306,7 +306,7 @@ class KerasCallbackMultiProcessTest(parameterized.TestCase, test.TestCase):
       # The saving_filepath shouldn't exist at the beginning (as it's unique).
       test_obj.assertFalse(file_io.file_exists_v2(saving_filepath))
 
-      multi_process_runner.barrier().wait()
+      multi_process_runner.get_barrier().wait()
 
       model.fit(
           x=train_ds,
@@ -314,7 +314,7 @@ class KerasCallbackMultiProcessTest(parameterized.TestCase, test.TestCase):
           steps_per_epoch=steps,
           callbacks=[callbacks.TensorBoard(log_dir=saving_filepath)])
 
-      multi_process_runner.barrier().wait()
+      multi_process_runner.get_barrier().wait()
 
       test_obj.assertTrue(file_io.list_directory_v2(saving_filepath))
 

tensorflow/python/keras/distribute/multi_worker_tutorial_test.py

@@ -158,7 +158,7 @@ class MultiWorkerTutorialTest(parameterized.TestCase, test.TestCase):
         file_io.delete_recursively_v2(os.path.dirname(write_model_path))
 
       # Make sure chief finishes saving before non-chief's assertions.
-      multi_process_runner.barrier().wait()
+      multi_process_runner.get_barrier().wait()
 
       if not file_io.file_exists_v2(model_path):
         raise RuntimeError()
@@ -179,7 +179,7 @@ class MultiWorkerTutorialTest(parameterized.TestCase, test.TestCase):
         file_io.delete_recursively_v2(write_checkpoint_dir)
 
       # Make sure chief finishes saving before non-chief's assertions.
-      multi_process_runner.barrier().wait()
+      multi_process_runner.get_barrier().wait()
 
       if not file_io.file_exists_v2(checkpoint_dir):
         raise RuntimeError()

tensorflow/python/kernel_tests/collective_ops_multi_worker_test.py

@@ -64,7 +64,7 @@ class CollectiveOpTest(test.TestCase):
         except errors.UnavailableError:
           continue
         break
-      multi_process_runner.barrier().wait()
+      multi_process_runner.get_barrier().wait()
 
     cluster_spec = multi_worker_test_base.create_cluster_spec(num_workers=2)
     mpr = multi_process_runner.MultiProcessRunner(worker_fn, cluster_spec)