Add condition to avoid saving duplicate checkpoints.

PiperOrigin-RevId: 277156216

official/modeling/training/distributed_executor.py

@@ -452,7 +452,6 @@ class DistributedExecutor(object):
       save_freq = FLAGS.save_checkpoint_freq
     else:
       save_freq = iterations_per_loop
-    last_save_checkpoint_step = 0
 
     params = self._params
     strategy = self._strategy
@@ -507,6 +506,7 @@ class DistributedExecutor(object):
       test_step = self._create_test_step(strategy, model, metric=eval_metric)
 
     logging.info('Training started')
+    last_save_checkpoint_step = current_step
     while current_step < total_steps:
 
       num_steps = _steps_to_run(current_step, total_steps, iterations_per_loop)
@@ -569,8 +569,9 @@ class DistributedExecutor(object):
         train_metric.reset_states()
 
     # Reaches the end of training and saves the last checkpoint.
-    _save_checkpoint(checkpoint, model_dir,
-                     checkpoint_name.format(step=current_step))
+    if last_save_checkpoint_step < total_steps:
+      _save_checkpoint(checkpoint, model_dir,
+                       checkpoint_name.format(step=current_step))
 
     if test_step:
       logging.info('Running final evaluation after training is complete.')