Clean up

PiperOrigin-RevId: 348291651

official/core/base_trainer_test.py

@@ -34,9 +34,7 @@ def all_strategy_combinations():
           strategy_combinations.default_strategy,
           strategy_combinations.cloud_tpu_strategy,
           strategy_combinations.one_device_strategy_gpu,
-      ],
-      mode='eager',
-  )
+      ],)
 
 
 class TrainerTest(tf.test.TestCase, parameterized.TestCase):

official/core/train_lib_test.py

@@ -68,7 +68,6 @@ class TrainTest(tf.test.TestCase, parameterized.TestCase):
               strategy_combinations.cloud_tpu_strategy,
               strategy_combinations.one_device_strategy_gpu,
           ],
-          mode='eager',
           flag_mode=['train', 'eval', 'train_and_eval'],
           run_post_eval=[True, False]))
   def test_end_to_end(self, distribution_strategy, flag_mode, run_post_eval):

official/modeling/progressive/train_lib_test.py

@@ -137,7 +137,6 @@ class TrainTest(tf.test.TestCase, parameterized.TestCase):
               strategy_combinations.cloud_tpu_strategy,
               strategy_combinations.one_device_strategy_gpu,
           ],
-          mode='eager',
           flag_mode=['train', 'eval', 'train_and_eval'],
           run_post_eval=[True, False]))
   def test_end_to_end(self, distribution_strategy, flag_mode, run_post_eval):

official/modeling/progressive/trainer_test.py

@@ -37,9 +37,7 @@ def all_strategy_combinations():
           strategy_combinations.default_strategy,
           strategy_combinations.cloud_tpu_strategy,
           strategy_combinations.one_device_strategy_gpu,
-      ],
-      mode='eager',
-  )
+      ],)
 
 
 def get_exp_config():

official/nlp/bert/model_training_utils_test.py

@@ -40,9 +40,7 @@ def eager_strategy_combinations():
           strategy_combinations.one_device_strategy_gpu,
           strategy_combinations.mirrored_strategy_with_gpu_and_cpu,
           strategy_combinations.mirrored_strategy_with_two_gpus,
-      ],
-      mode='eager',
-  )
+      ],)
 
 
 def eager_gpu_strategy_combinations():
@@ -52,9 +50,7 @@ def eager_gpu_strategy_combinations():
           strategy_combinations.one_device_strategy_gpu,
           strategy_combinations.mirrored_strategy_with_gpu_and_cpu,
           strategy_combinations.mirrored_strategy_with_two_gpus,
-      ],
-      mode='eager',
-  )
+      ],)
 
 
 def create_fake_data_input_fn(batch_size, features_shape, num_classes):
@@ -290,9 +286,7 @@ class ModelTrainingUtilsTest(tf.test.TestCase, parameterized.TestCase):
       combinations.combine(
           distribution=[
               strategy_combinations.one_device_strategy_gpu,
-          ],
-          mode='eager',
-      ))
+          ],))
   def test_train_check_artifacts_non_chief(self, distribution):
     # We shouldn't export artifacts on non-chief workers. Since there's no easy
     # way to test with real MultiWorkerMirroredStrategy, we patch the strategy

official/nlp/nhnet/models_test.py

@@ -38,9 +38,7 @@ def all_strategy_combinations():
           strategy_combinations.one_device_strategy_gpu,
           strategy_combinations.mirrored_strategy_with_gpu_and_cpu,
           strategy_combinations.mirrored_strategy_with_two_gpus,
-      ],
-      mode="eager",
-  )
+      ],)
 
 
 def distribution_forward_path(strategy,

official/nlp/nhnet/trainer_test.py

@@ -39,9 +39,7 @@ def all_strategy_combinations():
           strategy_combinations.one_device_strategy_gpu,
           strategy_combinations.mirrored_strategy_with_gpu_and_cpu,
           strategy_combinations.cloud_tpu_strategy,
-      ],
-      mode="eager",
-  )
+      ],)
 
 
 def get_trivial_data(config) -> tf.data.Dataset:

official/vision/image_classification/classifier_trainer_test.py

@@ -54,7 +54,6 @@ def distribution_strategy_combinations() -> Iterable[Tuple[Any, ...]]:
           'efficientnet',
           'resnet',
       ],
-      mode='eager',
       dataset=[
           'imagenet',
       ],
@@ -151,7 +150,6 @@ class ClassifierTest(tf.test.TestCase, parameterized.TestCase):
               'efficientnet',
               'resnet',
           ],
-          mode='eager',
           dataset='imagenet',
           dtype='float16',
       ))
@@ -196,7 +194,6 @@ class ClassifierTest(tf.test.TestCase, parameterized.TestCase):
               'efficientnet',
               'resnet',
           ],
-          mode='eager',
           dataset='imagenet',
           dtype='bfloat16',
       ))

official/vision/image_classification/mnist_test.py

@@ -38,9 +38,7 @@ def eager_strategy_combinations():
           strategy_combinations.default_strategy,
           strategy_combinations.cloud_tpu_strategy,
           strategy_combinations.one_device_strategy_gpu,
-      ],
-      mode="eager",
-  )
+      ],)
 
 
 class KerasMnistTest(tf.test.TestCase, parameterized.TestCase):