Skip wav2vec2 hubert high mem tests (#21643)

* Skip high memory tests

* Skip high memory tests

* Remove unused import

tests/models/hubert/test_modeling_tf_hubert.py

@@ -450,19 +450,15 @@ class TFHubertRobustModelTest(TFModelTesterMixin, unittest.TestCase):
         model = TFHubertModel.from_pretrained("facebook/hubert-large-ls960-ft")
         self.assertIsNotNone(model)
 
-    # We override here as passing a full batch of 13 samples results in OOM errors for CTC
+    @unittest.skip(reason="Fix me! Hubert hits OOM errors when loss is computed on full batch")
     def test_dataset_conversion(self):
-        default_batch_size = self.model_tester.batch_size
-        self.model_tester.batch_size = 2
-        super().test_dataset_conversion()
-        self.model_tester.batch_size = default_batch_size
+        # TODO: (Amy) - check whether skipping CTC model resolves this issue and possible resolutions for CTC
+        pass
 
-    # We override here as passing a full batch of 13 samples results in OOM errors for CTC
+    @unittest.skip(reason="Fix me! Hubert hits OOM errors when loss is computed on full batch")
     def test_keras_fit(self):
-        default_batch_size = self.model_tester.batch_size
-        self.model_tester.batch_size = 2
-        super().test_keras_fit()
-        self.model_tester.batch_size = default_batch_size
+        # TODO: (Amy) - check whether skipping CTC model resolves this issue and possible resolutions for CTC
+        pass
 
 
 @require_tf

tests/models/wav2vec2/test_modeling_tf_wav2vec2.py

@@ -385,20 +385,15 @@ class TFWav2Vec2ModelTest(TFModelTesterMixin, unittest.TestCase):
         model = TFWav2Vec2Model.from_pretrained("facebook/wav2vec2-base-960h")
         self.assertIsNotNone(model)
 
-    # We override here as passing a full batch of 13 samples results in OOM errors for CTC
-    @unittest.skip("Fix me!")
+    @unittest.skip(reason="Fix me! Wav2Vec2 hits OOM errors when loss is computed on full batch")
     def test_dataset_conversion(self):
-        default_batch_size = self.model_tester.batch_size
-        self.model_tester.batch_size = 2
-        super().test_dataset_conversion()
-        self.model_tester.batch_size = default_batch_size
+        # TODO: (Amy) - check whether skipping CTC model resolves this issue and possible resolutions for CTC
+        pass
 
-    # We override here as passing a full batch of 13 samples results in OOM errors for CTC
+    @unittest.skip(reason="Fix me! Wav2Vec2 hits OOM errors when loss is computed on full batch")
     def test_keras_fit(self):
-        default_batch_size = self.model_tester.batch_size
-        self.model_tester.batch_size = 2
-        super().test_keras_fit()
-        self.model_tester.batch_size = default_batch_size
+        # TODO: (Amy) - check whether skipping CTC model resolves this issue and possible resolutions for CTC
+        pass
 
 
 @require_tf