mark preset test to extra large to skip GPU testing (#2458)

* mark preset test to extra large to skip GPU testing

* add few more tests

Author: sachinprasadhs

keras_hub/src/models/albert/albert_backbone_test.py

@@ -56,7 +56,7 @@ def test_saved_model(self):
             input_data=self.input_data,
         )
 
-    @pytest.mark.large
+    @pytest.mark.extra_large
     def test_smallest_preset(self):
         self.run_preset_test(
             cls=AlbertBackbone,

keras_hub/src/models/bart/bart_backbone_test.py

@@ -41,7 +41,7 @@ def test_saved_model(self):
             input_data=self.input_data,
         )
 
-    @pytest.mark.large
+    @pytest.mark.extra_large
     def test_smallest_preset(self):
         self.run_preset_test(
             cls=BartBackbone,

keras_hub/src/models/bart/bart_tokenizer_test.py

@@ -34,7 +34,7 @@ def test_errors_missing_special_tokens(self):
         with self.assertRaises(ValueError):
             BartTokenizer(vocabulary=["a", "b", "c"], merges=[])
 
-    @pytest.mark.large
+    @pytest.mark.extra_large
     def test_smallest_preset(self):
         self.run_preset_test(
             cls=BartTokenizer,

keras_hub/src/models/bert/bert_backbone_test.py

@@ -40,7 +40,7 @@ def test_saved_model(self):
             input_data=self.input_data,
         )
 
-    @pytest.mark.large
+    @pytest.mark.extra_large
     def test_smallest_preset(self):
         self.run_preset_test(
             cls=BertBackbone,

keras_hub/src/models/bert/bert_text_classifier_test.py

@@ -53,7 +53,7 @@ def test_saved_model(self):
             input_data=self.input_data,
         )
 
-    @pytest.mark.large
+    @pytest.mark.extra_large
     def test_smallest_preset(self):
         self.run_preset_test(
             cls=BertTextClassifier,

keras_hub/src/models/bert/bert_tokenizer_test.py

@@ -39,7 +39,7 @@ def test_errors_missing_special_tokens(self):
         with self.assertRaises(ValueError):
             BertTokenizer(vocabulary=["a", "b", "c"])
 
-    @pytest.mark.large
+    @pytest.mark.extra_large
     def test_smallest_preset(self):
         self.run_preset_test(
             cls=BertTokenizer,

keras_hub/src/models/bloom/bloom_backbone_test.py

@@ -35,7 +35,7 @@ def test_saved_model(self):
             input_data=self.input_data,
         )
 
-    @pytest.mark.large
+    @pytest.mark.extra_large
     def test_smallest_preset(self):
         self.run_preset_test(
             cls=BloomBackbone,

keras_hub/src/models/bloom/bloom_tokenizer_test.py

@@ -30,7 +30,7 @@ def test_errors_missing_special_tokens(self):
         with self.assertRaises(ValueError):
             BloomTokenizer(vocabulary=["a", "b", "c"], merges=[])
 
-    @pytest.mark.large
+    @pytest.mark.extra_large
     def test_smallest_preset(self):
         self.run_preset_test(
             cls=BloomTokenizer,

keras_hub/src/models/clip/clip_tokenizer_test.py

@@ -35,7 +35,7 @@ def test_errors_missing_special_tokens(self):
         with self.assertRaises(ValueError):
             CLIPTokenizer(vocabulary={"foo": 0, "bar": 1}, merges=["fo o"])
 
-    @pytest.mark.large
+    @pytest.mark.extra_large
     def test_smallest_preset(self):
         self.run_preset_test(
             cls=CLIPTokenizer,

keras_hub/src/models/cspnet/cspnet_image_classifier_test.py

@@ -58,7 +58,7 @@ def test_classifier_basics(self):
             expected_output_shape=(2, 3),
         )
 
-    @pytest.mark.large
+    @pytest.mark.extra_large
     def test_smallest_preset(self):
         image_batch = self.load_test_image()[None, ...] / 255.0
         self.run_preset_test(