Skip tests properly (#31308)

* Skip tests properly

* [test_all]

* Add 'reason' as kwarg for skipTest

* [test_all] Fix up

* [test_all]

tests/models/chinese_clip/test_image_processing_chinese_clip.py

@@ -17,7 +17,7 @@
 import unittest
 
 from transformers.testing_utils import require_torch, require_vision
-from transformers.utils import is_torch_available, is_vision_available
+from transformers.utils import is_vision_available
 
 from ...test_image_processing_common import ImageProcessingTestMixin, prepare_image_inputs
 
@@ -26,10 +26,6 @@ if is_vision_available():
     from transformers import ChineseCLIPImageProcessor
 
 
-if is_torch_available():
-    pass
-
-
 class ChineseCLIPImageProcessingTester(unittest.TestCase):
     def __init__(
         self,
@@ -125,7 +121,9 @@ class ChineseCLIPImageProcessingTest(ImageProcessingTestMixin, unittest.TestCase
         self.assertEqual(image_processor.size, {"shortest_edge": 42})
         self.assertEqual(image_processor.crop_size, {"height": 84, "width": 84})
 
-    @unittest.skip("ChineseCLIPImageProcessor doesn't treat 4 channel PIL and numpy consistently yet")  # FIXME Amy
+    @unittest.skip(
+        reason="ChineseCLIPImageProcessor doesn't treat 4 channel PIL and numpy consistently yet"
+    )  # FIXME Amy
     def test_call_numpy_4_channels(self):
         pass
 
@@ -155,14 +153,16 @@ class ChineseCLIPImageProcessingTestFourChannels(ImageProcessingTestMixin, unitt
         self.assertTrue(hasattr(image_processing, "image_std"))
         self.assertTrue(hasattr(image_processing, "do_convert_rgb"))
 
-    @unittest.skip("ChineseCLIPImageProcessor does not support 4 channels yet")  # FIXME Amy
+    @unittest.skip(reason="ChineseCLIPImageProcessor does not support 4 channels yet")  # FIXME Amy
     def test_call_numpy(self):
         return super().test_call_numpy()
 
-    @unittest.skip("ChineseCLIPImageProcessor does not support 4 channels yet")  # FIXME Amy
+    @unittest.skip(reason="ChineseCLIPImageProcessor does not support 4 channels yet")  # FIXME Amy
     def test_call_pytorch(self):
         return super().test_call_torch()
 
-    @unittest.skip("ChineseCLIPImageProcessor doesn't treat 4 channel PIL and numpy consistently yet")  # FIXME Amy
+    @unittest.skip(
+        reason="ChineseCLIPImageProcessor doesn't treat 4 channel PIL and numpy consistently yet"
+    )  # FIXME Amy
     def test_call_numpy_4_channels(self):
         pass

tests/models/chinese_clip/test_modeling_chinese_clip.py

@@ -388,9 +388,11 @@ class ChineseCLIPTextModelTest(ModelTesterMixin, unittest.TestCase):
         model = ChineseCLIPTextModel.from_pretrained(model_name)
         self.assertIsNotNone(model)
 
+    @unittest.skip
     def test_training(self):
         pass
 
+    @unittest.skip
     def test_training_gradient_checkpointing(self):
         pass
 
@@ -466,9 +468,11 @@ class ChineseCLIPVisionModelTest(ModelTesterMixin, unittest.TestCase):
         config_and_inputs = self.model_tester.prepare_config_and_inputs()
         self.model_tester.create_and_check_model(*config_and_inputs)
 
+    @unittest.skip
     def test_training(self):
         pass
 
+    @unittest.skip
     def test_training_gradient_checkpointing(self):
         pass
 
@@ -621,7 +625,7 @@ class ChineseCLIPModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestC
 
     def _create_and_check_torchscript(self, config, inputs_dict):
         if not self.test_torchscript:
-            return
+            self.skipTest(reason="test_torchscript is set to False")
 
         configs_no_init = _config_zero_init(config)  # To be sure we have no Nan
         configs_no_init.torchscript = True