🔥Rework pipeline testing by removing PipelineTestCaseMeta 🚀 (#21516)

* Add PipelineTesterMixin

* remove class PipelineTestCaseMeta

* move validate_test_components

* Add for ViT

* Add to SPECIAL_MODULE_TO_TEST_MAP

* style and quality

* Add feature-extraction

* update

* raise instead of skip

* add tiny_model_summary.json

* more explicit

* skip tasks not in mapping

* add availability check

* Add Copyright

* A way to diable irrelevant tests

* update with main

* remove disable_irrelevant_tests

* skip tests

* better skip message

* better skip message

* Add all pipeline task tests

* revert

* Import PipelineTesterMixin

* subclass test classes with PipelineTesterMixin

* Add pipieline_model_mapping

* Fix import after adding pipieline_model_mapping

* Fix style and quality after adding pipieline_model_mapping

* Fix one more import after adding pipieline_model_mapping

* Fix style and quality after adding pipieline_model_mapping

* Fix test issues

* Fix import requirements

* Fix mapping for MobileViTModelTest

* Update

* Better skip message

* pipieline_model_mapping could not be None

* Remove some PipelineTesterMixin

* Fix typo

* revert tests_fetcher.py

* update

* rename

* revert

* Remove PipelineTestCaseMeta from ZeroShotAudioClassificationPipelineTests

* style and quality

* test fetcher for all pipeline/model tests

---------

Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

tests/models/mobilevit/test_modeling_mobilevit.py

@@ -24,6 +24,7 @@ from transformers.utils import cached_property, is_torch_available, is_vision_av
 
 from ...test_configuration_common import ConfigTester
 from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor
+from ...test_pipeline_mixin import PipelineTesterMixin
 
 
 if is_torch_available():
@@ -173,7 +174,7 @@ class MobileViTModelTester:
 
 
 @require_torch
-class MobileViTModelTest(ModelTesterMixin, unittest.TestCase):
+class MobileViTModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
     """
     Here we also overwrite some of the tests of test_modeling_common.py, as MobileViT does not use input_ids, inputs_embeds,
     attention_mask and seq_length.
@@ -184,6 +185,15 @@ class MobileViTModelTest(ModelTesterMixin, unittest.TestCase):
         if is_torch_available()
         else ()
     )
+    pipeline_model_mapping = (
+        {
+            "feature-extraction": MobileViTModel,
+            "image-classification": MobileViTForImageClassification,
+            "image-segmentation": MobileViTForSemanticSegmentation,
+        }
+        if is_torch_available()
+        else {}
+    )
 
     test_pruning = False
     test_resize_embeddings = False

tests/models/mobilevit/test_modeling_tf_mobilevit.py

@@ -24,6 +24,7 @@ from transformers.testing_utils import require_tf, slow
 
 from ...test_configuration_common import ConfigTester
 from ...test_modeling_tf_common import TFModelTesterMixin, floats_tensor, ids_tensor
+from ...test_pipeline_mixin import PipelineTesterMixin
 
 
 if is_tf_available():
@@ -154,7 +155,7 @@ class TFMobileViTModelTester:
 
 
 @require_tf
-class TFMobileViTModelTest(TFModelTesterMixin, unittest.TestCase):
+class TFMobileViTModelTest(TFModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
     """
     Here we also overwrite some of the tests of test_modeling_common.py, as MobileViT does not use input_ids, inputs_embeds,
     attention_mask and seq_length.
@@ -165,6 +166,11 @@ class TFMobileViTModelTest(TFModelTesterMixin, unittest.TestCase):
         if is_tf_available()
         else ()
     )
+    pipeline_model_mapping = (
+        {"feature-extraction": TFMobileViTModel, "image-classification": TFMobileViTForImageClassification}
+        if is_tf_available()
+        else {}
+    )
 
     test_pruning = False
     test_resize_embeddings = False