🔥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/wav2vec2_conformer/test_modeling_wav2vec2_conformer.py

@@ -31,6 +31,7 @@ from ...test_modeling_common import (
     ids_tensor,
     random_attention_mask,
 )
+from ...test_pipeline_mixin import PipelineTesterMixin
 
 
 if is_torch_available():
@@ -389,7 +390,7 @@ class Wav2Vec2ConformerModelTester:
 
 
 @require_torch
-class Wav2Vec2ConformerModelTest(ModelTesterMixin, unittest.TestCase):
+class Wav2Vec2ConformerModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
     all_model_classes = (
         (
             Wav2Vec2ConformerForCTC,
@@ -402,6 +403,15 @@ class Wav2Vec2ConformerModelTest(ModelTesterMixin, unittest.TestCase):
         if is_torch_available()
         else ()
     )
+    pipeline_model_mapping = (
+        {
+            "audio-classification": Wav2Vec2ConformerForSequenceClassification,
+            "automatic-speech-recognition": Wav2Vec2ConformerForCTC,
+            "feature-extraction": Wav2Vec2ConformerModel,
+        }
+        if is_torch_available()
+        else {}
+    )
     test_pruning = False
     test_headmasking = False
     test_torchscript = False