🔥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/t5/test_modeling_tf_t5.py

@@ -21,6 +21,7 @@ from transformers.utils import cached_property
 
 from ...test_configuration_common import ConfigTester
 from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
+from ...test_pipeline_mixin import PipelineTesterMixin
 
 
 if is_tf_available():
@@ -239,10 +240,20 @@ class TFT5ModelTester:
 
 
 @require_tf
-class TFT5ModelTest(TFModelTesterMixin, unittest.TestCase):
+class TFT5ModelTest(TFModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
     is_encoder_decoder = True
     all_model_classes = (TFT5Model, TFT5ForConditionalGeneration) if is_tf_available() else ()
     all_generative_model_classes = (TFT5ForConditionalGeneration,) if is_tf_available() else ()
+    pipeline_model_mapping = (
+        {
+            "conversational": TFT5ForConditionalGeneration,
+            "feature-extraction": TFT5Model,
+            "summarization": TFT5ForConditionalGeneration,
+            "text2text-generation": TFT5ForConditionalGeneration,
+        }
+        if is_tf_available()
+        else {}
+    )
     test_onnx = False
 
     def setUp(self):