🔥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/flaubert/test_modeling_flaubert.py

@@ -21,6 +21,7 @@ from transformers.testing_utils import require_torch, require_torch_gpu, slow, t
 
 from ...test_configuration_common import ConfigTester
 from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
+from ...test_pipeline_mixin import PipelineTesterMixin
 
 
 if is_torch_available():
@@ -362,7 +363,7 @@ class FlaubertModelTester(object):
 
 
 @require_torch
-class FlaubertModelTest(ModelTesterMixin, unittest.TestCase):
+class FlaubertModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
     all_model_classes = (
         (
             FlaubertModel,
@@ -376,6 +377,18 @@ class FlaubertModelTest(ModelTesterMixin, unittest.TestCase):
         if is_torch_available()
         else ()
     )
+    pipeline_model_mapping = (
+        {
+            "feature-extraction": FlaubertModel,
+            "fill-mask": FlaubertWithLMHeadModel,
+            "question-answering": FlaubertForQuestionAnsweringSimple,
+            "text-classification": FlaubertForSequenceClassification,
+            "token-classification": FlaubertForTokenClassification,
+            "zero-shot": FlaubertForSequenceClassification,
+        }
+        if is_torch_available()
+        else {}
+    )
 
     # Flaubert has 2 QA models -> need to manually set the correct labels for one of them here
     def _prepare_for_class(self, inputs_dict, model_class, return_labels=False):

tests/models/flaubert/test_modeling_tf_flaubert.py

@@ -20,6 +20,7 @@ from transformers.testing_utils import require_sentencepiece, require_tf, requir
 
 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():
@@ -274,7 +275,7 @@ class TFFlaubertModelTester:
 
 
 @require_tf
-class TFFlaubertModelTest(TFModelTesterMixin, unittest.TestCase):
+class TFFlaubertModelTest(TFModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
     all_model_classes = (
         (
             TFFlaubertModel,
@@ -290,6 +291,18 @@ class TFFlaubertModelTest(TFModelTesterMixin, unittest.TestCase):
     all_generative_model_classes = (
         (TFFlaubertWithLMHeadModel,) if is_tf_available() else ()
     )  # TODO (PVP): Check other models whether language generation is also applicable
+    pipeline_model_mapping = (
+        {
+            "feature-extraction": TFFlaubertModel,
+            "fill-mask": TFFlaubertWithLMHeadModel,
+            "question-answering": TFFlaubertForQuestionAnsweringSimple,
+            "text-classification": TFFlaubertForSequenceClassification,
+            "token-classification": TFFlaubertForTokenClassification,
+            "zero-shot": TFFlaubertForSequenceClassification,
+        }
+        if is_tf_available()
+        else {}
+    )
     test_head_masking = False
     test_onnx = False