🔥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/albert/test_modeling_albert.py

@@ -22,6 +22,7 @@ from transformers.testing_utils import require_torch, slow, torch_device
 
 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():
@@ -239,7 +240,7 @@ class AlbertModelTester:
 
 
 @require_torch
-class AlbertModelTest(ModelTesterMixin, unittest.TestCase):
+class AlbertModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
     all_model_classes = (
         (
             AlbertModel,
@@ -253,6 +254,18 @@ class AlbertModelTest(ModelTesterMixin, unittest.TestCase):
         if is_torch_available()
         else ()
     )
+    pipeline_model_mapping = (
+        {
+            "feature-extraction": AlbertModel,
+            "fill-mask": AlbertForMaskedLM,
+            "question-answering": AlbertForQuestionAnswering,
+            "text-classification": AlbertForSequenceClassification,
+            "token-classification": AlbertForTokenClassification,
+            "zero-shot": AlbertForSequenceClassification,
+        }
+        if is_torch_available()
+        else {}
+    )
     fx_compatible = True
 
     # special case for ForPreTraining model

tests/models/albert/test_modeling_tf_albert.py

@@ -22,6 +22,7 @@ from transformers.testing_utils import require_tf, slow
 
 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():
@@ -227,7 +228,7 @@ class TFAlbertModelTester:
 
 
 @require_tf
-class TFAlbertModelTest(TFModelTesterMixin, unittest.TestCase):
+class TFAlbertModelTest(TFModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
     all_model_classes = (
         (
             TFAlbertModel,
@@ -241,6 +242,18 @@ class TFAlbertModelTest(TFModelTesterMixin, unittest.TestCase):
         if is_tf_available()
         else ()
     )
+    pipeline_model_mapping = (
+        {
+            "feature-extraction": TFAlbertModel,
+            "fill-mask": TFAlbertForMaskedLM,
+            "question-answering": TFAlbertForQuestionAnswering,
+            "text-classification": TFAlbertForSequenceClassification,
+            "token-classification": TFAlbertForTokenClassification,
+            "zero-shot": TFAlbertForSequenceClassification,
+        }
+        if is_tf_available()
+        else {}
+    )
     test_head_masking = False
     test_onnx = False