🔥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
 

tests/models/altclip/test_modeling_altclip.py

@@ -35,6 +35,7 @@ from ...test_modeling_common import (
     ids_tensor,
     random_attention_mask,
 )
+from ...test_pipeline_mixin import PipelineTesterMixin
 
 
 if is_torch_available():
@@ -392,8 +393,9 @@ def prepare_img():
 
 
 @require_torch
-class AltCLIPModelTest(ModelTesterMixin, unittest.TestCase):
+class AltCLIPModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
     all_model_classes = (AltCLIPModel,) if is_torch_available() else ()
+    pipeline_model_mapping = {"feature-extraction": AltCLIPModel} if is_torch_available() else {}
     fx_compatible = True
     test_head_masking = False
     test_pruning = False

tests/models/audio_spectrogram_transformer/test_modeling_audio_spectrogram_transformer.py

@@ -25,6 +25,7 @@ from transformers.utils import cached_property, is_torch_available, is_torchaudi
 
 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():
@@ -140,7 +141,7 @@ class ASTModelTester:
 
 
 @require_torch
-class ASTModelTest(ModelTesterMixin, unittest.TestCase):
+class ASTModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
     """
     Here we also overwrite some of the tests of test_modeling_common.py, as AST does not use input_ids, inputs_embeds,
     attention_mask and seq_length.
@@ -154,6 +155,11 @@ class ASTModelTest(ModelTesterMixin, unittest.TestCase):
         if is_torch_available()
         else ()
     )
+    pipeline_model_mapping = (
+        {"audio-classification": ASTForAudioClassification, "feature-extraction": ASTModel}
+        if is_torch_available()
+        else {}
+    )
     fx_compatible = False
     test_pruning = False
     test_resize_embeddings = False

tests/models/bart/test_modeling_bart.py

@@ -28,6 +28,7 @@ from transformers.utils import cached_property
 from ...generation.test_utils import GenerationTesterMixin
 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():
@@ -414,13 +415,28 @@ class BartHeadTests(unittest.TestCase):
 
 
 @require_torch
-class BartModelTest(ModelTesterMixin, GenerationTesterMixin, unittest.TestCase):
+class BartModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMixin, unittest.TestCase):
     all_model_classes = (
         (BartModel, BartForConditionalGeneration, BartForSequenceClassification, BartForQuestionAnswering)
         if is_torch_available()
         else ()
     )
     all_generative_model_classes = (BartForConditionalGeneration,) if is_torch_available() else ()
+    pipeline_model_mapping = (
+        {
+            "conversational": BartForConditionalGeneration,
+            "feature-extraction": BartModel,
+            "fill-mask": BartForConditionalGeneration,
+            "question-answering": BartForQuestionAnswering,
+            "summarization": BartForConditionalGeneration,
+            "text2text-generation": BartForConditionalGeneration,
+            "text-classification": BartForSequenceClassification,
+            "text-generation": BartForCausalLM,
+            "zero-shot": BartForSequenceClassification,
+        }
+        if is_torch_available()
+        else {}
+    )
     is_encoder_decoder = True
     fx_compatible = False  # Fix me Michael
     test_pruning = False

tests/models/bart/test_modeling_tf_bart.py

@@ -25,6 +25,7 @@ from transformers.utils import cached_property
 
 from ...test_configuration_common import ConfigTester
 from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor
+from ...test_pipeline_mixin import PipelineTesterMixin
 from ...utils.test_modeling_tf_core import TFCoreModelTesterMixin
 
 
@@ -188,11 +189,23 @@ def prepare_bart_inputs_dict(
 
 
 @require_tf
-class TFBartModelTest(TFModelTesterMixin, TFCoreModelTesterMixin, unittest.TestCase):
+class TFBartModelTest(TFModelTesterMixin, TFCoreModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
     all_model_classes = (
         (TFBartForConditionalGeneration, TFBartForSequenceClassification, TFBartModel) if is_tf_available() else ()
     )
     all_generative_model_classes = (TFBartForConditionalGeneration,) if is_tf_available() else ()
+    pipeline_model_mapping = (
+        {
+            "conversational": TFBartForConditionalGeneration,
+            "feature-extraction": TFBartModel,
+            "summarization": TFBartForConditionalGeneration,
+            "text2text-generation": TFBartForConditionalGeneration,
+            "text-classification": TFBartForSequenceClassification,
+            "zero-shot": TFBartForSequenceClassification,
+        }
+        if is_tf_available()
+        else {}
+    )
     is_encoder_decoder = True
     test_pruning = False
     test_onnx = True

tests/models/beit/test_modeling_beit.py

@@ -28,6 +28,7 @@ from transformers.utils import cached_property, is_torch_available, is_vision_av
 
 from ...test_configuration_common import ConfigTester
 from ...test_modeling_common import ModelTesterMixin, _config_zero_init, floats_tensor, ids_tensor
+from ...test_pipeline_mixin import PipelineTesterMixin
 
 
 if is_torch_available():
@@ -185,7 +186,7 @@ class BeitModelTester:
 
 
 @require_torch
-class BeitModelTest(ModelTesterMixin, unittest.TestCase):
+class BeitModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
     """
     Here we also overwrite some of the tests of test_modeling_common.py, as BEiT does not use input_ids, inputs_embeds,
     attention_mask and seq_length.
@@ -196,6 +197,15 @@ class BeitModelTest(ModelTesterMixin, unittest.TestCase):
         if is_torch_available()
         else ()
     )
+    pipeline_model_mapping = (
+        {
+            "feature-extraction": BeitModel,
+            "image-classification": BeitForImageClassification,
+            "image-segmentation": BeitForSemanticSegmentation,
+        }
+        if is_torch_available()
+        else {}
+    )
 
     test_pruning = False
     test_resize_embeddings = False

tests/models/bert/test_modeling_bert.py

@@ -23,6 +23,7 @@ from transformers.testing_utils import require_torch, require_torch_gpu, slow, t
 from ...generation.test_utils import GenerationTesterMixin
 from ...test_configuration_common import ConfigTester
 from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
+from ...test_pipeline_mixin import PipelineTesterMixin
 
 
 if is_torch_available():
@@ -426,7 +427,7 @@ class BertModelTester:
 
 
 @require_torch
-class BertModelTest(ModelTesterMixin, GenerationTesterMixin, unittest.TestCase):
+class BertModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMixin, unittest.TestCase):
     all_model_classes = (
         (
             BertModel,
@@ -443,6 +444,19 @@ class BertModelTest(ModelTesterMixin, GenerationTesterMixin, unittest.TestCase):
         else ()
     )
     all_generative_model_classes = (BertLMHeadModel,) if is_torch_available() else ()
+    pipeline_model_mapping = (
+        {
+            "feature-extraction": BertModel,
+            "fill-mask": BertForMaskedLM,
+            "question-answering": BertForQuestionAnswering,
+            "text-classification": BertForSequenceClassification,
+            "text-generation": BertLMHeadModel,
+            "token-classification": BertForTokenClassification,
+            "zero-shot": BertForSequenceClassification,
+        }
+        if is_torch_available()
+        else {}
+    )
     fx_compatible = True
 
     # special case for ForPreTraining model

tests/models/bert/test_modeling_tf_bert.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, floats_tensor, ids_tensor, random_attention_mask
+from ...test_pipeline_mixin import PipelineTesterMixin
 from ...utils.test_modeling_tf_core import TFCoreModelTesterMixin
 
 
@@ -590,7 +591,7 @@ class TFBertModelTester:
 
 
 @require_tf
-class TFBertModelTest(TFModelTesterMixin, TFCoreModelTesterMixin, unittest.TestCase):
+class TFBertModelTest(TFModelTesterMixin, TFCoreModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
     all_model_classes = (
         (
             TFBertModel,
@@ -606,6 +607,19 @@ class TFBertModelTest(TFModelTesterMixin, TFCoreModelTesterMixin, unittest.TestC
         if is_tf_available()
         else ()
     )
+    pipeline_model_mapping = (
+        {
+            "feature-extraction": TFBertModel,
+            "fill-mask": TFBertForMaskedLM,
+            "question-answering": TFBertForQuestionAnswering,
+            "text-classification": TFBertForSequenceClassification,
+            "text-generation": TFBertLMHeadModel,
+            "token-classification": TFBertForTokenClassification,
+            "zero-shot": TFBertForSequenceClassification,
+        }
+        if is_tf_available()
+        else {}
+    )
     test_head_masking = False
     test_onnx = True
     onnx_min_opset = 10

tests/models/bert_generation/test_modeling_bert_generation.py

@@ -22,6 +22,7 @@ from transformers.testing_utils import require_torch, slow, torch_device
 from ...generation.test_utils import GenerationTesterMixin
 from ...test_configuration_common import ConfigTester
 from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
+from ...test_pipeline_mixin import PipelineTesterMixin
 
 
 if is_torch_available():
@@ -240,9 +241,14 @@ class BertGenerationEncoderTester:
 
 
 @require_torch
-class BertGenerationEncoderTest(ModelTesterMixin, GenerationTesterMixin, unittest.TestCase):
+class BertGenerationEncoderTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMixin, unittest.TestCase):
     all_model_classes = (BertGenerationEncoder, BertGenerationDecoder) if is_torch_available() else ()
     all_generative_model_classes = (BertGenerationDecoder,) if is_torch_available() else ()
+    pipeline_model_mapping = (
+        {"feature-extraction": BertGenerationEncoder, "text-generation": BertGenerationDecoder}
+        if is_torch_available()
+        else {}
+    )
 
     def setUp(self):
         self.model_tester = BertGenerationEncoderTester(self)

tests/models/big_bird/test_modeling_big_bird.py

@@ -24,6 +24,7 @@ from transformers.testing_utils import require_torch, slow, torch_device
 
 from ...test_configuration_common import ConfigTester
 from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
+from ...test_pipeline_mixin import PipelineTesterMixin
 
 
 if is_torch_available():
@@ -429,7 +430,7 @@ class BigBirdModelTester:
 
 
 @require_torch
-class BigBirdModelTest(ModelTesterMixin, unittest.TestCase):
+class BigBirdModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
     # head masking & pruning is currently not supported for big bird
     test_head_masking = False
     test_pruning = False
@@ -453,6 +454,19 @@ class BigBirdModelTest(ModelTesterMixin, unittest.TestCase):
         else ()
     )
     all_generative_model_classes = (BigBirdForCausalLM,) if is_torch_available() else ()
+    pipeline_model_mapping = (
+        {
+            "feature-extraction": BigBirdModel,
+            "fill-mask": BigBirdForMaskedLM,
+            "question-answering": BigBirdForQuestionAnswering,
+            "text-classification": BigBirdForSequenceClassification,
+            "text-generation": BigBirdForCausalLM,
+            "token-classification": BigBirdForTokenClassification,
+            "zero-shot": BigBirdForSequenceClassification,
+        }
+        if is_torch_available()
+        else {}
+    )
 
     # special case for ForPreTraining model
     def _prepare_for_class(self, inputs_dict, model_class, return_labels=False):

tests/models/bigbird_pegasus/test_modeling_bigbird_pegasus.py

@@ -25,6 +25,7 @@ from transformers.testing_utils import require_sentencepiece, require_tokenizers
 from ...generation.test_utils import GenerationTesterMixin
 from ...test_configuration_common import ConfigTester
 from ...test_modeling_common import ModelTesterMixin, ids_tensor
+from ...test_pipeline_mixin import PipelineTesterMixin
 
 
 if is_torch_available():
@@ -232,7 +233,7 @@ class BigBirdPegasusModelTester:
 
 
 @require_torch
-class BigBirdPegasusModelTest(ModelTesterMixin, GenerationTesterMixin, unittest.TestCase):
+class BigBirdPegasusModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMixin, unittest.TestCase):
     all_model_classes = (
         (
             BigBirdPegasusModel,
@@ -244,6 +245,20 @@ class BigBirdPegasusModelTest(ModelTesterMixin, GenerationTesterMixin, unittest.
         else ()
     )
     all_generative_model_classes = (BigBirdPegasusForConditionalGeneration,) if is_torch_available() else ()
+    pipeline_model_mapping = (
+        {
+            "conversational": BigBirdPegasusForConditionalGeneration,
+            "feature-extraction": BigBirdPegasusModel,
+            "question-answering": BigBirdPegasusForQuestionAnswering,
+            "summarization": BigBirdPegasusForConditionalGeneration,
+            "text2text-generation": BigBirdPegasusForConditionalGeneration,
+            "text-classification": BigBirdPegasusForSequenceClassification,
+            "text-generation": BigBirdPegasusForCausalLM,
+            "zero-shot": BigBirdPegasusForSequenceClassification,
+        }
+        if is_torch_available()
+        else {}
+    )
     is_encoder_decoder = True
     test_missing_keys = False
     test_pruning = False

tests/models/biogpt/test_modeling_biogpt.py

@@ -23,6 +23,7 @@ from transformers.testing_utils import require_torch, slow, torch_device
 from ...generation.test_utils import GenerationTesterMixin
 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():
@@ -262,9 +263,12 @@ class BioGptModelTester:
 
 
 @require_torch
-class BioGptModelTest(ModelTesterMixin, GenerationTesterMixin, unittest.TestCase):
+class BioGptModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMixin, unittest.TestCase):
     all_model_classes = (BioGptModel, BioGptForCausalLM) if is_torch_available() else ()
     all_generative_model_classes = (BioGptForCausalLM,) if is_torch_available() else ()
+    pipeline_model_mapping = (
+        {"feature-extraction": BioGptModel, "text-generation": BioGptForCausalLM} if is_torch_available() else {}
+    )
     test_pruning = False
 
     def setUp(self):

tests/models/bit/test_modeling_bit.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():
@@ -150,13 +151,18 @@ class BitModelTester:
 
 
 @require_torch
-class BitModelTest(ModelTesterMixin, unittest.TestCase):
+class BitModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
     """
     Here we also overwrite some of the tests of test_modeling_common.py, as Bit does not use input_ids, inputs_embeds,
     attention_mask and seq_length.
     """
 
     all_model_classes = (BitModel, BitForImageClassification, BitBackbone) if is_torch_available() else ()
+    pipeline_model_mapping = (
+        {"feature-extraction": BitModel, "image-classification": BitForImageClassification}
+        if is_torch_available()
+        else {}
+    )
 
     fx_compatible = False
     test_pruning = False

tests/models/blenderbot/test_modeling_blenderbot.py

@@ -24,6 +24,7 @@ from transformers.utils import cached_property
 from ...generation.test_utils import GenerationTesterMixin
 from ...test_configuration_common import ConfigTester
 from ...test_modeling_common import ModelTesterMixin, ids_tensor
+from ...test_pipeline_mixin import PipelineTesterMixin
 
 
 if is_torch_available():
@@ -223,9 +224,20 @@ class BlenderbotModelTester:
 
 
 @require_torch
-class BlenderbotModelTest(ModelTesterMixin, GenerationTesterMixin, unittest.TestCase):
+class BlenderbotModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMixin, unittest.TestCase):
     all_model_classes = (BlenderbotModel, BlenderbotForConditionalGeneration) if is_torch_available() else ()
     all_generative_model_classes = (BlenderbotForConditionalGeneration,) if is_torch_available() else ()
+    pipeline_model_mapping = (
+        {
+            "conversational": BlenderbotForConditionalGeneration,
+            "feature-extraction": BlenderbotModel,
+            "summarization": BlenderbotForConditionalGeneration,
+            "text2text-generation": BlenderbotForConditionalGeneration,
+            "text-generation": BlenderbotForCausalLM,
+        }
+        if is_torch_available()
+        else {}
+    )
     is_encoder_decoder = True
     fx_compatible = True
     test_pruning = False

tests/models/blenderbot/test_modeling_tf_blenderbot.py

@@ -22,6 +22,7 @@ from transformers.utils import cached_property
 
 from ...test_configuration_common import ConfigTester
 from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor
+from ...test_pipeline_mixin import PipelineTesterMixin
 
 
 if is_tf_available():
@@ -175,9 +176,19 @@ def prepare_blenderbot_inputs_dict(
 
 
 @require_tf
-class TFBlenderbotModelTest(TFModelTesterMixin, unittest.TestCase):
+class TFBlenderbotModelTest(TFModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
     all_model_classes = (TFBlenderbotForConditionalGeneration, TFBlenderbotModel) if is_tf_available() else ()
     all_generative_model_classes = (TFBlenderbotForConditionalGeneration,) if is_tf_available() else ()
+    pipeline_model_mapping = (
+        {
+            "conversational": TFBlenderbotForConditionalGeneration,
+            "feature-extraction": TFBlenderbotModel,
+            "summarization": TFBlenderbotForConditionalGeneration,
+            "text2text-generation": TFBlenderbotForConditionalGeneration,
+        }
+        if is_tf_available()
+        else {}
+    )
     is_encoder_decoder = True
     test_pruning = False
     test_onnx = False

tests/models/blenderbot_small/test_modeling_blenderbot_small.py

@@ -24,6 +24,7 @@ from transformers.utils import cached_property
 from ...generation.test_utils import GenerationTesterMixin
 from ...test_configuration_common import ConfigTester
 from ...test_modeling_common import ModelTesterMixin, ids_tensor
+from ...test_pipeline_mixin import PipelineTesterMixin
 
 
 if is_torch_available():
@@ -217,9 +218,20 @@ class BlenderbotSmallModelTester:
 
 
 @require_torch
-class BlenderbotSmallModelTest(ModelTesterMixin, GenerationTesterMixin, unittest.TestCase):
+class BlenderbotSmallModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMixin, unittest.TestCase):
     all_model_classes = (BlenderbotSmallModel, BlenderbotSmallForConditionalGeneration) if is_torch_available() else ()
     all_generative_model_classes = (BlenderbotSmallForConditionalGeneration,) if is_torch_available() else ()
+    pipeline_model_mapping = (
+        {
+            "conversational": BlenderbotSmallForConditionalGeneration,
+            "feature-extraction": BlenderbotSmallModel,
+            "summarization": BlenderbotSmallForConditionalGeneration,
+            "text2text-generation": BlenderbotSmallForConditionalGeneration,
+            "text-generation": BlenderbotSmallForCausalLM,
+        }
+        if is_torch_available()
+        else {}
+    )
     is_encoder_decoder = True
     fx_compatible = True
     test_pruning = False

tests/models/blenderbot_small/test_modeling_tf_blenderbot_small.py

@@ -22,6 +22,7 @@ from transformers.utils import cached_property
 
 from ...test_configuration_common import ConfigTester
 from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor
+from ...test_pipeline_mixin import PipelineTesterMixin
 
 
 if is_tf_available():
@@ -175,11 +176,21 @@ def prepare_blenderbot_small_inputs_dict(
 
 
 @require_tf
-class TFBlenderbotSmallModelTest(TFModelTesterMixin, unittest.TestCase):
+class TFBlenderbotSmallModelTest(TFModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
     all_model_classes = (
         (TFBlenderbotSmallForConditionalGeneration, TFBlenderbotSmallModel) if is_tf_available() else ()
     )
     all_generative_model_classes = (TFBlenderbotSmallForConditionalGeneration,) if is_tf_available() else ()
+    pipeline_model_mapping = (
+        {
+            "conversational": TFBlenderbotSmallForConditionalGeneration,
+            "feature-extraction": TFBlenderbotSmallModel,
+            "summarization": TFBlenderbotSmallForConditionalGeneration,
+            "text2text-generation": TFBlenderbotSmallForConditionalGeneration,
+        }
+        if is_tf_available()
+        else {}
+    )
     is_encoder_decoder = True
     test_pruning = False
     test_onnx = False

tests/models/blip/test_modeling_blip.py

@@ -35,6 +35,7 @@ from ...test_modeling_common import (
     ids_tensor,
     random_attention_mask,
 )
+from ...test_pipeline_mixin import PipelineTesterMixin
 
 
 if is_torch_available():
@@ -391,8 +392,9 @@ class BlipModelTester:
 
 
 @require_torch
-class BlipModelTest(ModelTesterMixin, unittest.TestCase):
+class BlipModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
     all_model_classes = (BlipModel,) if is_torch_available() else ()
+    pipeline_model_mapping = {"feature-extraction": BlipModel} if is_torch_available() else {}
     fx_compatible = False
     test_head_masking = False
     test_pruning = False

tests/models/bloom/test_modeling_bloom.py

@@ -23,6 +23,7 @@ from transformers.testing_utils import require_torch, require_torch_gpu, slow, t
 from ...generation.test_utils import GenerationTesterMixin
 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():
@@ -319,7 +320,7 @@ class BloomModelTester:
 
 
 @require_torch
-class BloomModelTest(ModelTesterMixin, GenerationTesterMixin, unittest.TestCase):
+class BloomModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMixin, unittest.TestCase):
     all_model_classes = (
         (
             BloomModel,
@@ -333,6 +334,18 @@ class BloomModelTest(ModelTesterMixin, GenerationTesterMixin, unittest.TestCase)
     )
 
     all_generative_model_classes = (BloomForCausalLM,) if is_torch_available() else ()
+    pipeline_model_mapping = (
+        {
+            "feature-extraction": BloomModel,
+            "question-answering": BloomForQuestionAnswering,
+            "text-classification": BloomForSequenceClassification,
+            "text-generation": BloomForCausalLM,
+            "token-classification": BloomForTokenClassification,
+            "zero-shot": BloomForSequenceClassification,
+        }
+        if is_torch_available()
+        else {}
+    )
     fx_compatible = True
     test_missing_keys = False
     test_pruning = False