CI: avoid human error, automatically infer generative models (#33212)

* tmp commit

* move tests to the right class

* remove ALL all_generative_model_classes = ...

* skip tf roberta

* skip InstructBlipForConditionalGenerationDecoderOnlyTest

* videollava

* reduce diff

* reduce diff

* remove  on vlms

* fix a few more

* manual rebase bits

* more manual rebase

* remove all manual generative model class test entries

* fix up to ernie

* a few more removals

* handle remaining cases

* recurrent gemma

* it's better here

* make fixup

* tf idefics is broken

* tf bert + generate is broken

* don't touch tf :()

* don't touch tf :(

* make fixup

* better comments for test skips

* revert tf changes

* remove empty line removal

* one more

* missing one

tests/models/longt5/test_modeling_flax_longt5.py

@@ -237,7 +237,6 @@ class FlaxLongT5ModelTester:
 @require_flax
 class FlaxLongT5ModelTest(FlaxModelTesterMixin, FlaxGenerationTesterMixin, unittest.TestCase):
     all_model_classes = (FlaxLongT5Model, FlaxLongT5ForConditionalGeneration) if is_flax_available() else ()
-    all_generative_model_classes = (FlaxLongT5ForConditionalGeneration,) if is_flax_available() else ()
     is_encoder_decoder = True
 
     def setUp(self):

tests/models/longt5/test_modeling_longt5.py

@@ -502,7 +502,6 @@ class LongT5ModelTester:
 @require_torch
 class LongT5ModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMixin, unittest.TestCase):
     all_model_classes = (LongT5Model, LongT5ForConditionalGeneration) if is_torch_available() else ()
-    all_generative_model_classes = (LongT5ForConditionalGeneration,) if is_torch_available() else ()
     pipeline_model_mapping = (
         {
             "feature-extraction": LongT5Model,