[cache] make all classes cache compatible finally (#38635)

* dump

* push other models

* fix simple greedy generation

* xmod

* add fmst and clean up some mentions of old cache format

* gpt-bigcode now follows standards

* delete tuple cache reference in generation

* fix some models

* fix some models

* fix mambas and support cache in tapas

* fix some more tests

* fix copies

* delete `_reorder_cache`

* another fix copies

* fix typos and delete unnecessary test

* fix rag generate, needs special cache reordering

* fix tapas and superglue

* reformer create special cache

* recurrent gemma `reorder_cache` was a no-op, delete

* fix-copies

* fix blio and musicgen pipeline tests

* fix reformer

* fix reformer, again...

* delete `_supports_cache_class`

* delete `supports_quantized_cache`

* fix failing tests

* fix copies

* some minor clean up

* style

* style

* fix copies

* fix tests

* fix copies

* create causal mask now needs positions?

* fixc copies

* style

* Update tests/test_modeling_common.py

Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* clean-up of non-generative model after merging main

* check `is_decoder` for cache

* delete transpose for scores

* remove tuple cache from docs everywhere

* fix tests

* fix copies

* fix copies once more

* properly deprecate `encoder_attention_mask` in Bert-like models

* import `deprecate_kwarg` where needed

* fix copies again

* fix copies

* delete `nex_decoder_cache`

* fix copies asks to update for PLM

* fix copies

* rebasing had a few new models, fix them and merge asap!

* fix copies once more

* fix slow tests

* fix tests and updare PLM checkpoint

* add read token and revert accidentally removed line

* oh com -on, style

* just skip it, read token has no access to PLM yet

---------

Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

tests/models/mllama/test_modeling_mllama.py

@@ -34,6 +34,7 @@ from transformers.testing_utils import (
     Expectations,
     cleanup,
     require_bitsandbytes,
+    require_optimum_quanto,
     require_read_token,
     require_torch,
     require_torch_accelerator,
@@ -344,6 +345,12 @@ class MllamaForConditionalGenerationModelTest(ModelTesterMixin, GenerationTester
 
             self.assertListEqual([layer_attention.shape for layer_attention in iter_attentions], expected_shapes)
 
+    @require_optimum_quanto
+    @pytest.mark.generate
+    @unittest.skip("Mllama is actually an encoder decoder cache and thus can't supports quant cache")
+    def test_generate_with_quant_cache(self):
+        pass
+
     @unittest.skip("For some unknown reasons the tests fails in CrossAttention layer when doing torch.sdpa(). ")
     def test_sdpa_can_compile_dynamic(self):
         pass