Add TFBartForConditionalGeneration (#5411)

* half done

* doc improvement

* Cp test file

* brokedn

* broken test

* undo some mess

* ckpt

* borked

* Halfway

* 6 passing

* boom boom

* Much progress but still 6

* boom boom

* merged master

* 10 passing

* boom boom

* Style

* no t5 changes

* 13 passing

* Integration test failing, but not gibberish

* Frustrated

* Merged master

* 4 fail

* 4 fail

* fix return_dict

* boom boom

* Still only 4

* prepare method

* prepare method

* before delete classif

* Skip tests to avoid adding boilerplate

* boom boom

* fast tests passing

* style

* boom boom

* Switch to supporting many input types

* remove FIXMENORM

* working

* Fixed past_key_values/decoder_cached_states confusion

* new broken test

* Fix attention mask kwarg name

* undo accidental

* Style and reviewers

* style

* Docs and common tests

* Cleaner assert messages

* copy docs

* style issues

* Sphinx fix

* Simplify caching logic

* test does not require torch

* copy _NoLayerEmbedTokens

* Update src/transformers/modeling_tf_bart.py

Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Update tests/test_modeling_tf_bart.py

Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Update src/transformers/modeling_tf_bart.py

Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Update src/transformers/modeling_tf_bart.py

Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Update src/transformers/modeling_tf_bart.py

Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Line length and dont document None

* Add pipeline test coverage

* assert msg

* At parity

* Assert messages

* mark slow

* Update compile test

* back in init

* Merge master

* Fix tests

Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

tests/test_modeling_tf_t5.py

@@ -279,9 +279,8 @@ class TFT5ModelTest(TFModelTesterMixin, unittest.TestCase):
 
     @slow
     def test_model_from_pretrained(self):
-        for model_name in ["t5-small"]:
-            model = TFT5Model.from_pretrained(model_name)
-            self.assertIsNotNone(model)
+        model = TFT5Model.from_pretrained("t5-small")
+        self.assertIsNotNone(model)
 
 
 @require_tf