[Deberta/Deberta-v2] Refactor code base to support compile, export,…

… and fix LLM (huggingface#22105)

* some modification for roadmap

* revert some changes

* yups

* weird

* make it work

* sttling

* fix-copies

* fixup

* renaming

* more fix-copies

* move stuff around

* remove torch script warnings

* ignore copies

* revert bad changes

* woops

* just styling

* nit

* revert

* style fixup

* nits configuration style

* fixup

* nits

* will this fix the tf pt issue?

* style

* ???????

* update

* eval?

* update error message

* updates

* style

* grumble grumble

* update

* style

* nit

* skip torch fx tests that were failing

* style

* skip the failing tests

* skip another test and make style

src/transformers/models/deberta/configuration_deberta.py

@@ -82,6 +82,9 @@ class DebertaConfig(PretrainedConfig):
             `["p2c", "c2p"]`.
         layer_norm_eps (`float`, *optional*, defaults to 1e-12):
             The epsilon used by the layer normalization layers.
+        legacy (`bool`, *optional*, defaults to `True`):
+            Whether or not the model should use the legacy `LegacyDebertaOnlyMLMHead`, which does not work properly
+            for mask infilling tasks.
 
     Example:
 
@@ -121,6 +124,7 @@ def __init__(
         pos_att_type=None,
         pooler_dropout=0,
         pooler_hidden_act="gelu",
+        legacy=True,
         **kwargs,
     ):
         super().__init__(**kwargs)
@@ -151,6 +155,7 @@ def __init__(
         self.pooler_hidden_size = kwargs.get("pooler_hidden_size", hidden_size)
         self.pooler_dropout = pooler_dropout
         self.pooler_hidden_act = pooler_hidden_act
+        self.legacy = legacy
 
 
 # Copied from transformers.models.deberta_v2.configuration_deberta_v2.DebertaV2OnnxConfig