Make Camembert TF version independent from Roberta (#19364)

* camembert tf version independent

* fixup

* fixup, all working

* remove comments

* Adding copied from roberta

Co-authored-by: Mustapha AJEGHRIR <mustapha.ajeghrir@kleegroup.com>

src/transformers/__init__.py

@@ -2314,6 +2314,7 @@ else:
             "TFCamembertForSequenceClassification",
             "TFCamembertForTokenClassification",
             "TFCamembertModel",
+            "TFCamembertPreTrainedModel",
         ]
     )
     _import_structure["models.clip"].extend(
@@ -4981,6 +4982,7 @@ if TYPE_CHECKING:
             TFCamembertForSequenceClassification,
             TFCamembertForTokenClassification,
             TFCamembertModel,
+            TFCamembertPreTrainedModel,
         )
         from .models.clip import (
             TF_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST,

src/transformers/models/camembert/__init__.py

@@ -81,6 +81,7 @@ else:
         "TFCamembertForSequenceClassification",
         "TFCamembertForTokenClassification",
         "TFCamembertModel",
+        "TFCamembertPreTrainedModel",
     ]
 
 
@@ -136,6 +137,7 @@ if TYPE_CHECKING:
             TFCamembertForSequenceClassification,
             TFCamembertForTokenClassification,
             TFCamembertModel,
+            TFCamembertPreTrainedModel,
         )
 
 else:

src/transformers/utils/dummy_tf_objects.py

@@ -637,6 +637,13 @@ class TFCamembertModel(metaclass=DummyObject):
         requires_backends(self, ["tf"])
 
 
+class TFCamembertPreTrainedModel(metaclass=DummyObject):
+    _backends = ["tf"]
+
+    def __init__(self, *args, **kwargs):
+        requires_backends(self, ["tf"])
+
+
 TF_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST = None