Making camembert independent from roberta, clean (#19337)

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

src/transformers/__init__.py

@@ -1024,6 +1024,7 @@ else:
             "CamembertForSequenceClassification",
             "CamembertForTokenClassification",
             "CamembertModel",
+            "CamembertPreTrainedModel",
         ]
     )
     _import_structure["models.canine"].extend(
@@ -3873,6 +3874,7 @@ if TYPE_CHECKING:
             CamembertForSequenceClassification,
             CamembertForTokenClassification,
             CamembertModel,
+            CamembertPreTrainedModel,
         )
         from .models.canine import (
             CANINE_PRETRAINED_MODEL_ARCHIVE_LIST,

src/transformers/models/camembert/__init__.py

@@ -63,6 +63,7 @@ else:
         "CamembertForSequenceClassification",
         "CamembertForTokenClassification",
         "CamembertModel",
+        "CamembertPreTrainedModel",
     ]
 
 try:
@@ -117,6 +118,7 @@ if TYPE_CHECKING:
             CamembertForSequenceClassification,
             CamembertForTokenClassification,
             CamembertModel,
+            CamembertPreTrainedModel,
         )
 
     try:

src/transformers/utils/dummy_pt_objects.py

@@ -1093,6 +1093,13 @@ class CamembertModel(metaclass=DummyObject):
         requires_backends(self, ["torch"])
 
 
+class CamembertPreTrainedModel(metaclass=DummyObject):
+    _backends = ["torch"]
+
+    def __init__(self, *args, **kwargs):
+        requires_backends(self, ["torch"])
+
+
 CANINE_PRETRAINED_MODEL_ARCHIVE_LIST = None