Remove T5 dependency from mT5 model (#20949)

make mt5 independent from t5

src/transformers/__init__.py

@@ -1806,7 +1806,9 @@ else:
             "MPNetPreTrainedModel",
         ]
     )
-    _import_structure["models.mt5"].extend(["MT5EncoderModel", "MT5ForConditionalGeneration", "MT5Model"])
+    _import_structure["models.mt5"].extend(
+        ["MT5EncoderModel", "MT5ForConditionalGeneration", "MT5Model", "MT5PreTrainedModel"]
+    )
     _import_structure["models.mvp"].extend(
         [
             "MVP_PRETRAINED_MODEL_ARCHIVE_LIST",
@@ -4922,7 +4924,7 @@ if TYPE_CHECKING:
             MPNetModel,
             MPNetPreTrainedModel,
         )
-        from .models.mt5 import MT5EncoderModel, MT5ForConditionalGeneration, MT5Model
+        from .models.mt5 import MT5EncoderModel, MT5ForConditionalGeneration, MT5Model, MT5PreTrainedModel
         from .models.mvp import (
             MVP_PRETRAINED_MODEL_ARCHIVE_LIST,
             MvpForCausalLM,

src/transformers/models/mt5/__init__.py

@@ -51,7 +51,13 @@ try:
 except OptionalDependencyNotAvailable:
     pass
 else:
-    _import_structure["modeling_mt5"] = ["MT5EncoderModel", "MT5ForConditionalGeneration", "MT5Model"]
+    _import_structure["modeling_mt5"] = [
+        "MT5EncoderModel",
+        "MT5ForConditionalGeneration",
+        "MT5Model",
+        "MT5PreTrainedModel",
+        "MT5Stack",
+    ]
 
 try:
     if not is_tf_available():
@@ -79,7 +85,7 @@ if TYPE_CHECKING:
     except OptionalDependencyNotAvailable:
         pass
     else:
-        from .modeling_mt5 import MT5EncoderModel, MT5ForConditionalGeneration, MT5Model
+        from .modeling_mt5 import MT5EncoderModel, MT5ForConditionalGeneration, MT5Model, MT5PreTrainedModel, MT5Stack
 
     try:
         if not is_tf_available():

src/transformers/utils/dummy_pt_objects.py

@@ -4003,6 +4003,13 @@ class MT5Model(metaclass=DummyObject):
         requires_backends(self, ["torch"])
 
 
+class MT5PreTrainedModel(metaclass=DummyObject):
+    _backends = ["torch"]
+
+    def __init__(self, *args, **kwargs):
+        requires_backends(self, ["torch"])
+
+
 MVP_PRETRAINED_MODEL_ARCHIVE_LIST = None
 
 

utils/check_repo.py

@@ -40,6 +40,7 @@ PRIVATE_MODELS = [
     "LongT5Stack",
     "RealmBertModel",
     "T5Stack",
+    "MT5Stack",
     "SwitchTransformersStack",
     "TFDPRSpanPredictor",
     "MaskFormerSwinModel",