[BNB] Throw `ValueError` when trying to cast or assign (#20409)

* `bnb` ValueError when tries to cast or assign

* Apply suggestions from code review

Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* remove docstrings

* change error log

Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

src/transformers/modeling_utils.py

@@ -1666,6 +1666,36 @@ class PreTrainedModel(nn.Module, ModuleUtilsMixin, GenerationMixin, PushToHubMix
             mem = mem + mem_bufs
         return mem
 
+    def to(self, *args, **kwargs):
+        # Checks if the model has been loaded in 8-bit
+        if getattr(self, "is_loaded_in_8bit", False):
+            raise ValueError(
+                "`.to` is not supported for `8-bit` models. Please use the model as it is, since the"
+                " model has already been set to the correct devices and casted to the correct `dtype`."
+            )
+        else:
+            return super().to(*args, **kwargs)
+
+    def half(self, *args):
+        # Checks if the model has been loaded in 8-bit
+        if getattr(self, "is_loaded_in_8bit", False):
+            raise ValueError(
+                "`.half()` is not supported for `8-bit` models. Please use the model as it is, since the"
+                " model has already been casted to the correct `dtype`."
+            )
+        else:
+            return super().half(*args)
+
+    def float(self, *args):
+        # Checks if the model has been loaded in 8-bit
+        if getattr(self, "is_loaded_in_8bit", False):
+            raise ValueError(
+                "`.float()` is not supported for `8-bit` models. Please use the model as it is, since the"
+                " model has already been casted to the correct `dtype`."
+            )
+        else:
+            return super().float(*args)
+
     @classmethod
     def from_pretrained(cls, pretrained_model_name_or_path: Optional[Union[str, os.PathLike]], *model_args, **kwargs):
         r"""

tests/mixed_int8/test_mixed_int8.py

@@ -115,6 +115,46 @@ class MixedInt8Test(BaseMixedInt8Test):
         with self.assertWarns(UserWarning), tempfile.TemporaryDirectory() as tmpdirname:
             self.model_8bit.save_pretrained(tmpdirname)
 
+    def test_device_and_dtype_assignment(self):
+        r"""
+        Test whether trying to cast (or assigning a device to) a model after converting it in 8-bit will throw an error.
+        Checks also if other models are casted correctly.
+        """
+        with self.assertRaises(ValueError):
+            # Tries with `str`
+            self.model_8bit.to("cpu")
+
+        with self.assertRaises(ValueError):
+            # Tries with a `dtype``
+            self.model_8bit.to(torch.float16)
+
+        with self.assertRaises(ValueError):
+            # Tries with a `device`
+            self.model_8bit.to(torch.device("cuda:0"))
+
+        with self.assertRaises(ValueError):
+            # Tries with a `device`
+            self.model_8bit.float()
+
+        with self.assertRaises(ValueError):
+            # Tries with a `device`
+            self.model_8bit.half()
+
+        # Test if we did not break anything
+        encoded_input = self.tokenizer(self.input_text, return_tensors="pt")
+
+        self.model_fp16 = self.model_fp16.to(torch.float32)
+        _ = self.model_fp16.generate(input_ids=encoded_input["input_ids"].to(0), max_new_tokens=10)
+
+        # Check this does not throw an error
+        _ = self.model_fp16.to("cpu")
+
+        # Check this does not throw an error
+        _ = self.model_fp16.half()
+
+        # Check this does not throw an error
+        _ = self.model_fp16.float()
+
 
 class MixedInt8ModelClassesTest(BaseMixedInt8Test):
     def setUp(self):