[`core` / `Quantization`] Fix for 8bit serialization tests (#27234)

* fix for 8bit serialization

* added regression tests.

* fixup

src/transformers/modeling_utils.py

@@ -2110,7 +2110,13 @@ class PreTrainedModel(nn.Module, ModuleUtilsMixin, GenerationMixin, PushToHubMix
             # We're going to remove aliases before saving
             ptrs = collections.defaultdict(list)
             for name, tensor in state_dict.items():
-                ptrs[id_tensor_storage(tensor)].append(name)
+                # Sometimes in the state_dict we have non-tensor objects.
+                # e.g. in bitsandbytes we have some `str` objects in the state_dict
+                if isinstance(tensor, torch.Tensor):
+                    ptrs[id_tensor_storage(tensor)].append(name)
+                else:
+                    # In the non-tensor case, fall back to the pointer of the object itself
+                    ptrs[id(tensor)].append(name)
 
             # These are all the pointers of shared tensors.
             shared_ptrs = {ptr: names for ptr, names in ptrs.items() if len(names) > 1}

tests/quantization/bnb/test_mixed_int8.py

@@ -369,6 +369,33 @@ class MixedInt8Test(BaseMixedInt8Test):
                 self.tokenizer.decode(output_sequences[0], skip_special_tokens=True), self.EXPECTED_OUTPUT
             )
 
+    def test_int8_serialization_regression(self):
+        r"""
+        Test whether it is possible to serialize a model in 8-bit - using not safetensors
+        """
+        from bitsandbytes.nn import Int8Params
+
+        with tempfile.TemporaryDirectory() as tmpdirname:
+            self.model_8bit.save_pretrained(tmpdirname, safe_serialization=False)
+
+            # check that the file `quantization_config` is present
+            config = AutoConfig.from_pretrained(tmpdirname)
+            self.assertTrue(hasattr(config, "quantization_config"))
+
+            model_from_saved = AutoModelForCausalLM.from_pretrained(tmpdirname, load_in_8bit=True, device_map="auto")
+
+            linear = get_some_linear_layer(model_from_saved)
+            self.assertTrue(linear.weight.__class__ == Int8Params)
+            self.assertTrue(hasattr(linear.weight, "SCB"))
+
+            # generate
+            encoded_input = self.tokenizer(self.input_text, return_tensors="pt")
+            output_sequences = model_from_saved.generate(input_ids=encoded_input["input_ids"].to(0), max_new_tokens=10)
+
+            self.assertEqual(
+                self.tokenizer.decode(output_sequences[0], skip_special_tokens=True), self.EXPECTED_OUTPUT
+            )
+
     def test_int8_serialization_sharded(self):
         r"""
         Test whether it is possible to serialize a model in 8-bit - sharded version.