merge main in branch

Author: echarlaix

optimum/intel/openvino/modeling_decoder.py

@@ -70,22 +70,6 @@
     ```
 """
 
-_SUPPORTED_ARCHITECTURES = {
-    "bart",
-    "blenderbot",
-    "blenderbot-small",
-    "bloom",
-    "codegen",
-    "gpt2",
-    "gpt-bigcode",
-    "gpt-neo",
-    "gpt-neox",
-    "llama",
-    "marian",
-    "opt",
-    "pegasus",
-}
-
 
 @add_start_docstrings(
     """
@@ -247,11 +231,6 @@ def _from_transformers(
         quantization_config: Optional[Union[OVWeightQuantizationConfig, Dict]] = None,
         **kwargs,
     ):
-        if config.model_type.replace("_", "-") not in _SUPPORTED_ARCHITECTURES:
-            logger.warning(
-                f"This architecture : {config.model_type} was not validated, only :{', '.join(_SUPPORTED_ARCHITECTURES)} architectures were "
-                "validated, use at your own risk."
-            )
         save_dir = TemporaryDirectory()
         save_dir_path = Path(save_dir.name)
 

tests/openvino/test_modeling.py

@@ -502,6 +502,7 @@ class OVModelForCausalLMIntegrationTest(unittest.TestCase):
         "qwen2",
         "stablelm",
         "starcoder2",
+        "phi",
     )
     GENERATION_LENGTH = 100
     IS_SUPPORT_STATEFUL = is_openvino_version(">=", "2023.3")
@@ -532,6 +533,7 @@ def test_compare_to_transformers(self, model_arch):
         self.assertEqual(
             ov_model.stateful, self.IS_SUPPORT_STATEFUL and ov_model.config.model_type not in not_stateful
         )
+        set_seed(SEED)
         transformers_model = AutoModelForCausalLM.from_pretrained(model_id, **model_kwargs)
         tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=model_arch in self.REMOTE_CODE_MODELS)
         if model_arch == "qwen":

tests/openvino/utils_tests.py

@@ -70,6 +70,7 @@
     "nystromformer": "hf-internal-testing/tiny-random-NystromformerModel",
     "pegasus": "hf-internal-testing/tiny-random-pegasus",
     "pix2struct": "fxmarty/pix2struct-tiny-random",
+    "phi": "hf-internal-testing/tiny-random-PhiForCausalLM",
     "poolformer": "hf-internal-testing/tiny-random-PoolFormerModel",
     "qwen": "katuni4ka/tiny-random-qwen",
     "qwen2": "Qwen/Qwen1.5-0.5B",