Fix compatibility causallm models export with optimum 1.15 (huggingfa…

…ce#487)

optimum/exporters/openvino/convert.py

@@ -31,7 +31,7 @@
 from optimum.exporters.onnx.model_patcher import DecoderModelPatcher
 from optimum.utils import is_diffusers_available
 
-from ...intel.utils.import_utils import is_nncf_available
+from ...intel.utils.import_utils import is_nncf_available, is_optimum_version
 from .utils import (
     OV_XML_FILE_NAME,
     clear_class_registry,
@@ -307,8 +307,10 @@ def export_pytorch(
             # model.config.torchscript = True can not be used for patching, because it overrides return_dict to Flase
             if custom_patcher or dict_inputs:
                 patcher = config.patch_model_for_export(model, model_kwargs=model_kwargs)
-                # DecoderModelPatcher does not override model forward
-                if isinstance(patcher, DecoderModelPatcher) or patcher.orig_forward_name != "forward":
+                # DecoderModelPatcher does not override model forward in optimum < 1.15
+                if (
+                    isinstance(patcher, DecoderModelPatcher) and is_optimum_version("<", "1.15.0")
+                ) or patcher.orig_forward_name != "forward":
                     patch_model_forward = True
                     patched_forward = model.forward
                 else:

optimum/intel/utils/import_utils.py

@@ -29,6 +29,7 @@
 
 STR_OPERATION_TO_FUNC = {">": op.gt, ">=": op.ge, "==": op.eq, "!=": op.ne, "<=": op.le, "<": op.lt}
 
+_optimum_version = importlib_metadata.version("optimum")
 
 _transformers_available = importlib.util.find_spec("transformers") is not None
 _transformers_version = "N/A"
@@ -175,6 +176,10 @@ def is_transformers_version(operation: str, version: str):
     return compare_versions(parse(_transformers_version), operation, version)
 
 
+def is_optimum_version(operation: str, version: str):
+    return compare_versions(parse(_optimum_version), operation, version)
+
+
 def is_neural_compressor_version(operation: str, version: str):
     """
     Compare the current Neural Compressor version to a given reference with an operation.