fix ort

optimum_benchmark/backends/onnxruntime/backend.py

@@ -6,7 +6,6 @@
 import torch
 from hydra.utils import get_class
 from onnxruntime import SessionOptions
-from optimum.exporters.onnx import MODEL_TYPES_REQUIRING_POSITION_IDS
 from optimum.onnxruntime import (
     ONNX_DECODER_NAME,
     ONNX_DECODER_WITH_PAST_NAME,
@@ -298,8 +297,11 @@ def prepare_inputs(self, inputs: Dict[str, Any]) -> Dict[str, Any]:
             with Accelerator().split_between_processes(inputs=inputs, apply_padding=False) as process_inputs:
                 inputs = process_inputs
 
-        if self.config.model_type not in MODEL_TYPES_REQUIRING_POSITION_IDS:
-            inputs.pop("position_ids", None)
+        if self.config.library == "transformers":
+            for key, value in list(inputs.items()):
+                if key in ["position_ids", "token_type_ids"]:
+                    if key not in self.pretrained_model.input_names:
+                        inputs.pop(key)
 
         for key, value in inputs.items():
             if isinstance(value, torch.Tensor):

optimum_benchmark/scenarios/inference/scenario.py

@@ -85,11 +85,12 @@ def run(self, backend: Backend[BackendConfigT]) -> BenchmarkReport:
 
         self.logger.info("\t+ Preparing input shapes for Inference")
         self.config.input_shapes = backend.prepare_input_shapes(input_shapes=self.config.input_shapes)
-        self.logger.info("\t+ Preparing inputs for Inference")
-        self.inputs = backend.prepare_inputs(inputs=self.inputs)
 
         self.run_model_loading_tracking(backend)
 
+        self.logger.info("\t+ Preparing inputs for Inference")
+        self.inputs = backend.prepare_inputs(inputs=self.inputs)
+
         if self.config.memory:
             if backend.config.task in TEXT_GENERATION_TASKS:
                 self.run_text_generation_memory_tracking(backend)