Update save onnx in evaluation

Signed-off-by: Jael Gu <mengjia.gu@zilliz.com>

benchmark/run.py

@@ -122,7 +122,27 @@ elif args.format == 'onnx':
     collection_name = collection_name + '_onnx'
     saved_name = model_name.replace('/', '-')
     if not os.path.exists(onnx_path):
-        op.save_model(format='onnx', path=onnx_path[:-5])
+        try:
+            op.save_model(format='onnx', path=onnx_path[:-5])
+        except Exception:
+            inputs = op.tokenizer('This is test.', return_tensors='pt')
+            input_names = list(inputs.keys())
+            dynamic_axes = {}
+            for i_n in input_names:
+                dynamic_axes[i_n] = {0: 'batch_size', 1: 'sequence_length'}
+            output_names = ['last_hidden_state']
+            for o_n in output_names:
+                dynamic_axes[o_n] = {0: 'batch_size', 1: 'sequence_length'}
+            torch.onnx.export(
+                op.model,
+                tuple(inputs.values()),
+                onnx_path,
+                input_names=input_names,
+                output_names=output_names,
+                dynamic_axes=dynamic_axes,
+                opset_version=14,
+                do_constant_folding=True,
+                )
     sess = onnxruntime.InferenceSession(onnx_path,
                                         providers=onnxruntime.get_available_providers())