diff --git a/mmseg/models/segmentors/base.py b/mmseg/models/segmentors/base.py
index 3ce25ac..2d5ea23 100644
--- a/mmseg/models/segmentors/base.py
+++ b/mmseg/models/segmentors/base.py
@@ -307,13 +307,14 @@ class ONNXRuntimeSegmentorKN(BaseSegmentor):
         # register custom op for onnxruntime
         if osp.exists(ort_custom_op_path):
             session_options.register_custom_ops_library(ort_custom_op_path)
-        sess = ort.InferenceSession(onnx_file, session_options)
         providers = ['CPUExecutionProvider']
         options = [{}]
-        is_cuda_available = ort.get_device() == 'GPU'
+        is_cuda_available = False
+        # is_cuda_available = ort.get_device() == 'GPU'
         if is_cuda_available:
             providers.insert(0, 'CUDAExecutionProvider')
             options.insert(0, {'device_id': device_id})
+        sess = ort.InferenceSession(onnx_file, session_options, providers=providers)
 
         sess.set_providers(providers, options)
 
@@ -336,6 +337,7 @@ class ONNXRuntimeSegmentorKN(BaseSegmentor):
     def forward_train(self, imgs, img_metas, **kwargs):
         raise NotImplementedError('This method is not implemented.')
 
+    @torch.no_grad()
     def simple_test(self, img: torch.Tensor,
                     img_meta: Union[Iterable, None] = None,
                     **kwargs) -> list:
@@ -365,7 +367,6 @@ class ONNXRuntimeSegmentorKN(BaseSegmentor):
                 seg_pred = resize(
                     seg_pred, size=tuple(ori_shape[:2]), mode='nearest')
                 seg_pred = seg_pred.long().detach().cpu().numpy()
-        seg_pred = list(seg_pred[0])
         return list(seg_pred[0])
 
     def aug_test(self, imgs, img_metas, **kwargs):