diff --git a/benchmark/qps_test.py b/benchmark/qps_test.py
index 6a5a9f7..2bc4af1 100644
--- a/benchmark/qps_test.py
+++ b/benchmark/qps_test.py
@@ -34,7 +34,7 @@ p = (
         .output('vec')
 )
 
-data = 'towhee.jpeg'
+data = '../towhee.jpeg'
 out1 = p(data).get()[0]
 print('Pipe: OK')
 
@@ -93,7 +93,7 @@ if args.onnx:
     else:
         max_diff = numpy.abs(out1 - out3).max()
         min_diff = numpy.abs(out1 - out3).min()
-        mean_diff =  numpy.abs(out1 - out3).mean()
+        mean_diff = numpy.abs(out1 - out3).mean()
         print(f'Check accuracy: atol is larger than {args.atol}.')
         print(f'Maximum absolute difference is {max_diff}.')
         print(f'Minimum absolute difference is {min_diff}.')
diff --git a/benchmark/towhee.jpeg b/benchmark/towhee.jpeg
deleted file mode 100644
index caf63b3..0000000
Binary files a/benchmark/towhee.jpeg and /dev/null differ
diff --git a/isc.py b/isc.py
index 158a0a9..0253e11 100644
--- a/isc.py
+++ b/isc.py
@@ -106,7 +106,7 @@ class Isc(NNOperator):
             img = img if self.skip_tfms else self.tfms(img)
             img_list.append(img)
         inputs = torch.stack(img_list)
-        inputs = inputs.to(self.device)
+        inputs = inputs
         features = self.model(inputs)
         features = features.to('cpu')
 
@@ -138,7 +138,7 @@ class Isc(NNOperator):
                 path = path + '.onnx'
             else:
                 raise ValueError(f'Invalid format {format}.')
-        dummy_input = torch.rand(1, 3, 224, 224).to(self.device)
+        dummy_input = torch.rand(1, 3, 224, 224)
         if format == 'pytorch':
             torch.save(self._model, path)
         elif format == 'torchscript':
@@ -153,7 +153,7 @@ class Isc(NNOperator):
                 raise RuntimeError(f'Fail to save as torchscript: {e}.')
         elif format == 'onnx':
             try:
-                torch.onnx.export(self._model,
+                torch.onnx.export(self._model.to('cpu'),
                                   dummy_input,
                                   path,
                                   input_names=['input_0'],