check for onnx model

x2paddle/convert.py

@@ -163,13 +163,12 @@ def onnx2paddle(model_path, save_dir, params_merge=False):
         return
     print("Now translating model from onnx to paddle.")
 
+    from x2paddle.op_mapper.onnx_op_mapper import ONNXOpMapper
     from x2paddle.decoder.onnx_decoder import ONNXDecoder
-    model = ONNXDecoder(model_path)
+    from x2paddle.optimizer.onnx_optimizer import ONNXOptimizer
 
-    from x2paddle.op_mapper.onnx_op_mapper import ONNXOpMapper
+    model = ONNXDecoder(model_path)
     mapper = ONNXOpMapper(model, save_dir)
-
-    from x2paddle.optimizer.onnx_optimizer import ONNXOptimizer
     optimizer = ONNXOptimizer(mapper)
 
     optimizer.delete_redundance_code()

x2paddle/op_mapper/onnx_op_mapper.py

@@ -141,7 +141,12 @@ class ONNXOpMapper(OpMapper):
         onnx.save(model, os.path.join(self.tmp_data_dir,
                                       'onnx_model_infer.onnx'))
 
-        os.system('onnx_infer --save_dir=' + self.tmp_data_dir)
+        is_success = os.system('onnx_infer --save_dir=' + self.tmp_data_dir)
+        if is_success != 0:
+            raise Exception("onnxruntime inference onnx model failed, Please \
+                             confirm the correctness of onnx model by onnxruntime, \
+                             if onnx model is valid, you can submit issue in github."
+                            )
         return
 
     def get_dynamic_shape(self, layer):