diff --git a/x2paddle/decoder/onnx_decoder.py b/x2paddle/decoder/onnx_decoder.py
index 0289a1912a6ef91f7ebb185c40ebe4ae5011e61a..29996a076734fbdcba7229104e2be045a7a8063d 100644
--- a/x2paddle/decoder/onnx_decoder.py
+++ b/x2paddle/decoder/onnx_decoder.py
@@ -183,10 +183,10 @@ class ONNXGraph(Graph):
                     return False
         return True
 
-    def fix_unkown_input_shape(self, vi):
+    def fix_input_shape(self, vi):
         shape = self.get_symbolic_shape(vi.type.tensor_type.shape.dim)
         print(
-            "Unknown shape for input tensor[tensor name: '{}'] -> shape: {}, Please define shape of input here,\nNote:you can use visualization tools like Netron to check input shape."
+            "Input tensor[tensor name: '{}'] -> shape: {}, Please define shape of input here,\nNote:you can use visualization tools like Netron to check input shape."
             .format(vi.name, shape))
         right_shape_been_input = False
         while not right_shape_been_input:
@@ -200,8 +200,8 @@ class ONNXGraph(Graph):
                 print("Only 1 dimension can be -1, type again:)")
             else:
                 right_shape_been_input = True
-        if shape == 'N':
-            break
+            if shape == 'N':
+                break
         shape = [int(dim) for dim in shape.strip().split(',')]
         assert shape.count(-1) <= 1, "Only one dimension can be -1"
         self.fixed_input_shape[vi.name] = shape
@@ -214,7 +214,7 @@ class ONNXGraph(Graph):
         for ipt_vi in self.graph.input:
             if ipt_vi.name not in inner_nodes:
                 if self.define_input_shape:
-                    self.check_input_shape(ipt_vi)
+                    self.fix_input_shape(ipt_vi)
                 self.place_holder_nodes.append(ipt_vi.name)
 
     def get_output_nodes(self):