diff --git a/python/paddle/hapi/model_summary.py b/python/paddle/hapi/model_summary.py
index 7e435fdc27b4630179b09753c3114606dc047d1a..45db83f9141a72a9f44457bc8f19e105e1d8ce73 100644
--- a/python/paddle/hapi/model_summary.py
+++ b/python/paddle/hapi/model_summary.py
@@ -262,8 +262,10 @@ def summary_string(model, input_size=None, dtypes=None, input=None):
     def _get_output_shape(output):
         if isinstance(output, (list, tuple)):
             output_shape = [_get_output_shape(o) for o in output]
-        else:
+        elif hasattr(output, 'shape'):
             output_shape = list(output.shape)
+        else:
+            output_shape = []
         return output_shape
 
     def register_hook(layer):
diff --git a/python/paddle/tests/test_model.py b/python/paddle/tests/test_model.py
index 36478289ccbbf7b375337a7460b88c540897582f..abeb83391751bea0ebe5d858272a167ff6570723 100644
--- a/python/paddle/tests/test_model.py
+++ b/python/paddle/tests/test_model.py
@@ -68,6 +68,28 @@ class LeNetDygraph(paddle.nn.Layer):
         return x
 
 
+class ModelInner(paddle.nn.Layer):
+    def __init__(self):
+        super(ModelInner, self).__init__()
+        self.fc = paddle.nn.Linear(3, 4)
+
+    def forward(self, x):
+        y = self.fc(x)
+        return y, 0
+
+
+class ModelOutter(paddle.nn.Layer):
+    def __init__(self):
+        super(ModelOutter, self).__init__()
+        self.module1 = ModelInner()
+        self.module2 = paddle.nn.Linear(4, 5)
+
+    def forward(self, x):
+        y, dummpy = self.module1(x)
+        y = self.module2(y)
+        return y, 3
+
+
 class LeNetListInput(LeNetDygraph):
     def forward(self, inputs):
         x = inputs[0]
@@ -607,6 +629,9 @@ class TestModelFunction(unittest.TestCase):
             model.summary(input_size=[(20)])
             model.summary(input_size=(20), dtype='float32')
 
+    def test_summary_non_tensor(self):
+        paddle.summary(ModelOutter(), input_size=(-1, 3))
+
     def test_summary_nlp(self):
         def _get_param_from_state_dict(state_dict):
             params = 0