Reproduce summary api (#27367)

* reproduce summary api

python/paddle/hapi/model.py

@@ -1813,7 +1813,7 @@ class Model(object):
             return logs, outputs
         return logs
 
-    def summary(self, input_size=None, batch_size=None, dtype=None):
+    def summary(self, input_size=None, dtype=None):
         """Prints a string summary of the network.
 
         Args:
@@ -1822,7 +1822,6 @@ class Model(object):
                     one input, input_size can be tuple or InputSpec. if model have multiple 
                     input, input_size must be a list which contain every input's shape. 
                     Default: None.
-            batch_size (int, optional): batch size of input tensor, Default: None.
             dtypes (str, optional): if dtypes is None, 'float32' will be used, Default: None.
 
         Returns:
@@ -1859,7 +1858,7 @@ class Model(object):
             _input_size = input_size
         else:
             _input_size = self._inputs
-        return summary(self.network, _input_size, batch_size, dtype)
+        return summary(self.network, _input_size, dtype)
 
     def _verify_spec(self, specs, is_input=False):
         out_specs = []

python/paddle/tests/test_model.py

@@ -494,17 +494,22 @@ class TestModelFunction(unittest.TestCase):
 
             model.summary(input_size=(20))
             model.summary(input_size=[(20)])
-            model.summary(input_size=(20), batch_size=2)
+            model.summary(input_size=(20), dtype='float32')
 
     def test_summary_nlp(self):
         paddle.enable_static()
-        nlp_net = paddle.nn.GRU(input_size=2, hidden_size=3, num_layers=3)
+        nlp_net = paddle.nn.GRU(input_size=2,
-        paddle.summary(nlp_net, (1, 2))
+                                hidden_size=3,
+                                num_layers=3,
+                                direction="bidirectional")
+        paddle.summary(nlp_net, (1, 1, 2))
+        rnn = paddle.nn.LSTM(16, 32, 2)
+        paddle.summary(rnn, [(-1, 23, 16), ((2, None, 32), (2, -1, 32))])
 
     def test_summary_error(self):
         with self.assertRaises(TypeError):
             nlp_net = paddle.nn.GRU(input_size=2, hidden_size=3, num_layers=3)
-            paddle.summary(nlp_net, (1, '2'))
+            paddle.summary(nlp_net, (1, 1, '2'))
 
         with self.assertRaises(ValueError):
             nlp_net = paddle.nn.GRU(input_size=2, hidden_size=3, num_layers=3)
@@ -512,7 +517,7 @@ class TestModelFunction(unittest.TestCase):
 
         paddle.disable_static()
         nlp_net = paddle.nn.GRU(input_size=2, hidden_size=3, num_layers=3)
-        paddle.summary(nlp_net, (1, 2))
+        paddle.summary(nlp_net, (1, 1, 2))
 
     def test_export_deploy_model(self):
         for dynamic in [True, False]: