diff --git a/python/paddle/tensor/linalg.py b/python/paddle/tensor/linalg.py
index 4bb2cf4227deed1b9e8cd9f1720ac2ec62331c78..a5492d508103736ef44c8bb4586254ca2910838f 100644
--- a/python/paddle/tensor/linalg.py
+++ b/python/paddle/tensor/linalg.py
@@ -1557,30 +1557,29 @@ def bmm(x, y, name=None):
             #          [60., 60.]]])
 
     """
-    x_shape = x.shape
-    y_shape = y.shape
-    if not len(x_shape) == len(y_shape) == 3:
-        raise ValueError(
-            "x and y should be 3-dimensional. But received x's dimention: {}, y's dimention: {}".format(
-                x_shape, y_shape
-            )
-        )
-    if x_shape[2] != y_shape[1]:
-        raise ValueError(
-            "x's width must be equal with y's height. But received x's shape: {}, y's shape: {}".format(
-                x_shape, y_shape
-            )
-        )
-    if x_shape[0] != y_shape[0]:
-        raise ValueError(
-            "x's batch (shape[0]) must be equal with y's batch (shape[0]). But received x's shape: {}, y's shape: {}".format(
-                x_shape, y_shape
-            )
-        )
-
     if in_dygraph_mode():
         return _C_ops.bmm(x, y)
     else:
+        x_shape = x.shape
+        y_shape = y.shape
+        if not len(x_shape) == len(y_shape) == 3:
+            raise ValueError(
+                "x and y should be 3-dimensional. But received x's dimention: {}, y's dimention: {}".format(
+                    x_shape, y_shape
+                )
+            )
+        if x_shape[2] != y_shape[1]:
+            raise ValueError(
+                "x's width must be equal with y's height. But received x's shape: {}, y's shape: {}".format(
+                    x_shape, y_shape
+                )
+            )
+        if x_shape[0] != y_shape[0]:
+            raise ValueError(
+                "x's batch (shape[0]) must be equal with y's batch (shape[0]). But received x's shape: {}, y's shape: {}".format(
+                    x_shape, y_shape
+                )
+            )
         helper = LayerHelper('bmm', **locals())
         out = helper.create_variable_for_type_inference(dtype=x.dtype)
         helper.append_op(