diff --git a/python/paddle/fluid/layers/nn.py b/python/paddle/fluid/layers/nn.py
index 3e7d10f8d1a02126c3d4bec490fcd2f3194123ee..87a1971747e84ffa1db4ebcce29941d577d2df24 100755
--- a/python/paddle/fluid/layers/nn.py
+++ b/python/paddle/fluid/layers/nn.py
@@ -13391,7 +13391,7 @@ def temporal_shift(x, seg_num, shift_ratio=0.25, name=None):
     ${comment}
 
     Args:
-        x(Variable): ${x_comment}
+        x(Tensor): ${x_comment}
         seg_num(int): ${seg_num_comment}
         shift_ratio(float): ${shift_ratio_comment}
         name(str, optional): For detailed information, please refer
@@ -13399,7 +13399,7 @@ def temporal_shift(x, seg_num, shift_ratio=0.25, name=None):
                              None by default.
 
     Returns:
-        out(Variable): The temporal shifting result is a tensor variable with the
+        out(Tensor): The temporal shifting result is a tensor with the
         same shape and same data type as the input.
 
     Raises:
@@ -13408,9 +13408,11 @@ def temporal_shift(x, seg_num, shift_ratio=0.25, name=None):
     Examples:
         .. code-block:: python
 
-            import paddle.fluid as fluid
-            input = fluid.data(name='input', shape=[None,4,2,2], dtype='float32')
-            out = fluid.layers.temporal_shift(x=input, seg_num=2, shift_ratio=0.2)
+            import paddle
+            import paddle.nn.functional as F
+
+            input = paddle.randn([3, 4, 2, 2])
+            out = F.temporal_shift(x=input, seg_num=2, shift_ratio=0.2)
     """
     helper = LayerHelper("temporal_shift", **locals())
     check_variable_and_dtype(x, 'x', ['float32', 'float64'], 'temporal_shift')
diff --git a/python/paddle/nn/functional/vision.py b/python/paddle/nn/functional/vision.py
index a74a98d5ed45b9f613b0f2f6d5f04544ffae3d2a..935b9881e5943da1aa001538dbddc35d08c4902e 100644
--- a/python/paddle/nn/functional/vision.py
+++ b/python/paddle/nn/functional/vision.py
@@ -34,7 +34,6 @@ from ...fluid.layers import distribute_fpn_proposals  #DEFINE_ALIAS
 from ...fluid.layers import generate_mask_labels  #DEFINE_ALIAS
 from ...fluid.layers import generate_proposal_labels  #DEFINE_ALIAS
 from ...fluid.layers import generate_proposals  #DEFINE_ALIAS
-from ...fluid.layers import grid_sampler  #DEFINE_ALIAS
 from ...fluid.layers import image_resize  #DEFINE_ALIAS
 from ...fluid.layers import prior_box  #DEFINE_ALIAS
 from ...fluid.layers import prroi_pool  #DEFINE_ALIAS
@@ -74,7 +73,7 @@ __all__ = [
     'generate_mask_labels',
     'generate_proposal_labels',
     'generate_proposals',
-    'grid_sampler',
+    'grid_sample',
     'image_resize',
     'image_resize_short',
     #       'multi_box_head',
@@ -304,13 +303,13 @@ def grid_sample(x,
             #    [ 0.596  0.38   0.52   0.24 ]]]]
     """
     helper = LayerHelper("grid_sample", **locals())
-    check_variable_and_dtype(x, 'x', ['float32', 'float64'], 'grid_sampler')
+    check_variable_and_dtype(x, 'x', ['float32', 'float64'], 'grid_sample')
     check_variable_and_dtype(grid, 'grid', ['float32', 'float64'],
-                             'grid_sampler')
+                             'grid_sample')
     if not isinstance(x, Variable):
-        raise ValueError("The x should be a Variable")
+        raise ValueError("The x should be a Tensor")
     if not isinstance(grid, Variable):
-        raise ValueError("The grid should be a Variable")
+        raise ValueError("The grid should be a Tensor")
     _modes = ['bilinear', 'nearest']
     _padding_modes = ['zeros', 'reflection', 'border']
     if mode not in _modes: