Romove grid_sampler and refine example code

python/paddle/fluid/layers/nn.py

@@ -13391,15 +13391,15 @@ 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
                              to :ref:`api_guide_Name`. Usually name is no need to set and
                              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([6, 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')
@@ -13422,6 +13424,10 @@ def temporal_shift(x, seg_num, shift_ratio=0.25, name=None):
     if not isinstance(seg_num, int):
         raise TypeError("seg_num must be int type.")
 
+    if in_dygraph_mode():
+        return core.ops.temporal_shift(x, 'seg_num', seg_num, 'shift_ratio',
+                                       shift_ratio)
+
     helper.append_op(
         type="temporal_shift",
         inputs={"X": x},

python/paddle/fluid/tests/unittests/test_grid_sample_function.py

@@ -127,5 +127,15 @@ def load_tests(loader, standard_tests, pattern):
     return suite
 
 
+class TestGridSampleAPI(unittest.TestCase):
+    def test_errors(self):
+        with self.assertRaises(ValueError):
+            x = paddle.randn([1, 1, 3, 3])
+            F.grid_sample(x, 1.0)
+        with self.assertRaises(ValueError):
+            x = paddle.randn([1, 1, 3, 3])
+            F.grid_sample(1.0, x)
+
+
 if __name__ == '__main__':
     unittest.main()

python/paddle/fluid/tests/unittests/test_temporal_shift_op.py

@@ -18,6 +18,7 @@
 import numpy as np
 from op_test import OpTest
 
+import paddle
 from paddle.fluid import core
 
 
@@ -77,5 +78,12 @@ def initTestCase(self):
         self.shift_ratio = 0.3
 
 
+class TestTemporalShiftAPI(unittest.TestCase):
+    def test_api(self):
+        input = paddle.randn([6, 4, 2, 2])
+        out = paddle.nn.functional.temporal_shift(
+            x=input, seg_num=2, shift_ratio=0.2)
+
+
 if __name__ == "__main__":
     unittest.main()

python/paddle/nn/functional/vision.py

@@ -34,7 +34,6 @@
 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 @@
     'generate_mask_labels',
     'generate_proposal_labels',
     'generate_proposals',
-    'grid_sampler',
+    'grid_sample',
     'image_resize',
     'image_resize_short',
     #       'multi_box_head',
@@ -287,7 +286,7 @@ def grid_sample(x,
                             [ 0.7,  0.4],
                             [ 0.2,  0.8]]]]).astype("float64")
 
-            paddle.disable_static()
+
             x = paddle.to_tensor(x)
             grid = paddle.to_tensor(grid)
             y_t = F.grid_sample(
@@ -304,13 +303,10 @@ 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')
-    if not isinstance(x, Variable):
-        raise ValueError("The x should be a Variable")
-    if not isinstance(grid, Variable):
-        raise ValueError("The grid should be a Variable")
+                             'grid_sample')
+
     _modes = ['bilinear', 'nearest']
     _padding_modes = ['zeros', 'reflection', 'border']
     if mode not in _modes: