api change: create_variable_for_type_inference. test=develop

paddle/fluid/API.spec

@@ -175,9 +175,9 @@ paddle.fluid.layers.mul ArgSpec(args=['x', 'y', 'x_num_col_dims', 'y_num_col_dim
 paddle.fluid.layers.sigmoid_cross_entropy_with_logits ArgSpec(args=['x', 'label', 'name'], varargs=None, keywords=None, defaults=(None,))
 paddle.fluid.layers.maxout ArgSpec(args=['x', 'groups', 'name'], varargs=None, keywords=None, defaults=(None,))
 paddle.fluid.layers.sequence_reverse ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,))
-paddle.fluid.layers.grid_sampler ArgSpec(args=['x', 'grid', 'name'], varargs=None, keywords=None, defaults=(None,))
 paddle.fluid.layers.affine_channel ArgSpec(args=['x', 'scale', 'bias', 'data_layout', 'name'], varargs=None, keywords=None, defaults=(None, None, 'NCHW', None))
 paddle.fluid.layers.hash ArgSpec(args=['input', 'hash_size', 'num_hash', 'name'], varargs=None, keywords=None, defaults=(1, None))
+paddle.fluid.layers.grid_sampler ArgSpec(args=['x', 'grid', 'name'], varargs=None, keywords=None, defaults=(None,))
 paddle.fluid.layers.log_loss ArgSpec(args=['input', 'label', 'epsilon', 'name'], varargs=None, keywords=None, defaults=(0.0001, None))
 paddle.fluid.layers.add_position_encoding ArgSpec(args=['input', 'alpha', 'beta', 'name'], varargs=None, keywords=None, defaults=(None,))
 paddle.fluid.layers.data ArgSpec(args=['name', 'shape', 'append_batch_size', 'dtype', 'lod_level', 'type', 'stop_gradient'], varargs=None, keywords=None, defaults=(True, 'float32', 0, VarType.LOD_TENSOR, True))

python/paddle/fluid/layers/nn.py

@@ -7652,6 +7652,7 @@ def grid_sampler(x, grid, name=None):
         out = fluid.layers.grid_sampler(x=x, grid=grid)
     """
     helper = LayerHelper("grid_sampler", **locals())
+    dtype = helper.input_dtype()
 
     if not isinstance(x, Variable):
         return ValueError("The x should be a Variable")
@@ -7659,10 +7660,10 @@ def grid_sampler(x, grid, name=None):
     if not isinstance(grid, Variable):
         return ValueError("The grid should be a Variable")
 
-    out = helper.create_tmp_variable(x.dtype)
+    out = helper.create_variable_for_type_inference(dtype)
     ipts = {'X': x, 'Grid': grid}
 
-    helper.apppend_op(type='grid_sampler', inputs=ipts, outputs={'Output', out})
+    helper.append_op(type='grid_sampler', inputs=ipts, outputs={'Output', out})
     return out
 
 

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

@@ -865,10 +865,10 @@ class TestBook(unittest.TestCase):
             self.assertIsNotNone(out)
         print(str(program))
 
-    def test_affine_grid_gen(self):
+    def test_grid_sampler(self):
         program = Program()
         with program_guard(program):
-            x = layers.data(name='x', shape=[2, 5, 7, 3], dtype='float32')
+            x = layers.data(name='x', shape=[2, 3, 5, 7], dtype='float32')
             grid = layers.data(name='grid', shape=[2, 5, 7, 2], dtype='float32')
             out = layers.grid_sampler(x, grid)
             self.assertIsNotNone(out)