提交 e99da0b5 编写于 作者: D dengkaipeng

api change: create_variable_for_type_inference. test=develop

上级 a3b26e85
...@@ -175,9 +175,9 @@ paddle.fluid.layers.mul ArgSpec(args=['x', 'y', 'x_num_col_dims', 'y_num_col_dim ...@@ -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.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.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.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.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.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.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.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)) 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))
......
...@@ -7652,6 +7652,7 @@ def grid_sampler(x, grid, name=None): ...@@ -7652,6 +7652,7 @@ def grid_sampler(x, grid, name=None):
out = fluid.layers.grid_sampler(x=x, grid=grid) out = fluid.layers.grid_sampler(x=x, grid=grid)
""" """
helper = LayerHelper("grid_sampler", **locals()) helper = LayerHelper("grid_sampler", **locals())
dtype = helper.input_dtype()
if not isinstance(x, Variable): if not isinstance(x, Variable):
return ValueError("The x should be a Variable") return ValueError("The x should be a Variable")
...@@ -7659,10 +7660,10 @@ def grid_sampler(x, grid, name=None): ...@@ -7659,10 +7660,10 @@ def grid_sampler(x, grid, name=None):
if not isinstance(grid, Variable): if not isinstance(grid, Variable):
return ValueError("The grid should be a 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} 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 return out
......
...@@ -865,10 +865,10 @@ class TestBook(unittest.TestCase): ...@@ -865,10 +865,10 @@ class TestBook(unittest.TestCase):
self.assertIsNotNone(out) self.assertIsNotNone(out)
print(str(program)) print(str(program))
def test_affine_grid_gen(self): def test_grid_sampler(self):
program = Program() program = Program()
with program_guard(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') grid = layers.data(name='grid', shape=[2, 5, 7, 2], dtype='float32')
out = layers.grid_sampler(x, grid) out = layers.grid_sampler(x, grid)
self.assertIsNotNone(out) self.assertIsNotNone(out)
......
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