static graph autogen code for expand

paddle/fluid/operators/expand_op.cc

@@ -1,11 +1,8 @@
 /* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
-
 Licensed under the Apache License, Version 2.0 (the "License");
 you may not use this file except in compliance with the License.
 You may obtain a copy of the License at
-
     http://www.apache.org/licenses/LICENSE-2.0
-
 Unless required by applicable law or agreed to in writing, software
 distributed under the License is distributed on an "AS IS" BASIS,
 WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
@@ -128,23 +125,17 @@ Expand operator tiles the input by given times number. You should set times
 number for each dimension by providing attribute 'expand_times'. The rank of X
 should be in [1, 6]. Please note that size of 'expand_times' must be the same
 with X's rank. Following is a using case:
-
 Input(X) is a 3-D tensor with shape [2, 3, 1]:
-
         [
            [[1], [2], [3]],
            [[4], [5], [6]]
         ]
-
 Attr(expand_times):  [1, 2, 2]
-
 Output(Out) is a 3-D tensor with shape [2, 6, 2]:
-
         [
             [[1, 1], [2, 2], [3, 3], [1, 1], [2, 2], [3, 3]],
             [[4, 4], [5, 5], [6, 6], [4, 4], [5, 5], [6, 6]]
         ]
-
 )DOC");
   }
 };

paddle/phi/api/yaml/backward.yaml

@@ -682,6 +682,26 @@
     func : expand_as_grad
   no_need_buffer : x
 
+- backward_op : expand_double_grad
+  forward : expand_grad (Tensor x, Tensor grad_out, IntArray shape) -> Tensor(grad_x)
+  args : (Tensor grad_x_grad, IntArray shape)
+  output : Tensor(grad_out_grad)
+  invoke : expand(grad_x_grad, shape)
+
+- backward_op : expand_grad
+  forward : expand (Tensor x, IntArray shape) -> Tensor(out)
+  args : (Tensor x, Tensor out_grad, IntArray shape)
+  output : Tensor(x_grad)
+  infer_meta :
+    func : UnchangedInferMeta
+    param : [x]
+  kernel :
+    func : expand_grad
+    data_type : out_grad
+  no_need_buffer : x
+  backward : expand_double_grad
+  composite: expand_grad(x, out_grad, shape, x_grad)
+
 - backward_op : expm1_grad
   forward : expm1 (Tensor x) -> Tensor(out)
   args : (Tensor out, Tensor out_grad)

paddle/phi/api/yaml/legacy_backward.yaml

@@ -255,25 +255,6 @@
   invoke : embedding_grad_impl(x, weight, out_grad, padding_idx, sparse, weight_grad)
   no_need_buffer : weight
 
-- backward_op : expand_double_grad
-  forward : expand_grad (Tensor x, Tensor grad_out, IntArray shape) -> Tensor(grad_x)
-  args : (Tensor grad_x_grad, IntArray shape)
-  output : Tensor(grad_out_grad)
-  invoke : expand(grad_x_grad, shape)
-
-- backward_op : expand_grad
-  forward : expand (Tensor x, IntArray shape) -> Tensor(out)
-  args : (Tensor x, Tensor out_grad, IntArray shape)
-  output : Tensor(x_grad)
-  infer_meta :
-    func : UnchangedInferMeta
-    param : [x]
-  kernel :
-    func : expand_grad
-  no_need_buffer : x
-  backward : expand_double_grad
-  composite: expand_grad(x, out_grad, shape, x_grad)
-
 - backward_op : exponential__grad
   forward : exponential_ (Tensor x, float lam) -> Tensor(out)
   args : (Tensor out_grad)

paddle/phi/api/yaml/legacy_ops.yaml

@@ -302,15 +302,6 @@
   kernel :
     func : equal
 
-- op : expand
-  args : (Tensor x, IntArray shape)
-  output : Tensor
-  infer_meta :
-    func : ExpandInferMeta
-  kernel :
-    func : expand
-  backward : expand_grad
-
 - op : exponential_
   args : (Tensor x, float lam)
   output : Tensor(out)

paddle/phi/api/yaml/op_compat.yaml

@@ -914,7 +914,7 @@
     attrs : [bool use_mkldnn = false, bool use_cudnn = false]
 
 - op : expand (expand_v2)
-  backward : expand_grad (expand_v2_grad)
+  backward : expand_grad (expand_v2_grad), expand_double_grad(expand_v2_double_grad)
   inputs :
     x : X
   attrs :
@@ -928,6 +928,7 @@
       tensors_name : expand_shapes_tensor
   extra :
     attrs : [bool use_mkldnn = false, str mkldnn_data_type = "float32"]
+  manual_signature : [expand, expand_grad]
 
 - op : expand_as (expand_as_v2)
   backward : expand_as_grad (expand_as_v2_grad)

paddle/phi/api/yaml/ops.yaml

@@ -762,6 +762,16 @@
   inplace : (x -> out)
   backward : exp_grad
 
+- op : expand
+  args : (Tensor x, IntArray shape = {})
+  output : Tensor(out)
+  infer_meta :
+    func : ExpandInferMeta
+  kernel :
+    func : expand
+    data_type : x
+  backward : expand_grad
+
 - op : expand_as
   args : (Tensor x, Tensor y, int[] target_shape = {})
   output : Tensor(out)