[static op generation] triangular_solve

paddle/phi/api/yaml/backward.yaml

@@ -1931,6 +1931,16 @@
     data_type : out_grad
   no_need_buffer : x
 
+- backward_op : triangular_solve_grad
+  forward : triangular_solve (Tensor x, Tensor y, bool upper=true, bool tranpose=false, bool unitriangular=false) -> Tensor(out)
+  args : (Tensor x, Tensor y, Tensor out, Tensor out_grad, bool upper, bool tranpose, bool unitriangular)
+  output : Tensor(x_grad), Tensor(y_grad)
+  infer_meta :
+    func : GeneralBinaryGradInferMeta
+    param : [x, y]
+  kernel :
+    func : triangular_solve_grad
+
 - backward_op : trilinear_interp_grad
   forward : trilinear_interp (Tensor x, Tensor out_size, Tensor[] size_tensor, Tensor scale_tensor, str data_layout="NCHW", int out_d=0, int out_h=0, int out_w=0, float[] scale={}, str interp_method="bilinear", bool align_corners=true, int align_mode=1) -> Tensor(output)
   args : (Tensor x, Tensor out_size, Tensor[] size_tensor, Tensor scale_tensor, Tensor output_grad, str data_layout, int out_d, int out_h, int out_w, float[] scale, str interp_method, bool align_corners, int align_mode)

paddle/phi/api/yaml/legacy_backward.yaml

@@ -1051,16 +1051,6 @@
   backward : transpose_double_grad
   composite: transpose_grad(out_grad, perm, x_grad)
 
-- backward_op : triangular_solve_grad
-  forward : triangular_solve (Tensor x, Tensor y, bool upper, bool tranpose, bool unitriangular) -> Tensor(out)
-  args : (Tensor x, Tensor y, Tensor out, Tensor out_grad, bool upper, bool tranpose, bool unitriangular)
-  output : Tensor(x_grad), Tensor(y_grad)
-  infer_meta :
-    func : GeneralBinaryGradInferMeta
-    param : [x, y]
-  kernel :
-    func : triangular_solve_grad
-
 - backward_op : tril_grad
   forward : tril(Tensor x,  int diagonal) -> Tensor(out)
   args : (Tensor out_grad,  int diagonal)

paddle/phi/api/yaml/legacy_ops.yaml

@@ -1175,16 +1175,6 @@
     func : transpose
   backward : transpose_grad
 
-- op : triangular_solve
-  args : (Tensor x, Tensor y, bool upper, bool transpose, bool unitriangular)
-  output : Tensor
-  infer_meta :
-    func : TriangularSolveInferMeta
-  kernel :
-    func : triangular_solve
-    data_type : x
-  backward : triangular_solve_grad
-
 - op : tril
   args : (Tensor x, int diagonal)
   output : Tensor(out)

paddle/phi/api/yaml/op_compat.yaml

@@ -2300,6 +2300,13 @@
     outputs : [XShape]
     attrs : [bool use_mkldnn = false, str data_format = "AnyLayout", str mkldnn_data_type = "float32"]
 
+- op : triangular_solve
+  backward : triangular_solve_grad
+  inputs :
+    {x : X, y : Y}
+  outputs :
+    out : Out
+
 - op : trilinear_interp (trilinear_interp_v2)
   backward : trilinear_interp_grad (trilinear_interp_v2_grad)
   inputs :

paddle/phi/api/yaml/ops.yaml

@@ -2016,6 +2016,16 @@
     func : trace
   backward : trace_grad
 
+- op : triangular_solve
+  args : (Tensor x, Tensor y, bool upper=true, bool transpose=false, bool unitriangular=false)
+  output : Tensor
+  infer_meta :
+    func : TriangularSolveInferMeta
+  kernel :
+    func : triangular_solve
+    data_type : x
+  backward : triangular_solve_grad
+
 - op : trilinear_interp
   args : (Tensor x, Tensor out_size, Tensor[] size_tensor, Tensor scale_tensor, str data_layout="NCHW", int out_d=0, int out_h=0, int out_w=0, float[] scale={}, str interp_method="bilinear", bool align_corners=true, int align_mode=1)
   output : Tensor(output)