add autogen code for clip_by_norm op (#52743)

* add autogen code for clip_by_norm op

* bug fixed

paddle/fluid/operators/clip_by_norm_op.cc

-/* 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.
-See the License for the specific language governing permissions and
-limitations under the License. */
-
-#include "paddle/fluid/operators/clip_by_norm_op.h"
-#include "paddle/fluid/framework/infershape_utils.h"
-#include "paddle/phi/core/infermeta_utils.h"
-#include "paddle/phi/infermeta/unary.h"
-
-namespace ops = paddle::operators;
-
-DECLARE_INFER_SHAPE_FUNCTOR(clip_by_norm,
-                            ClipByNormInferShapeFunctor,
-                            PD_INFER_META(phi::ClipByNormInferMeta));
-
-REGISTER_OP_WITHOUT_GRADIENT(clip_by_norm,
-                             ops::ClipByNormOp,
-                             ops::ClipByNormOpMaker,
-                             ClipByNormInferShapeFunctor);

paddle/phi/api/yaml/legacy_ops.yaml

@@ -222,14 +222,6 @@
   kernel :
     func : class_center_sample
 
-- op : clip_by_norm
-  args : (Tensor x, float max_norm)
-  output : Tensor(out)
-  infer_meta :
-    func : ClipByNormInferMeta
-  kernel :
-    func : clip_by_norm
-
 - op : coalesce_tensor
   args : (Tensor[] input, DataType dtype, bool copy_data = false, bool set_constant = false, bool persist_output = false, float constant = 0.0, bool use_align = true, int align_size = -1, int size_of_dtype = -1, int64_t[] concated_shapes = {}, int64_t[] concated_ranks = {})
   output : Tensor[](output){input.size()}, Tensor(fused_output)

paddle/phi/api/yaml/op_compat.yaml

@@ -356,6 +356,12 @@
   extra :
     attrs : [bool use_mkldnn = false, str mkldnn_data_type = "float32"]
 
+- op : clip_by_norm
+  inputs :
+    x : X
+  outputs :
+    out : Out
+
 - op : complex
   backward : complex_grad
   inputs :

paddle/phi/api/yaml/ops.yaml

@@ -355,6 +355,15 @@
     data_type : x
   backward : clip_grad
 
+- op : clip_by_norm
+  args : (Tensor x, float max_norm)
+  output : Tensor(out)
+  infer_meta :
+    func : ClipByNormInferMeta
+  kernel :
+    func : clip_by_norm {dense -> dense}
+           clip_by_norm_sr {selected_rows -> selected_rows}
+
 - op : complex
   args : (Tensor real, Tensor imag)
   output : Tensor

paddle/phi/ops/compat/clip_by_norm_sig.cc

-/* Copyright (c) 2022 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.
-See the License for the specific language governing permissions and
-limitations under the License. */
-
-#include "paddle/phi/core/compat/op_utils.h"
-
-namespace phi {
-
-KernelSignature ClipByNormOpArgumentMapping(const ArgumentMappingContext& ctx) {
-  if (ctx.IsDenseTensorInput("X")) {
-    return KernelSignature("clip_by_norm", {"X"}, {"max_norm"}, {"Out"});
-  } else if (ctx.IsSelectedRowsInput("X")) {
-    return KernelSignature("clip_by_norm_sr", {"X"}, {"max_norm"}, {"Out"});
-  }
-  return KernelSignature("unregistered", {}, {}, {});
-}
-
-}  // namespace phi
-
-PD_REGISTER_ARG_MAPPING_FN(clip_by_norm, phi::ClipByNormOpArgumentMapping);