support auto generation V2 abs (#53341)

paddle/fluid/operators/abs_op.cc

-// Copyright (c) 2021 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 <memory>
-#include <string>
-#include <unordered_map>
-#include <vector>
-
-#include "paddle/fluid/framework/infershape_utils.h"
-#include "paddle/fluid/framework/op_registry.h"
-#include "paddle/fluid/prim/api/composite_backward/composite_backward_api.h"
-#include "paddle/fluid/prim/utils/static/composite_grad_desc_maker.h"
-#include "paddle/fluid/prim/utils/static/desc_tensor.h"
-#include "paddle/phi/core/infermeta_utils.h"
-#include "paddle/phi/infermeta/unary.h"
-
-namespace paddle {
-namespace operators {
-
-class AbsOp : public framework::OperatorWithKernel {
- public:
-  using framework::OperatorWithKernel::OperatorWithKernel;
-
-  phi::KernelKey GetExpectedKernelType(
-      const framework::ExecutionContext& ctx) const override {
-    auto input_data_type =
-        framework::OperatorWithKernel::IndicateVarDataType(ctx, "X");
-    return phi::KernelKey(input_data_type, ctx.GetPlace());
-  }
-};
-
-class AbsOpMaker : public framework::OpProtoAndCheckerMaker {
- public:
-  void Make() override {
-    AddInput("X", "(Tensor), The input tensor of abs op.");
-    AddOutput("Out", "(Tensor), The output tensor of abs op.");
-    AddComment(R"DOC(
-Abs Operator.
-
-This operator is used to perform elementwise abs for input $X$.
-$$out = |x|$$
-
-)DOC");
-  }
-};
-
-class AbsGradOp : public framework::OperatorWithKernel {
- public:
-  using framework::OperatorWithKernel::OperatorWithKernel;
-  void InferShape(framework::InferShapeContext* ctx) const override {
-    OP_INOUT_CHECK(ctx->HasInput(framework::GradVarName("Out")),
-                   "Input",
-                   "Out@Grad",
-                   "AbsGrad");
-    OP_INOUT_CHECK(ctx->HasOutput(framework::GradVarName("X")),
-                   "Output",
-                   "X@Grad",
-                   "AbsGrad");
-
-    auto dout_dims = ctx->GetInputDim(framework::GradVarName("Out"));
-    ctx->SetOutputDim(framework::GradVarName("X"), dout_dims);
-  }
-
- protected:
-  phi::KernelKey GetExpectedKernelType(
-      const framework::ExecutionContext& ctx) const override {
-    auto input_data_type =
-        framework::OperatorWithKernel::IndicateVarDataType(ctx, "X");
-    return phi::KernelKey(input_data_type, ctx.GetPlace());
-  }
-};
-
-template <typename T>
-class AbsGradMaker : public framework::SingleGradOpMaker<T> {
- public:
-  using framework::SingleGradOpMaker<T>::SingleGradOpMaker;
-
-  void Apply(GradOpPtr<T> retv) const override {
-    retv->SetType("abs_grad");
-    retv->SetInput(framework::GradVarName("Out"), this->OutputGrad("Out"));
-    retv->SetInput("X", this->Input("X"));
-    retv->SetAttrMap(this->Attrs());
-    retv->SetOutput(framework::GradVarName("X"), this->InputGrad("X"));
-  }
-};
-
-class AbsCompositeGradOpMaker : public prim::CompositeGradOpMakerBase {
-  using prim::CompositeGradOpMakerBase::CompositeGradOpMakerBase;
-
- public:
-  void Apply() override {
-    paddle::Tensor input = this->GetSingleForwardInput("X");
-    paddle::Tensor out_grad = this->GetSingleOutputGrad("Out");
-    paddle::Tensor input_grad = this->GetSingleInputGrad("X");
-
-    auto dx_ptr = this->GetOutputPtr(&input_grad);
-    std::string dx_name = this->GetOutputName(input_grad);
-
-    VLOG(6) << "Running abs_grad composite func";
-    prim::abs_grad<prim::DescTensor>(input, out_grad, dx_ptr);
-    this->RecoverOutputName(input_grad, dx_name);
-  }
-};
-
-// AbsGrad: dx=dy if x >=0 else -dy
-// AbsDoubleGrad: ddy = ddx if x >=0 else -ddx
-template <typename T>
-class AbsDoubleGradMaker : public framework::SingleGradOpMaker<T> {
- public:
-  using ::paddle::framework::SingleGradOpMaker<T>::SingleGradOpMaker;
-
- protected:
-  void Apply(GradOpPtr<T> op) const override {
-    op->SetType("abs_double_grad");
-    // input1: x
-    op->SetInput("X", this->Input("X"));
-    // input2: ddx
-    op->SetInput("DDX", this->OutputGrad(framework::GradVarName("X")));
-    op->SetAttrMap(this->Attrs());
-    // output: ddy
-    op->SetOutput("DDOut", this->InputGrad(framework::GradVarName("Out")));
-  }
-};
-
-class AbsDoubleGradOp : public framework::OperatorWithKernel {
- public:
-  using framework::OperatorWithKernel::OperatorWithKernel;
-
-  void InferShape(framework::InferShapeContext* ctx) const override {
-    if (ctx->HasOutput("DDOut")) {
-      ctx->ShareDim("X", "DDOut");
-      ctx->ShareLoD("X", "DDOut");
-    }
-  }
-
- protected:
-  phi::KernelKey GetExpectedKernelType(
-      const framework::ExecutionContext& ctx) const override {
-    auto dtype = OperatorWithKernel::IndicateVarDataType(ctx, "DDX");
-    return phi::KernelKey(dtype, ctx.GetPlace());
-  }
-
-  phi::KernelKey GetKernelTypeForVar(
-      const std::string& var_name,
-      const phi::DenseTensor& tensor,
-      const phi::KernelKey& expected_kernel_type) const override {
-    return phi::KernelKey(tensor.place(), tensor.layout(), tensor.dtype());
-  }
-};
-
-}  // namespace operators
-}  // namespace paddle
-
-DECLARE_INFER_SHAPE_FUNCTOR(abs,
-                            AbsInferShapeFunctor,
-                            PD_INFER_META(phi::RealAndImagInferMeta));
-
-namespace ops = paddle::operators;
-
-REGISTER_OPERATOR(abs,
-                  ops::AbsOp,
-                  ops::AbsOpMaker,
-                  ops::AbsCompositeGradOpMaker,
-                  ops::AbsGradMaker<paddle::framework::OpDesc>,
-                  ops::AbsGradMaker<paddle::imperative::OpBase>,
-                  AbsInferShapeFunctor);
-
-REGISTER_OPERATOR(abs_grad,
-                  ops::AbsGradOp,
-                  ops::AbsDoubleGradMaker<paddle::framework::OpDesc>,
-                  ops::AbsDoubleGradMaker<paddle::imperative::OpBase>);
-
-REGISTER_OPERATOR(abs_double_grad, ops::AbsDoubleGradOp);

paddle/phi/api/yaml/backward.yaml

 # This file is designed for backward C++ operators associated with
 # the operator in ops.yaml.
 
+- backward_op : abs_double_grad
+  forward : abs_grad (Tensor x, Tensor grad_out) -> Tensor(grad_x)
+  args : (Tensor x, Tensor grad_x_grad)
+  output : Tensor(grad_out_grad)
+  infer_meta :
+    func : UnchangedInferMeta
+    param : [x]
+  data_transform :
+    support_trans_dtype : x, grad_x_grad
+  kernel :
+    func : abs_double_grad
+    data_type : grad_x_grad
+
+- backward_op : abs_grad
+  forward : abs (Tensor x) -> Tensor(out)
+  args : (Tensor x, Tensor out_grad)
+  output : Tensor(x_grad)
+  infer_meta :
+    func : UnchangedInferMeta
+    param : [x]
+  kernel :
+    func : abs_grad
+    data_type : x
+  composite : abs_grad(x, out_grad, x_grad)
+  backward : abs_double_grad
+
 - backward_op : acos_grad
   forward : acos (Tensor x) -> Tensor(out)
   args : (Tensor x, Tensor out_grad)

paddle/phi/api/yaml/legacy_backward.yaml

-- backward_op : abs_double_grad
-  forward : abs_grad (Tensor x, Tensor grad_out) -> Tensor(grad_x)
-  args : (Tensor x, Tensor grad_x_grad)
-  output : Tensor(grad_out_grad)
-  infer_meta :
-    func : UnchangedInferMeta
-    param : [x]
-  kernel :
-    func : abs_double_grad
-
-- backward_op : abs_grad
-  forward : abs (Tensor x) -> Tensor(out)
-  args : (Tensor x, Tensor out_grad)
-  output : Tensor(x_grad)
-  infer_meta :
-    func : UnchangedInferMeta
-    param : [x]
-  kernel :
-    func : abs_grad
-  composite : abs_grad(x, out_grad, x_grad)
-  backward : abs_double_grad
-
 - backward_op : add_double_grad
   forward : add_grad (Tensor x, Tensor y, Tensor grad_out, int axis = -1) -> Tensor(grad_x), Tensor(grad_y)
   args : (Tensor y, Tensor grad_out, Tensor grad_x_grad, Tensor grad_y_grad, int axis = -1)

paddle/phi/api/yaml/legacy_ops.yaml

 # The apis in this file are unstandardized that may caused by a variety of reasons,
 # we are trying to fix these apis and will move standardized apis into ops.yaml.
 
-- op : abs
-  args : (Tensor x)
-  output : Tensor
-  infer_meta :
-    func : RealAndImagInferMeta
-  kernel :
-    func : abs
-  backward : abs_grad
-
 - op : adadelta_
   args : (Tensor param, Tensor grad, Tensor avg_squared_grad, Tensor avg_squared_update, Tensor learning_rate, Tensor master_param, float rho, float epsilon, bool multi_precision)
   output : Tensor(param_out), Tensor(moment_out), Tensor(inf_norm_out), Tensor(master_param_out)

paddle/phi/api/yaml/ops.yaml

@@ -5,6 +5,16 @@
 # are consistent and correspond one-to-one. It's forbidden that the
 # operator configured in this yaml file does not have Python API.
 
+- op : abs
+  args : (Tensor x)
+  output : Tensor(out)
+  infer_meta :
+    func : RealAndImagInferMeta
+  kernel :
+    func : abs
+    data_type : x
+  backward : abs_grad
+
 - op : accuracy
   args : (Tensor x, Tensor indices, Tensor label)
   output : Tensor(accuracy), Tensor(correct), Tensor(total)

paddle/phi/ops/compat/abs_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 AbsOpArgumentMapping(const ArgumentMappingContext& ctx) {
-  return KernelSignature("abs", {"X"}, {}, {"Out"});
-}
-
-KernelSignature AbsGradOpArgumentMapping(const ArgumentMappingContext& ctx) {
-  return KernelSignature("abs_grad", {"X", "Out@GRAD"}, {}, {"X@GRAD"});
-}
-
-KernelSignature AbsDoubleGradOpArgumentMapping(
-    const ArgumentMappingContext& ctx) {
-  return KernelSignature("abs_double_grad", {"X", "DDX"}, {}, {"DDOut"});
-}
-
-}  // namespace phi
-
-PD_REGISTER_ARG_MAPPING_FN(abs, phi::AbsOpArgumentMapping);
-PD_REGISTER_ARG_MAPPING_FN(abs_grad, phi::AbsGradOpArgumentMapping);
-PD_REGISTER_ARG_MAPPING_FN(abs_double_grad,
-                           phi::AbsDoubleGradOpArgumentMapping);

python/paddle/tensor/layer_function_generator.py

@@ -308,12 +308,28 @@ def generate_activation_fn(op_type):
             return output
 
     func.__name__ = op_type
-    func.__doc__ = _generate_doc_string_(
-        op_proto,
-        additional_args_lines=[
-            "name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`."
-        ],
-    )
+    if op_type == 'abs':
+        func.__doc__ = r"""
+
+Abs Operator.
+Perform elementwise abs for input `X`.
+
+.. math::
+
+    out = |x|
+
+Args:
+    x (Tensor): The input tensor of abs op.
+    out (Tensor): The output tensor of abs op.
+    name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`.
+"""
+    else:
+        func.__doc__ = _generate_doc_string_(
+            op_proto,
+            additional_args_lines=[
+                "name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`."
+            ],
+        )
     return func