elementwise_sub_op.cc 6.7 KB
Newer Older
1
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
G
gongweibao 已提交
2

L
Luo Tao 已提交
3 4 5
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
G
gongweibao 已提交
6

L
Luo Tao 已提交
7
    http://www.apache.org/licenses/LICENSE-2.0
G
gongweibao 已提交
8

L
Luo Tao 已提交
9 10 11 12 13
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. */
G
gongweibao 已提交
14

W
Wu Yi 已提交
15
#include "paddle/fluid/operators/elementwise/elementwise_sub_op.h"
W
wanghuancoder 已提交
16

17
#include <string>
W
wanghuancoder 已提交
18

W
Wu Yi 已提交
19
#include "paddle/fluid/operators/elementwise/elementwise_op.h"
20 21 22

namespace paddle {
namespace platform {
23 24
template <typename T>
struct complex;
25 26
}  // namespace platform
}  // namespace paddle
27

W
wanghuancoder 已提交
28 29 30 31 32 33 34 35 36 37 38 39 40
namespace paddle {
namespace framework {
class OpDesc;
}  // namespace framework
namespace imperative {
class OpBase;
}  // namespace imperative
namespace platform {
class CPUDeviceContext;
struct CPUPlace;
}  // namespace platform
}  // namespace paddle

41 42 43
namespace paddle {
namespace operators {

44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70
template <typename T>
struct SameDimsElemwiseSub<
    platform::CPUDeviceContext, T,
    typename std::enable_if<std::is_floating_point<T>::value>::type> {
  void operator()(const framework::ExecutionContext &ctx,
                  const framework::Tensor *x, const framework::Tensor *y,
                  framework::Tensor *z) {
    auto blas = math::GetBlas<platform::CPUDeviceContext, T>(ctx);
    blas.VSUB(x->numel(), x->data<T>(), y->data<T>(), z->data<T>());
  }
};

template <typename T>
struct SameDimsElemwiseSub<
    platform::CPUDeviceContext, T,
    typename std::enable_if<!std::is_floating_point<T>::value>::type> {
  void operator()(const framework::ExecutionContext &ctx,
                  const framework::Tensor *x, const framework::Tensor *y,
                  framework::Tensor *z) {
    auto eigen_x = framework::EigenVector<T>::Flatten(*x);
    auto eigen_y = framework::EigenVector<T>::Flatten(*y);
    auto eigen_z = framework::EigenVector<T>::Flatten(*z);
    auto &place = *ctx.template device_context<platform::CPUDeviceContext>()
                       .eigen_device();
    eigen_z.device(place) = eigen_x - eigen_y;
  }
};
71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92
class ElementwiseSubOpMaker : public ElementwiseOpMaker {
 protected:
  std::string GetName() const override { return "Sub"; }
  std::string GetEquation() const override { return "Out = X - Y"; }

  void AddInputX() override {
    AddInput("X",
             "(Variable), Tensor or LoDTensor of any dimensions. Its dtype "
             "should be int32, int64, float32, float64.");
  }

  void AddInputY() override {
    AddInput("Y",
             "(Variable), Tensor or LoDTensor of any dimensions. Its dtype "
             "should be int32, int64, float32, float64.");
  }

  std::string GetOpFuntionality() const override {
    return "Substract two tensors element-wise";
  }
};

H
hong 已提交
93 94
template <typename T>
class ElementwiseSubDoubleGradMaker : public framework::SingleGradOpMaker<T> {
95
 public:
H
hong 已提交
96
  using framework::SingleGradOpMaker<T>::SingleGradOpMaker;
97 98

 protected:
99
  void Apply(GradOpPtr<T> op) const override {
100
    op->SetType("elementwise_sub_grad_grad");
H
hong 已提交
101 102 103 104
    op->SetInput("Y", this->Input("Y"));
    op->SetInput("DOut", this->Input(framework::GradVarName("Out")));
    op->SetInput("DDX", this->OutputGrad(framework::GradVarName("X")));
    op->SetInput("DDY", this->OutputGrad(framework::GradVarName("Y")));
105

H
hong 已提交
106
    op->SetAttrMap(this->Attrs());
107

H
hong 已提交
108
    op->SetOutput("DDOut", this->InputGrad(framework::GradVarName("Out")));
109 110 111 112 113 114
  }
};

}  // namespace operators
}  // namespace paddle

115
REGISTER_ELEMWISE_GRAD_MAKER(elementwise_sub, Sub);
116
REGISTER_ELEMWISE_EXPLICIT_OP_WITHOUT_GRAD(elementwise_sub, Sub);
117

118 119
namespace ops = paddle::operators;

H
hong 已提交
120
REGISTER_OPERATOR(
121 122
    elementwise_sub_grad, ops::ElementwiseOpGrad,
    ops::ElementwiseGradOpInplaceInferer, ops::ElementwiseGradNoBufVarsInferer,
H
hong 已提交
123 124
    ops::ElementwiseSubDoubleGradMaker<paddle::framework::OpDesc>,
    ops::ElementwiseSubDoubleGradMaker<paddle::imperative::OpBase>);
125
REGISTER_OPERATOR(elementwise_sub_grad_grad,
126
                  ops::ElementwiseOpDoubleGradWithoutDXDY,
127 128
                  ops::ElementwiseDoubleGradOpInplaceInferer,
                  ops::ElementwiseDoubleGradNoBufVarsInferer);
129

G
gongweibao 已提交
130 131
REGISTER_OP_CPU_KERNEL(
    elementwise_sub,
Q
QI JUN 已提交
132 133 134
    ops::ElementwiseSubKernel<paddle::platform::CPUDeviceContext, float>,
    ops::ElementwiseSubKernel<paddle::platform::CPUDeviceContext, double>,
    ops::ElementwiseSubKernel<paddle::platform::CPUDeviceContext, int>,
135 136
    ops::ElementwiseSubKernel<paddle::platform::CPUDeviceContext, int64_t>,
    ops::ElementwiseSubKernel<paddle::platform::CPUDeviceContext,
137
                              paddle::platform::complex<float>>,
138
    ops::ElementwiseSubKernel<paddle::platform::CPUDeviceContext,
139
                              paddle::platform::complex<double>>);
G
gongweibao 已提交
140 141
REGISTER_OP_CPU_KERNEL(
    elementwise_sub_grad,
Q
QI JUN 已提交
142 143 144
    ops::ElementwiseSubGradKernel<paddle::platform::CPUDeviceContext, float>,
    ops::ElementwiseSubGradKernel<paddle::platform::CPUDeviceContext, double>,
    ops::ElementwiseSubGradKernel<paddle::platform::CPUDeviceContext, int>,
145 146
    ops::ElementwiseSubGradKernel<paddle::platform::CPUDeviceContext, int64_t>,
    ops::ElementwiseSubGradKernel<paddle::platform::CPUDeviceContext,
147
                                  paddle::platform::complex<float>>,
148
    ops::ElementwiseSubGradKernel<paddle::platform::CPUDeviceContext,
149
                                  paddle::platform::complex<double>>);
150 151 152 153 154 155 156 157 158
REGISTER_OP_CPU_KERNEL(
    elementwise_sub_grad_grad,
    ops::ElementwiseSubDoubleGradKernel<paddle::platform::CPUDeviceContext,
                                        float>,
    ops::ElementwiseSubDoubleGradKernel<paddle::platform::CPUDeviceContext,
                                        double>,
    ops::ElementwiseSubDoubleGradKernel<paddle::platform::CPUDeviceContext,
                                        int>,
    ops::ElementwiseSubDoubleGradKernel<paddle::platform::CPUDeviceContext,
159 160
                                        int64_t>,
    ops::ElementwiseSubDoubleGradKernel<paddle::platform::CPUDeviceContext,
161
                                        paddle::platform::complex<float>>,
162
    ops::ElementwiseSubDoubleGradKernel<paddle::platform::CPUDeviceContext,
163
                                        paddle::platform::complex<double>>);
164 165 166 167 168 169 170 171 172

REGISTER_OP_VERSION(elementwise_sub)
    .AddCheckpoint(
        R"ROC(Register elementwise_sub for adding the attribute of Scale_y)ROC",
        paddle::framework::compatible::OpVersionDesc().NewAttr(
            "Scale_y",
            "In order to support the function of scaling the input Y when "
            "using the operator of elementwise_sub.",
            1.0f));