cos_sim_op.cc 4.5 KB
Newer Older
X
Xinghai Sun 已提交
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.

   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/operators/cos_sim_op.h"

namespace paddle {
namespace operators {

using framework::Tensor;

class CosSimOp : public framework::OperatorWithKernel {
 public:
  using framework::OperatorWithKernel::OperatorWithKernel;

 protected:
  void InferShape(const framework::InferShapeContext &ctx) const override {
28 29
    PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("X"), "Input(X) must not be null.");
    PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("Y"), "Input(Y) must not be null.");
X
Xinghai Sun 已提交
30 31 32 33 34
    PADDLE_ENFORCE_EQ(ctx.Input<Tensor>("X")->dims(),
                      ctx.Input<Tensor>("Y")->dims(),
                      "Dimensions of Input(X) and Input(Y) must be the same.");

    auto dims = ctx.Input<Tensor>("X")->dims();
35 36 37
    ctx.Output<framework::LoDTensor>("Out")->Resize({dims[0], 1});
    ctx.Output<framework::LoDTensor>("XNorm")->Resize({dims[0], 1});
    ctx.Output<framework::LoDTensor>("YNorm")->Resize({dims[0], 1});
X
Xinghai Sun 已提交
38 39 40 41 42 43 44 45 46 47
  }
};

class CosSimOpMaker : public framework::OpProtoAndCheckerMaker {
 public:
  CosSimOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker)
      : OpProtoAndCheckerMaker(proto, op_checker) {
    AddInput("X", "The first input of cos_sim op.");
    AddInput("Y", "The second input of cos_sim op.");
    AddOutput("Out", "The output of cos_sim op.");
48 49 50
    AddOutput("XNorm", "Row norm of the first input.").AsIntermediate();
    AddOutput("YNorm", "Row norm of the second input.").AsIntermediate();

X
Xinghai Sun 已提交
51 52 53 54 55 56 57 58 59 60 61 62 63 64
    AddComment(R"DOC(
Cosine Similarity Operator.

The equation is: Out = X^T * Y / (sqrt(X^T * X) * sqrt(Y^T * Y))
)DOC");
  }
};

class CosSimOpGrad : public framework::OperatorWithKernel {
 public:
  using framework::OperatorWithKernel::OperatorWithKernel;

 protected:
  void InferShape(const framework::InferShapeContext &ctx) const override {
65 66 67 68 69 70
    PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("X"), "Input(X) must not be null.");
    PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("Y"), "Input(Y) must not be null.");
    PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("XNorm"),
                            "Input(XNorm) must not be null.");
    PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("YNorm"),
                            "Input(YNorm) must not be null.");
X
Xinghai Sun 已提交
71
    PADDLE_ENFORCE_NOT_NULL(ctx.InputVar(framework::GradVarName("Out")),
72
                            "Input(Out@GRAD) must not be null.");
X
Xinghai Sun 已提交
73 74 75

    auto x_dims = ctx.Input<Tensor>("X")->dims();
    auto y_dims = ctx.Input<Tensor>("Y")->dims();
76 77
    auto xnorm_dims = ctx.Input<Tensor>("XNorm")->dims();
    auto ynorm_dims = ctx.Input<Tensor>("YNorm")->dims();
X
Xinghai Sun 已提交
78 79 80
    auto out_dims = ctx.Input<Tensor>(framework::GradVarName("Out"))->dims();
    PADDLE_ENFORCE_EQ(x_dims, y_dims,
                      "Dimensions of Input(X) and Input(Y) must be the same.");
81 82 83 84 85 86
    PADDLE_ENFORCE_EQ(xnorm_dims[0], x_dims[0],
                      "1st dimension of XNorm must equal that of Input(X).");
    PADDLE_ENFORCE_EQ(xnorm_dims[1], 1, "2st dimension of XNorm must be one.");
    PADDLE_ENFORCE_EQ(ynorm_dims[0], y_dims[0],
                      "1st dimension of YNorm must equal that of Input(Y).");
    PADDLE_ENFORCE_EQ(ynorm_dims[1], 1, "2st dimension of YNorm must be one.");
X
Xinghai Sun 已提交
87
    PADDLE_ENFORCE_EQ(out_dims[0], x_dims[0],
88 89
                      "1st dimension of Out@GRAD must equal that of Input(X)");
    PADDLE_ENFORCE_EQ(out_dims[1], 1, "1st dimension of Out@GRAD must be one.");
X
Xinghai Sun 已提交
90

91 92 93 94
    auto *x_grad =
        ctx.Output<framework::LoDTensor>(framework::GradVarName("X"));
    auto *y_grad =
        ctx.Output<framework::LoDTensor>(framework::GradVarName("Y"));
95 96
    if (x_grad) x_grad->Resize(x_dims);
    if (y_grad) y_grad->Resize(y_dims);
X
Xinghai Sun 已提交
97 98 99 100 101 102 103 104 105 106 107 108 109
  }
};

}  // namespace operators
}  // namespace paddle

namespace ops = paddle::operators;
REGISTER_OP(cos_sim, ops::CosSimOp, ops::CosSimOpMaker, cos_sim_grad,
            ops::CosSimOpGrad);
REGISTER_OP_CPU_KERNEL(cos_sim,
                       ops::CosSimKernel<paddle::platform::CPUPlace, float>);
REGISTER_OP_CPU_KERNEL(
    cos_sim_grad, ops::CosSimGradKernel<paddle::platform::CPUPlace, float>);