Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into clip_op
wanghaoshuang
8 years ago
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/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License. */
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#include "paddle/operators/cos_sim_op.h"
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namespace paddle {
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namespace operators {
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using framework::Tensor;
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class CosSimOp : public framework::OperatorWithKernel {
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public:
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using framework::OperatorWithKernel::OperatorWithKernel;
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protected:
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void InferShape(const framework::InferShapeContext &ctx) const override {
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PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("X"), "Input(X) must not be null.");
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PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("Y"), "Input(Y) must not be null.");
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PADDLE_ENFORCE_EQ(ctx.Input<Tensor>("X")->dims(),
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ctx.Input<Tensor>("Y")->dims(),
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"Dimensions of Input(X) and Input(Y) must be the same.");
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auto dims = ctx.Input<Tensor>("X")->dims();
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ctx.Output<Tensor>("Out")->Resize({dims[0], 1});
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ctx.Output<Tensor>("XNorm")->Resize({dims[0], 1});
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ctx.Output<Tensor>("YNorm")->Resize({dims[0], 1});
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}
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};
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class CosSimOpMaker : public framework::OpProtoAndCheckerMaker {
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public:
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CosSimOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker)
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: OpProtoAndCheckerMaker(proto, op_checker) {
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AddInput("X", "The first input of cos_sim op.");
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AddInput("Y", "The second input of cos_sim op.");
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AddOutput("Out", "The output of cos_sim op.");
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AddOutput("XNorm", "Row norm of the first input.").AsIntermediate();
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AddOutput("YNorm", "Row norm of the second input.").AsIntermediate();
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AddComment(R"DOC(
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Cosine Similarity Operator.
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The equation is: Out = X^T * Y / (sqrt(X^T * X) * sqrt(Y^T * Y))
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)DOC");
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}
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};
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class CosSimOpGrad : public framework::OperatorWithKernel {
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public:
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using framework::OperatorWithKernel::OperatorWithKernel;
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protected:
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void InferShape(const framework::InferShapeContext &ctx) const override {
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PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("X"), "Input(X) must not be null.");
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PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("Y"), "Input(Y) must not be null.");
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PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("XNorm"),
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"Input(XNorm) must not be null.");
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PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("YNorm"),
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"Input(YNorm) must not be null.");
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PADDLE_ENFORCE_NOT_NULL(ctx.InputVar(framework::GradVarName("Out")),
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"Input(Out@GRAD) must not be null.");
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auto x_dims = ctx.Input<Tensor>("X")->dims();
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auto y_dims = ctx.Input<Tensor>("Y")->dims();
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auto xnorm_dims = ctx.Input<Tensor>("XNorm")->dims();
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auto ynorm_dims = ctx.Input<Tensor>("YNorm")->dims();
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auto out_dims = ctx.Input<Tensor>(framework::GradVarName("Out"))->dims();
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PADDLE_ENFORCE_EQ(x_dims, y_dims,
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"Dimensions of Input(X) and Input(Y) must be the same.");
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PADDLE_ENFORCE_EQ(xnorm_dims[0], x_dims[0],
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"1st dimension of XNorm must equal that of Input(X).");
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PADDLE_ENFORCE_EQ(xnorm_dims[1], 1, "2st dimension of XNorm must be one.");
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PADDLE_ENFORCE_EQ(ynorm_dims[0], y_dims[0],
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"1st dimension of YNorm must equal that of Input(Y).");
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PADDLE_ENFORCE_EQ(ynorm_dims[1], 1, "2st dimension of YNorm must be one.");
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PADDLE_ENFORCE_EQ(out_dims[0], x_dims[0],
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"1st dimension of Out@GRAD must equal that of Input(X)");
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PADDLE_ENFORCE_EQ(out_dims[1], 1, "1st dimension of Out@GRAD must be one.");
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auto *x_grad = ctx.Output<Tensor>(framework::GradVarName("X"));
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auto *y_grad = ctx.Output<Tensor>(framework::GradVarName("Y"));
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if (x_grad) x_grad->Resize(x_dims);
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if (y_grad) y_grad->Resize(y_dims);
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}
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};
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} // namespace operators
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} // namespace paddle
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namespace ops = paddle::operators;
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REGISTER_OP(cos_sim, ops::CosSimOp, ops::CosSimOpMaker, cos_sim_grad,
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ops::CosSimOpGrad);
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REGISTER_OP_CPU_KERNEL(cos_sim,
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ops::CosSimKernel<paddle::platform::CPUPlace, float>);
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REGISTER_OP_CPU_KERNEL(
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cos_sim_grad, ops::CosSimGradKernel<paddle::platform::CPUPlace, float>);
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