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69 lines
2.6 KiB
69 lines
2.6 KiB
/* 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/softmax_op.h"
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namespace paddle {
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namespace operators {
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class SoftmaxOp : public OperatorWithKernel {
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protected:
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void InferShape(const InferShapeContext &ctx) const override {
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PADDLE_ENFORCE(ctx.InputSize() == 1UL,
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"Only one input is need for softmax");
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PADDLE_ENFORCE(ctx.Input<Tensor>("X")->dims().size() == 2UL,
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"The input of softmax op must be matrix");
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PADDLE_ENFORCE(ctx.OutputSize() == 1UL,
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"Only one output is need for softmax");
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ctx.Output<Tensor>("Y")->Resize(ctx.Input<Tensor>("X")->dims());
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}
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};
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class SoftmaxOpMaker : public OpProtoAndCheckerMaker {
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public:
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SoftmaxOpMaker(OpProto *proto, OpAttrChecker *op_checker)
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: OpProtoAndCheckerMaker(proto, op_checker) {
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AddInput("X", "input of softmax");
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AddOutput("Y", "output of softmax");
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AddComment("Softmax Op");
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}
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};
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class SoftmaxOpGrad : public OperatorWithKernel {
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protected:
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void InferShape(const InferShapeContext &ctx) const override {
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PADDLE_ENFORCE(ctx.InputSize() == 3UL,
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"Input of SoftmaxOpGrad should be 3, X, Y, YG");
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PADDLE_ENFORCE(ctx.OutputSize() == 1UL,
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"Output of SoftmaxOpGrad should be 1");
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PADDLE_ENFORCE(ctx.InputVar("Y") != nullptr, "Input(Y) should not be null");
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PADDLE_ENFORCE(ctx.InputVar(GRAD_VAR_NAME("Y")) != nullptr,
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"Input(Y@GRAD) should not be null");
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PADDLE_ENFORCE(ctx.Input<Tensor>("Y")->dims() ==
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ctx.Input<Tensor>(GRAD_VAR_NAME("Y"))->dims(),
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"the shape of Input(0) and Input(1) should be the same");
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ctx.Output<Tensor>(GRAD_VAR_NAME("X"))
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->Resize(ctx.Input<Tensor>("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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REGISTER_OP(softmax, ops::SoftmaxOp, ops::SoftmaxOpMaker);
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REGISTER_OP_CPU_KERNEL(softmax, ops::SoftmaxKernel<ops::CPUPlace, float>);
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REGISTER_GRADIENT_OP(softmax, softmax_grad, ops::SoftmaxOpGrad);
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REGISTER_OP_CPU_KERNEL(softmax_grad,
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ops::SoftmaxGradKernel<ops::CPUPlace, float>);
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