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91 lines
2.6 KiB
91 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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#pragma once
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#include "paddle/framework/op_registry.h"
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namespace paddle {
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namespace operators {
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using Tensor = framework::Tensor;
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template <typename T>
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T tolerable_value(T x) {
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static_assert(std::is_floating_point<T>::value,
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"tolerable_value works only on float, "
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"double and double double.");
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const T kApproInf = 1e20;
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if (x == INFINITY) {
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return kApproInf;
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}
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if (x == -INFINITY) {
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return -kApproInf;
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}
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return x;
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}
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template <typename Place, typename T>
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class OnehotCrossEntropyOpKernel : public framework::OpKernel {
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public:
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void Compute(const framework::ExecutionContext& ctx) const override {
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auto X = ctx.Input<Tensor>("X");
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const T* Xdata = X->data<T>();
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const int* label_data = ctx.Input<Tensor>("label")->data<int>();
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auto Y = ctx.Output<Tensor>("Y");
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Y->mutable_data<T>(ctx.GetPlace());
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T* Ydata = Y->data<T>();
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int batch_size = X->dims()[0];
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int class_num = X->dims()[1];
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for (int i = 0; i < batch_size; ++i) {
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int index = i * class_num + label_data[i];
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Ydata[i] = -tolerable_value(std::log(Xdata[index]));
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}
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}
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};
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template <typename Place, typename T>
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class OnehotCrossEntropyGradientOpKernel : public framework::OpKernel {
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public:
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void Compute(const framework::ExecutionContext& ctx) const override {
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auto X = ctx.Input<Tensor>("X");
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auto dX = ctx.Output<Tensor>(framework::GradVarName("X"));
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auto dY = ctx.Input<Tensor>(framework::GradVarName("Y"));
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auto label = ctx.Input<Tensor>("label");
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auto* dXdata = dX->template mutable_data<T>(ctx.GetPlace());
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auto* dYdata = dY->template data<T>();
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auto* Xdata = X->template data<T>();
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auto* label_data = label->data<int>();
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const int batch_size = X->dims()[0];
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const int class_num = X->dims()[1];
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for (int i = 0; i < batch_size; ++i) {
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int index = i * class_num + label_data[i];
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dXdata[index] = -tolerable_value(dYdata[i] / Xdata[index]);
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}
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}
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};
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} // namespace operators
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} // namespace paddle
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