wehub-resource-sync
48 lines
1.6 KiB
C++
48 lines
1.6 KiB
C++
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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//
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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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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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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/phi/kernels/funcs/eigen/common.h"
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#include "paddle/phi/kernels/funcs/eigen/eigen_function.h"
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namespace phi {
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template <typename T, typename Context>
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void LogLossGradKernel(const Context& dev_ctx,
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const DenseTensor& input,
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const DenseTensor& label,
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const DenseTensor& out_grad,
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float epsilon,
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DenseTensor* in_grad) {
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if (in_grad && in_grad->numel() == 0) {
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dev_ctx.template Alloc<T>(in_grad);
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return;
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}
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auto prediction = EigenVector<T>::Flatten(input);
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auto label_out = EigenVector<T>::Flatten(label);
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auto dl = EigenVector<T>::Flatten(out_grad);
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auto& place = *dev_ctx.eigen_device();
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if (in_grad) {
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dev_ctx.template Alloc<T>(in_grad);
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auto dx = EigenVector<T>::Flatten(*in_grad);
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funcs::EigenLogLossGrad<std::decay_t<decltype(place)>, T>::Eval(
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place, dx, dl, prediction, label_out, epsilon);
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}
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}
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} // namespace phi
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