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2026-07-13 12:40:42 +08:00

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// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
//
// 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.
#pragma once
#include "paddle/phi/kernels/funcs/eigen/common.h"
#include "paddle/phi/kernels/funcs/eigen/eigen_function.h"
namespace phi {
template <typename T, typename Context>
void LogLossKernel(const Context& dev_ctx,
const DenseTensor& input,
const DenseTensor& label,
float epsilon,
DenseTensor* out) {
dev_ctx.template Alloc<T>(out);
if (out && out->numel() == 0) return;
auto prediction = EigenVector<T>::Flatten(input);
auto label_out = EigenVector<T>::Flatten(label);
auto loss = EigenVector<T>::Flatten(*out);
auto& place = *dev_ctx.eigen_device();
funcs::EigenLogLoss<std::decay_t<decltype(place)>, T>::Eval(
place, loss, prediction, label_out, epsilon);
}
} // namespace phi