wehub-resource-sync
63 lines
2.0 KiB
C++
63 lines
2.0 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/common/amp_type_traits.h"
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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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#include "paddle/phi/kernels/huber_loss_kernel.h"
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namespace phi {
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template <typename T>
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struct HuberLossForward {
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HOSTDEVICE HuberLossForward(const T& delta) : delta(delta) {}
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HOSTDEVICE T operator()(const T& val) const {
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T abs_val = abs(val);
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if (abs_val <= delta) {
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return static_cast<T>(0.5) * val * val;
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} else {
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return delta * (abs_val - static_cast<T>(0.5) * delta);
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}
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}
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T delta;
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};
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template <typename T, typename Context>
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void HuberLossKernel(const Context& dev_ctx,
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const DenseTensor& input,
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const DenseTensor& label,
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float delta,
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DenseTensor* out,
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DenseTensor* residual) {
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T delta_ = static_cast<T>(delta);
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auto& place = *dev_ctx.eigen_device();
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auto x = EigenVector<T>::Flatten(input);
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auto y = EigenVector<T>::Flatten(label);
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dev_ctx.template Alloc<T>(residual);
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auto eigen_residual = EigenVector<T>::Flatten(*residual);
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eigen_residual.device(place) = y - x;
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dev_ctx.template Alloc<T>(out);
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auto loss = EigenVector<T>::Flatten(*out);
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loss.device(place) = eigen_residual.unaryExpr(HuberLossForward<T>(delta_));
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}
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} // namespace phi
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