wehub-resource-sync
50 lines
2.0 KiB
C++
50 lines
2.0 KiB
C++
// Copyright (c) 2023 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/decayed_adagrad_kernel.h"
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#include "paddle/phi/kernels/funcs/eigen/common.h"
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namespace phi {
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template <typename T, typename Context>
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void DecayedAdagradDenseKernel(const Context& dev_ctx,
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const DenseTensor& param_t,
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const DenseTensor& grad_t,
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const DenseTensor& moment_t,
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const DenseTensor& learning_rate,
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float decay,
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float epsilon,
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DenseTensor* param_out_t,
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DenseTensor* moment_out_t) {
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dev_ctx.template Alloc<T>(param_out_t);
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dev_ctx.template Alloc<T>(moment_out_t);
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auto param = EigenVector<T>::Flatten(param_t);
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auto grad = EigenVector<T>::Flatten(grad_t);
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auto moment = EigenVector<T>::Flatten(moment_t);
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auto lr = EigenVector<T>::Flatten(learning_rate);
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auto param_out = EigenVector<T>::Flatten(*param_out_t);
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auto moment_out = EigenVector<T>::Flatten(*moment_out_t);
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auto& place = *dev_ctx.eigen_device();
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moment_out.device(place) = decay * moment + (1 - decay) * grad * grad;
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Eigen::DSizes<int, 1> m_dsize(moment_out_t->numel());
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param_out.device(place) =
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param - lr.broadcast(m_dsize) * grad / (moment_out.sqrt() + epsilon);
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}
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} // namespace phi
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