wehub-resource-sync
65 lines
2.0 KiB
C++
65 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 <unsupported/Eigen/SpecialFunctions>
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#include "paddle/phi/common/amp_type_traits.h"
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#include "paddle/phi/core/dense_tensor.h"
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#include "paddle/phi/kernels/funcs/for_range.h"
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namespace phi {
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template <typename T>
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struct DigammaGradFunctor {
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DigammaGradFunctor(const T* dout, const T* x, T* output, int64_t numel)
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: dout_(dout), x_(x), output_(output), numel_(numel) {}
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HOSTDEVICE void operator()(int64_t idx) const {
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using MPType = typename MPTypeTrait<T>::Type;
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const MPType mp_dout = static_cast<MPType>(dout_[idx]);
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const MPType mp_x = static_cast<MPType>(x_[idx]);
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output_[idx] =
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static_cast<T>(mp_dout * Eigen::numext::polygamma(MPType(1), mp_x));
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}
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private:
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const T* dout_;
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const T* x_;
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T* output_;
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int64_t numel_;
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};
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template <typename T, typename Context>
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void DigammaGradKernel(const Context& dev_ctx,
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const DenseTensor& x,
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const DenseTensor& out_grad,
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DenseTensor* x_grad) {
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dev_ctx.template Alloc<T>(x_grad);
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if (x_grad && x_grad->numel() == 0) {
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return;
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}
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auto* dout_data = out_grad.data<T>();
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auto* x_data = x.data<T>();
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auto* dx_data = x_grad->data<T>();
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auto numel = out_grad.numel();
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funcs::ForRange<Context> for_range(dev_ctx, numel);
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DigammaGradFunctor<T> functor(dout_data, x_data, dx_data, numel);
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for_range(functor);
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}
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} // namespace phi
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