wehub-resource-sync
67 lines
2.2 KiB
C++
67 lines
2.2 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/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 IgammaGradFunctor {
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IgammaGradFunctor(
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const T* dout, const T* x, const T* a, T* output, int64_t numel)
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: dout_(dout), x_(x), a_(a), output_(output), numel_(numel) {}
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HOSTDEVICE void operator()(int64_t idx) const {
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using MT = typename MPTypeTrait<T>::Type;
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const MT mp_dout = static_cast<MT>(dout_[idx]);
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const MT mp_x = static_cast<MT>(x_[idx]);
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const MT mp_a = static_cast<MT>(a_[idx]);
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const MT mp_a_1 = static_cast<MT>(a_[idx] - 1);
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output_[idx] = static_cast<T>(mp_dout * -std::exp(-mp_x) *
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std::pow(mp_x, mp_a_1) / std::tgamma(mp_a));
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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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const T* a_;
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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 GammainccGradKernel(const Context& dev_ctx,
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const DenseTensor& x,
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const DenseTensor& y,
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const DenseTensor& d_out,
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DenseTensor* d_y) {
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if (d_y && d_y->numel() == 0) {
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dev_ctx.template Alloc<T>(d_y);
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return;
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}
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auto numel = d_out.numel();
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auto* dout_data = d_out.data<T>();
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auto* x_data = x.data<T>();
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auto* y_data = y.data<T>();
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auto* dy_data =
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dev_ctx.template Alloc<T>(d_y, static_cast<size_t>(numel * sizeof(T)));
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funcs::ForRange<Context> for_range(dev_ctx, numel);
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IgammaGradFunctor<T> functor(dout_data, y_data, x_data, dy_data, numel);
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for_range(functor);
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}
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} // namespace phi
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