wehub-resource-sync
55 lines
1.8 KiB
Plaintext
55 lines
1.8 KiB
Plaintext
// 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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#include "paddle/phi/kernels/lgamma_kernel.h"
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#include "paddle/phi/backends/gpu/gpu_context.h"
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#include "paddle/phi/common/amp_type_traits.h"
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#include "paddle/phi/core/kernel_registry.h"
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#include "paddle/phi/kernels/funcs/elementwise_base.h"
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namespace phi {
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template <typename T>
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struct CudaLgammaFunctor {
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__device__ __forceinline__ T operator()(const T x) const {
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using MT = typename MPTypeTrait<T>::Type;
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const MT mp_x = static_cast<MT>(x);
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return static_cast<T>(Eigen::numext::lgamma(mp_x));
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}
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};
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template <typename T, typename Context>
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void LgammaKernel(const Context& dev_ctx,
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const DenseTensor& x,
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DenseTensor* out) {
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// XKTODO( add gpu kernel implementation. )
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dev_ctx.template Alloc<T>(out);
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if (out && out->numel() == 0) {
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return;
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}
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std::vector<const DenseTensor*> ins = {&x};
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std::vector<DenseTensor*> outs = {out};
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auto functor = CudaLgammaFunctor<T>();
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funcs::ElementwiseKernel<T>(dev_ctx, ins, &outs, functor);
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}
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} // namespace phi
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PD_REGISTER_KERNEL(lgamma,
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GPU,
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ALL_LAYOUT,
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phi::LgammaKernel,
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float,
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double,
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phi::float16,
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phi::bfloat16) {}
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