wehub-resource-sync
70 lines
2.2 KiB
Plaintext
70 lines
2.2 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/mean_all_kernel.h"
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#include "paddle/phi/common/memory_utils.h"
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#include "paddle/phi/core/kernel_registry.h"
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#include "paddle/phi/kernels/full_kernel.h"
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#include "paddle/phi/kernels/funcs/reduce_function.h"
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#include "paddle/phi/kernels/primitive/functor_primitives.h"
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namespace phi {
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template <typename T, typename Context>
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void MeanAllKernel(const Context& dev_ctx,
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const DenseTensor& x,
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DenseTensor* out) {
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if (x.numel() == 0) {
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Full<T, Context>(dev_ctx, out->dims(), NAN, out);
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return;
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}
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const T* in_data = x.data<T>();
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T* out_data = dev_ctx.template Alloc<T>(out);
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auto numel = x.numel();
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auto rank = x.dims().size();
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auto place = dev_ctx.GetPlace();
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auto stream = dev_ctx.stream();
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if (rank == 0) { // scalar
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memory_utils::Copy(
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place, out_data, place, in_data, numel * sizeof(T), stream);
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return;
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}
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std::vector<int> reduce_dims;
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reduce_dims.reserve(rank);
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for (decltype(rank) i = 0; i < rank; ++i) {
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reduce_dims.push_back(i);
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}
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funcs::ReduceKernel<T,
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T,
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kps::AddFunctor,
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kps::IdentityFunctor<T>,
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/*is_mean*/ true>(
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dev_ctx, x, out, kps::IdentityFunctor<T>(), reduce_dims);
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}
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} // namespace phi
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PD_REGISTER_KERNEL(mean_all,
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GPU,
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ALL_LAYOUT,
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phi::MeanAllKernel,
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float,
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double,
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phi::float16,
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phi::complex64,
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phi::complex128) {}
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