wehub-resource-sync
64 lines
2.3 KiB
C++
64 lines
2.3 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 "paddle/phi/kernels/split_kernel.h"
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#include "paddle/phi/common/int_array.h"
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#include "paddle/phi/common/scalar.h"
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#include "paddle/phi/core/dense_tensor.h"
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#include "paddle/phi/kernels/funcs/concat_and_split_functor.h"
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#include "paddle/phi/kernels/funcs/strided_memcpy.h"
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namespace phi {
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template <typename T, typename Context>
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void SplitKernel(const Context& dev_ctx,
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const DenseTensor& x,
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const IntArray& sections UNUSED,
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const Scalar& axis_scalar,
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std::vector<DenseTensor*> outs) {
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std::vector<const DenseTensor*> shape_refer;
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for (size_t j = 0; j < outs.size(); ++j) {
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dev_ctx.template Alloc<T>(outs[j]);
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shape_refer.emplace_back(outs[j]);
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}
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int axis = axis_scalar.to<int>();
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// Sometimes direct copies will be faster, this maybe need deeply analysis.
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if (axis == 0 && outs.size() < 10) {
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funcs::StridedMemcpyWithAxis0<T, Context>(dev_ctx, x, shape_refer, &outs);
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} else {
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funcs::SplitFunctor<Context, T> functor;
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functor(dev_ctx, x, shape_refer, axis, &outs);
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}
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}
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template <typename T, typename Context>
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void SplitWithNumKernel(const Context& dev_ctx,
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const DenseTensor& x,
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int num,
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const Scalar& axis_scalar,
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std::vector<DenseTensor*> outs) {
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int axis_value = axis_scalar.to<int>();
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auto input_axis_dim = x.dims().at(axis_value);
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std::vector<int64_t> sections_vec;
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for (int i = 0; i < num; ++i) {
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sections_vec.push_back(input_axis_dim / num);
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}
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IntArray sections(sections_vec);
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SplitKernel<T, Context>(dev_ctx, x, sections, axis_scalar, outs);
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}
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} // namespace phi
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