split_kernel.cc 2.6 KB
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// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
//     http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.

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#include "paddle/phi/kernels/split_kernel.h"
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#include "paddle/fluid/operators/strided_memcpy.h"
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#include "paddle/phi/common/float16.h"
#include "paddle/phi/core/kernel_registry.h"
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#include "paddle/phi/infermeta/unary.h"
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#include "paddle/phi/kernels/funcs/concat_and_split_functor.h"
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namespace phi {
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template <typename T, typename Context>
void SplitKernel(const Context& dev_ctx,
                 const DenseTensor& x,
                 const ScalarArray& num_or_sections,
                 const Scalar& axis_scalar,
                 std::vector<DenseTensor*> outs) {
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  // need to infershape output
  if (num_or_sections.FromTensor() || axis_scalar.FromTensor()) {
    std::vector<MetaTensor> out_metas;
    out_metas.reserve(outs.size());
    std::vector<MetaTensor*> out_metas_ptr;
    for (size_t i = 0; i < outs.size(); ++i) {
      out_metas.push_back(outs[i]);
      out_metas_ptr.push_back(&out_metas.back());
    }

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    phi::SplitInferMeta(x, num_or_sections, axis_scalar, out_metas_ptr);
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    for (size_t i = 0; i < out_metas.size(); ++i) {
      outs[i]->Resize(out_metas[i].dims());
    }
  }

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  std::vector<const DenseTensor*> shape_refer;
  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]);
  }

  int axis = axis_scalar.to<int>();
  // Sometimes direct copies will be faster, this maybe need deeply analysis.
  if (axis == 0 && outs.size() < 10) {
    paddle::operators::StridedMemcpyWithAxis0<T>(
        dev_ctx, x, shape_refer, &outs);
  } else {
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    phi::funcs::SplitFunctor<Context, T> functor;
    functor(dev_ctx, x, shape_refer, axis, &outs);
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  }
}

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}  // namespace phi
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PD_REGISTER_KERNEL(split,
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                   CPU,
                   ALL_LAYOUT,
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                   phi::SplitKernel,
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                   float,
                   double,
                   int64_t,
                   int,
                   bool,
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                   phi::dtype::float16,
                   phi::dtype::bfloat16) {}