split_compute.cc 2.5 KB
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// Copyright (c) 2019 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.

#include "lite/kernels/arm/split_compute.h"
#include <vector>
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#include "lite/backends/arm/math/funcs.h"
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namespace paddle {
namespace lite {
namespace kernels {
namespace arm {

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template <typename T, PrecisionType PType>
void SplitCompute<T, PType>::Run() {
  auto& param = this->template Param<operators::SplitParam>();
  const T* din = param.x->template data<T>();
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  auto& dout = param.output;
  auto in_dim = param.x->dims();
  std::vector<int> in_strides(in_dim.size());
  in_strides[in_dim.size() - 1] = in_dim[in_dim.size() - 1];
  for (int i = in_dim.size() - 2; i >= 0; --i) {
    in_strides[i] = in_strides[i + 1] * in_dim[i];
  }
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  for (auto out : dout) {
    out->set_lod(param.x->lod());
  }
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  lite::arm::math::split(din, dout, param.axis, in_strides);
}

}  // namespace arm
}  // namespace kernels
}  // namespace lite
}  // namespace paddle

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using split_float =
    paddle::lite::kernels::arm::SplitCompute<float, PRECISION(kFloat)>;
REGISTER_LITE_KERNEL(split, kARM, kFloat, kNCHW, split_float, def)
    .BindInput("X", {LiteType::GetTensorTy(TARGET(kARM), PRECISION(kFloat))})
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    .BindInput("AxisTensor",
               {LiteType::GetTensorTy(TARGET(kARM), PRECISION(kInt32))})
    .BindInput("SectionsTensorList",
               {LiteType::GetTensorTy(TARGET(kARM), PRECISION(kInt32))})
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    .BindOutput("Out", {LiteType::GetTensorTy(TARGET(kARM), PRECISION(kFloat))})
    .Finalize();

using split_int64 =
    paddle::lite::kernels::arm::SplitCompute<int64_t, PRECISION(kInt64)>;
REGISTER_LITE_KERNEL(split, kARM, kInt64, kNCHW, split_int64, def)
    .BindInput("X", {LiteType::GetTensorTy(TARGET(kARM), PRECISION(kInt64))})
    .BindInput("AxisTensor",
               {LiteType::GetTensorTy(TARGET(kARM), PRECISION(kInt32))})
    .BindInput("SectionsTensorList",
               {LiteType::GetTensorTy(TARGET(kARM), PRECISION(kInt32))})
    .BindOutput("Out", {LiteType::GetTensorTy(TARGET(kARM), PRECISION(kInt64))})
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    .Finalize();