// 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/xpu/reduce_sum_compute.h"
#include <vector>
#include "lite/core/op_registry.h"

namespace paddle {
namespace lite {
namespace kernels {
namespace xpu {

void ReduceSumCompute::Run() {
  auto& param = Param<operators::ReduceParam>();
  auto& ctx = this->ctx_->As<XPUContext>();
  const float* input = param.x->data<float>();
  float* output = param.output->mutable_data<float>(TARGET(kXPU));
  bool reduce_all = param.reduce_all;

  if (reduce_all) {
    int input_len = param.x->numel();
    int r = xdnn::sum(ctx.GetRawContext(), input, output, input_len);
    CHECK_EQ(r, 0);
  } else {
    auto x_dims = param.x->dims();
    int x_rank = x_dims.size();
    auto reduce_dim = param.dim;
    auto rdim = reduce_dim.size();

    std::vector<int> idims;
    for (int i = 0; i < x_rank; i++) {
      idims.push_back(x_dims[i]);
    }

    auto type = xdnn::ReduceOp::REDUCE_SUM;
    int r = xdnn::reduce(ctx.GetRawContext(),
                         input,
                         output,
                         idims.data(),
                         x_rank,
                         reduce_dim.data(),
                         rdim,
                         type);
    CHECK_EQ(r, 0);
  }
}

}  // namespace xpu
}  // namespace kernels
}  // namespace lite
}  // namespace paddle

REGISTER_LITE_KERNEL(reduce_sum,
                     kXPU,
                     kFloat,
                     kNCHW,
                     paddle::lite::kernels::xpu::ReduceSumCompute,
                     def)
    .BindInput("X", {LiteType::GetTensorTy(TARGET(kXPU))})
    .BindOutput("Out", {LiteType::GetTensorTy(TARGET(kXPU))})
    .Finalize();