// 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/fpga/yolo_box_compute.h"
#include <vector>
#include "lite/backends/arm/math/funcs.h"
#include "lite/core/tensor.h"

namespace paddle {
namespace lite {
namespace kernels {
namespace fpga {

void YoloBoxCompute::PrepareForRun() {
  auto& param = Param<operators::YoloBoxParam>();
  lite::Tensor* X = param.X;
  lite::Tensor* ImgSize = param.ImgSize;
  lite::Tensor* Boxes = param.Boxes;
  lite::Tensor* Scores = param.Scores;

  Boxes->mutable_data<float>();
  Scores->mutable_data<float>();

  zynqmp::YoloBoxParam& yolobox_param = pe_.param();
  yolobox_param.input = X->ZynqTensor();
  yolobox_param.imgSize = ImgSize->ZynqTensor();
  yolobox_param.outputBoxes = Boxes->ZynqTensor();
  yolobox_param.outputScores = Scores->ZynqTensor();
  yolobox_param.downsampleRatio = param.downsample_ratio;
  yolobox_param.anchors = param.anchors;
  yolobox_param.classNum = param.class_num;
  yolobox_param.confThresh = param.conf_thresh;

  pe_.init();
  pe_.apply();
}

void YoloBoxCompute::Run() {
  pe_.dispatch();

  zynqmp::YoloBoxParam& yolobox_param = pe_.param();
  yolobox_param.imgSize->saveToFile("img_size", true);
  //   exit(-1);
  yolobox_param.outputBoxes->saveToFile("yolo_boxes", true);
  yolobox_param.outputScores->saveToFile("yolo_scores", true);
}

}  // namespace fpga
}  // namespace kernels
}  // namespace lite
}  // namespace paddle

// REGISTER_LITE_KERNEL(yolo_box,
//                      kFPGA,
//                      kFP16,
//                      kNHWC,
//                      paddle::lite::kernels::fpga::YoloBoxCompute,
//                      def)
//     .BindInput("X", {LiteType::GetTensorTy(TARGET(kFPGA),
//                                       PRECISION(kFP16),
//                                       DATALAYOUT(kNHWC))})
//     .BindInput("ImgSize",
//                {LiteType::GetTensorTy(TARGET(kARM), PRECISION(kInt32))})
//     .BindOutput("Boxes", {LiteType::GetTensorTy(TARGET(kARM))})
//     .BindOutput("Scores", {LiteType::GetTensorTy(TARGET(kARM))})
//     .Finalize();