/* Copyright (c) 2016 Baidu, Inc. All Rights Reserved.
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
==============================================================================*/
#pragma once
#include "../test_include.h"
#include "operators/box_coder_op.h"

namespace paddle_mobile {
namespace framework {

template <typename Dtype>
class TestBoxCoderOp {
 public:
  explicit TestBoxCoderOp(const Program<Dtype> p) : program_(p) {
    if (use_optimize_) {
      to_predict_program_ = program_.optimizeProgram;
    } else {
      to_predict_program_ = program_.originProgram;
    }

    const std::vector<std::shared_ptr<BlockDesc>> blocks =
        to_predict_program_->Blocks();
    //  DLOG << " **block size " << blocks.size();
    for (auto block_desc : blocks) {
      std::vector<std::shared_ptr<OpDesc>> ops = block_desc->Ops();
      //    DLOG << " ops " << ops.size();
      for (auto op : ops) {
        if (op->Type() == "box_coder" &&
            op->Input("PriorBox")[0] == "concat_0.tmp_0") {
          DLOG << " mul attr size: " << op->GetAttrMap().size();
          DLOG << " inputs size: " << op->GetInputs().size();
          DLOG << " outputs size: " << op->GetOutputs().size();
          DLOG << " Input PriorBox is : " << op->Input("PriorBox")[0];
          DLOG << " Input PriorBoxVar is : " << op->Input("PriorBoxVar")[0];
          DLOG << " Input TargetBox is : " << op->Input("TargetBox")[0];
          DLOG << " OutputBox is : " << op->Output("OutputBox")[0];
          DLOG << " code_type : "
               << op->GetAttrMap().at("code_type").Get<std::string>();
          std::shared_ptr<operators::BoxCoderOp<Dtype, float>> boxcoder =
              std::make_shared<operators::BoxCoderOp<Dtype, float>>(
                  op->Type(), op->GetInputs(), op->GetOutputs(),
                  op->GetAttrMap(), program_.scope);
          ops_of_block_[*block_desc.get()].push_back(boxcoder);
        }
      }
    }
  }

  std::shared_ptr<Tensor> predict_boxcoder(const Tensor &t1, const Tensor &t2,
                                           const Tensor &t3) {
    // feed
    auto scope = program_.scope;
    Variable *prior_box = scope->Var("concat_0.tmp_0");
    auto tensor_x1 = prior_box->GetMutable<Tensor>();
    tensor_x1->ShareDataWith(t1);

    Variable *prior_box_var = scope->Var("concat_1.tmp_0");
    auto tensor_x2 = prior_box_var->GetMutable<Tensor>();
    tensor_x2->ShareDataWith(t2);

    Variable *target_box = scope->Var("concat_2.tmp_0");
    auto tensor_x3 = target_box->GetMutable<Tensor>();
    tensor_x3->ShareDataWith(t3);

    Variable *boxes_output = scope->Var("box_coder_0.tmp_0");
    auto *boxes_output_tensor = boxes_output->GetMutable<Tensor>();
    boxes_output_tensor->mutable_data<float>({1, 1917, 4});

    //  DLOG << typeid(output_tensor).name();
    //  DLOG << "output_tensor dims: " << output_tensor->dims();

    std::shared_ptr<Tensor> outbox_tensor = std::make_shared<LoDTensor>();
    outbox_tensor.reset(boxes_output_tensor);

    predict_boxcoder(t1, t2, t3, 0);

    return outbox_tensor;
  }

 private:
  const framework::Program<Dtype> program_;
  std::shared_ptr<ProgramDesc> to_predict_program_;
  std::map<framework::BlockDesc,
           std::vector<std::shared_ptr<OperatorBase<Dtype>>>>
      ops_of_block_;
  bool use_optimize_ = false;

  void predict_boxcoder(const Tensor &t1, const Tensor &t2, const Tensor &t3,
                        int block_id) {
    std::shared_ptr<BlockDesc> to_predict_block =
        to_predict_program_->Block(block_id);
    for (int j = 0; j < ops_of_block_[*to_predict_block.get()].size(); ++j) {
      auto op = ops_of_block_[*to_predict_block.get()][j];
      DLOG << "op -> run()";
      op->Run();
    }
  }
};

template class TestBoxCoderOp<CPU>;
}  // namespace framework
}  // namespace paddle_mobile

int main() {
  DLOG << "----------**********----------";
  DLOG << "begin to run BoxCoderOp Test";
  paddle_mobile::Loader<paddle_mobile::CPU> loader;
  auto program = loader.Load(std::string("../../test/models/mobilenet+ssd"));

  paddle_mobile::framework::Tensor priorbox;
  SetupTensor<float>(&priorbox, {1917, 4}, static_cast<float>(0),
                     static_cast<float>(1));
  auto *priorbox_ptr = priorbox.data<float>();

  paddle_mobile::framework::Tensor priorboxvar;
  SetupTensor<float>(&priorboxvar, {1917, 4}, static_cast<float>(0.1),
                     static_cast<float>(0.2));
  auto *priorboxvar_ptr = priorboxvar.data<float>();

  paddle_mobile::framework::Tensor targetbox;
  SetupTensor<float>(&targetbox, {1, 1917, 4}, static_cast<float>(0),
                     static_cast<float>(1));
  auto *targetbox_ptr = targetbox.data<float>();

  paddle_mobile::framework::TestBoxCoderOp<paddle_mobile::CPU> testBoxCoderOp(
      program);

  auto output_boxcoder =
      testBoxCoderOp.predict_boxcoder(priorbox, priorboxvar, targetbox);
  auto output_boxcoder_ptr = output_boxcoder->data<float>();

  for (int i = 0; i < output_boxcoder->numel(); i++) {
    DLOG << output_boxcoder_ptr[i];
  }
  DLOGF("\n");
  /// testing 25th bbox.
  DLOG << "PriorBox**************";
  DLOG << priorbox_ptr[100];
  DLOG << priorbox_ptr[101];
  DLOG << priorbox_ptr[102];
  DLOG << priorbox_ptr[103];
  DLOG << "PriorBoxVar**************";
  DLOG << priorboxvar_ptr[100];
  DLOG << priorboxvar_ptr[101];
  DLOG << priorboxvar_ptr[102];
  DLOG << priorboxvar_ptr[103];
  DLOG << "TargetBox***************";
  DLOG << targetbox_ptr[100];
  DLOG << targetbox_ptr[101];
  DLOG << targetbox_ptr[102];
  DLOG << targetbox_ptr[103];
  DLOG << "OutputBox**************";
  DLOG << output_boxcoder_ptr[100];
  DLOG << output_boxcoder_ptr[101];
  DLOG << output_boxcoder_ptr[102];
  DLOG << output_boxcoder_ptr[103];

  DLOG << "***********----------------------**************";
  auto priorbox_w = priorbox_ptr[102] - priorbox_ptr[100];
  auto priorbox_h = priorbox_ptr[103] - priorbox_ptr[101];
  auto priorbox_center_x = (priorbox_ptr[100] + priorbox_ptr[102]) / 2;
  auto priorbox_center_y = (priorbox_ptr[101] + priorbox_ptr[103]) / 2;
  DLOG << "prior box width : " << priorbox_w;
  DLOG << "prior box height : " << priorbox_h;
  DLOG << "prior box center x : " << priorbox_center_x;
  DLOG << "prior box center y : " << priorbox_center_y;
  auto target_box_center_x =
      priorboxvar_ptr[100] * targetbox_ptr[100] * priorbox_w +
      priorbox_center_x;
  DLOG << "target_box_center_x : " << target_box_center_x;
  auto target_box_center_y =
      priorboxvar_ptr[101] * targetbox_ptr[101] * priorbox_h +
      priorbox_center_y;
  DLOG << "target_box_center_y : " << target_box_center_y;
  auto target_box_width =
      std::exp(priorboxvar_ptr[102] * targetbox_ptr[102]) * priorbox_w;
  DLOG << "target_box_width : " << target_box_width;
  auto target_box_height =
      std::exp(priorboxvar_ptr[103] * targetbox_ptr[103]) * priorbox_h;
  DLOG << "target_box_height : " << target_box_height;
  DLOG << "pre x min : " << target_box_center_x - target_box_width / 2;
  DLOG << "pre y min : " << target_box_center_y - target_box_height / 2;
  DLOG << "pre x max : " << target_box_center_x + target_box_width / 2;
  DLOG << "pre y max : " << target_box_center_y + target_box_height / 2;
  return 0;
}