// 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 <gflags/gflags.h>
#ifdef PADDLE_WITH_TESTING
#include <gtest/gtest.h>
#endif
// "all_kernel_faked.cc" and "kernel_src_map.h" are created automatically during
// model_optimize_tool's compiling period
#include "all_kernel_faked.cc"  // NOLINT
#include "kernel_src_map.h"     // NOLINT
#include "lite/api/cxx_api.h"
#include "lite/api/paddle_api.h"
#include "lite/api/paddle_use_ops.h"
#include "lite/api/paddle_use_passes.h"
#include "lite/core/op_registry.h"
#include "lite/utils/cp_logging.h"
#include "lite/utils/string.h"

DEFINE_string(model_dir,
              "",
              "path of the model. This option will be ignored if model_file "
              "and param_file are exist");
DEFINE_string(model_filename,
              "",
              "model topo filename of the model in models set. This option"
              " will be used to specific tailoring");
DEFINE_string(param_filename,
              "",
              "model param filename of the model in models set. This option"
              " will be used to specific tailoring");
DEFINE_string(model_set_dir,
              "",
              "path of the models set. This option will be used to specific"
              " tailoring");
DEFINE_string(model_file, "", "model file path of the combined-param model");
DEFINE_string(param_file, "", "param file path of the combined-param model");
DEFINE_string(
    optimize_out_type,
    "protobuf",
    "store type of the output optimized model. protobuf/naive_buffer");
DEFINE_bool(display_kernels, false, "Display kernel information");
DEFINE_bool(record_tailoring_info,
            false,
            "Record kernels and operators information of the optimized model "
            "for tailoring compiling, information are stored into optimized "
            "model path as hidden files");
DEFINE_string(optimize_out, "", "path of the output optimized model");
DEFINE_string(valid_targets,
              "arm",
              "The targets this model optimized for, should be one of (arm, "
              "opencl, x86), splitted by space");
DEFINE_bool(prefer_int8_kernel, false, "Prefer to run model with int8 kernels");

namespace paddle {
namespace lite_api {

//! Display the kernel information.
void DisplayKernels() {
  LOG(INFO) << ::paddle::lite::KernelRegistry::Global().DebugString();
}

std::vector<Place> ParserValidPlaces() {
  std::vector<Place> valid_places;
  auto target_reprs = lite::Split(FLAGS_valid_targets, ",");
  for (auto& target_repr : target_reprs) {
    if (target_repr == "arm") {
      valid_places.emplace_back(TARGET(kARM));
    } else if (target_repr == "opencl") {
      valid_places.emplace_back(
          Place{TARGET(kOpenCL), PRECISION(kFP16), DATALAYOUT(kNCHW)});
      valid_places.emplace_back(
          Place{TARGET(kOpenCL), PRECISION(kFP16), DATALAYOUT(kNHWC)});
      valid_places.emplace_back(
          Place{TARGET(kOpenCL), PRECISION(kFloat), DATALAYOUT(kNCHW)});
      valid_places.emplace_back(
          Place{TARGET(kOpenCL), PRECISION(kFloat), DATALAYOUT(kNHWC)});
      valid_places.emplace_back(
          TARGET(kARM));  // enable kARM CPU kernel when no opencl kernel
    } else if (target_repr == "x86") {
      valid_places.emplace_back(TARGET(kX86));
    } else {
      LOG(FATAL) << lite::string_format(
          "Wrong target '%s' found, please check the command flag "
          "'valid_targets'",
          target_repr.c_str());
    }
  }

  CHECK(!valid_places.empty())
      << "At least one target should be set, should set the "
         "command argument 'valid_targets'";

  if (FLAGS_prefer_int8_kernel) {
    LOG(WARNING) << "Int8 mode is only support by ARM target";
    valid_places.insert(valid_places.begin(),
                        Place{TARGET(kARM), PRECISION(kInt8)});
  }
  return valid_places;
}

void RunOptimize(const std::string& model_dir,
                 const std::string& model_file,
                 const std::string& param_file,
                 const std::string& optimize_out,
                 const std::string& optimize_out_type,
                 const std::vector<Place>& valid_places,
                 bool record_tailoring_info) {
  if (!model_file.empty() && !param_file.empty()) {
    LOG(WARNING)
        << "Load combined-param model. Option model_dir will be ignored";
  }

  lite_api::CxxConfig config;
  config.set_model_dir(model_dir);
  config.set_model_file(model_file);
  config.set_param_file(param_file);

  config.set_valid_places(valid_places);

  auto predictor = lite_api::CreatePaddlePredictor(config);

  LiteModelType model_type;
  if (optimize_out_type == "protobuf") {
    model_type = LiteModelType::kProtobuf;
  } else if (optimize_out_type == "naive_buffer") {
    model_type = LiteModelType::kNaiveBuffer;
  } else {
    LOG(FATAL) << "Unsupported Model type :" << optimize_out_type;
  }

  OpKernelInfoCollector::Global().SetKernel2path(kernel2path_map);
  predictor->SaveOptimizedModel(
      optimize_out, model_type, record_tailoring_info);
  if (record_tailoring_info) {
    LOG(INFO) << "Record the information of tailored model into :"
              << optimize_out;
  }
}

void CollectModelMetaInfo(const std::string& output_dir,
                          const std::vector<std::string>& models,
                          const std::string& filename) {
  std::set<std::string> total;
  for (const auto& name : models) {
    std::string model_path =
        lite::Join<std::string>({output_dir, name, filename}, "/");
    auto lines = lite::ReadLines(model_path);
    total.insert(lines.begin(), lines.end());
  }
  std::string output_path =
      lite::Join<std::string>({output_dir, filename}, "/");
  lite::WriteLines(std::vector<std::string>(total.begin(), total.end()),
                   output_path);
}

void Main() {
  if (FLAGS_display_kernels) {
    DisplayKernels();
    exit(0);
  }

  auto valid_places = ParserValidPlaces();
  if (FLAGS_model_set_dir == "") {
    RunOptimize(FLAGS_model_dir,
                FLAGS_model_file,
                FLAGS_param_file,
                FLAGS_optimize_out,
                FLAGS_optimize_out_type,
                valid_places,
                FLAGS_record_tailoring_info);
    return;
  }

  if (!FLAGS_record_tailoring_info) {
    LOG(WARNING) << "--model_set_dir option only be used with "
                    "--record_tailoring_info=true together";
    return;
  }

  auto model_dirs = lite::ListDir(FLAGS_model_set_dir, true);
  if (model_dirs.size() == 0) {
    LOG(FATAL) << "[" << FLAGS_model_set_dir << "] does not contain any model";
  }
  // Optimize models in FLAGS_model_set_dir
  for (const auto& name : model_dirs) {
    std::string input_model_dir =
        lite::Join<std::string>({FLAGS_model_set_dir, name}, "/");
    std::string output_model_dir =
        lite::Join<std::string>({FLAGS_optimize_out, name}, "/");

    std::string model_file = "";
    std::string param_file = "";

    if (FLAGS_model_filename != "" && FLAGS_param_filename != "") {
      model_file =
          lite::Join<std::string>({input_model_dir, FLAGS_model_filename}, "/");
      param_file =
          lite::Join<std::string>({input_model_dir, FLAGS_param_filename}, "/");
    }

    LOG(INFO) << "Start optimize model: " << input_model_dir;
    RunOptimize(input_model_dir,
                model_file,
                param_file,
                output_model_dir,
                FLAGS_optimize_out_type,
                valid_places,
                FLAGS_record_tailoring_info);
    LOG(INFO) << "Optimize done. ";
  }

  // Collect all models information
  CollectModelMetaInfo(
      FLAGS_optimize_out, model_dirs, lite::TAILORD_OPS_SOURCE_LIST_FILENAME);
  CollectModelMetaInfo(
      FLAGS_optimize_out, model_dirs, lite::TAILORD_OPS_LIST_NAME);
  CollectModelMetaInfo(FLAGS_optimize_out,
                       model_dirs,
                       lite::TAILORD_KERNELS_SOURCE_LIST_FILENAME);
  CollectModelMetaInfo(
      FLAGS_optimize_out, model_dirs, lite::TAILORD_KERNELS_LIST_NAME);
}

}  // namespace lite_api
}  // namespace paddle

int main(int argc, char** argv) {
  google::ParseCommandLineFlags(&argc, &argv, false);
  paddle::lite_api::Main();
  return 0;
}