// 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.
#pragma once

#include <sys/stat.h>
#include <sys/types.h>
#include <unistd.h>

#include <algorithm>
#include <fstream>
#include <map>
#include <string>
#include <vector>

#include "core/sdk-cpp/builtin_format.pb.h"
#include "core/sdk-cpp/general_model_service.pb.h"
#include "core/sdk-cpp/include/common.h"
#include "core/sdk-cpp/include/predictor_sdk.h"

using baidu::paddle_serving::sdk_cpp::Predictor;
using baidu::paddle_serving::sdk_cpp::PredictorApi;

DECLARE_bool(profile_client);
DECLARE_bool(profile_server);

// given some input data, pack into pb, and send request
namespace baidu {
namespace paddle_serving {
namespace general_model {

class ModelRes {
 public:
  ModelRes() {}
  ~ModelRes() {}
 public:
  const std::vector<std::vector<int64_t>>& get_int64_by_name(
      const std::string& name) {
    return _int64_map[name];
  }
  const std::vector<std::vector<float>>& get_float_by_name(
      const std::string& name) {
    return _float_map[name];
  }
  void set_engine_name(const std::string& engine_name) {
    _engine_name = engine_name;
  }
  const std::string& engine_name() {
    return engine_name;
  }
  ModelRes& operator = (ModelRes&& res) {
    std::cout << "move ++++++++>";
    if (this != &res) {
      _int64_map = res._int64_map;
      _float_map = res._float_map;
      res._int64_map = nullptr;
      res._float_map = nullptr;
    }
    return *this;
  }
 public:
  std::string _engine_name;
  std::map<std::string, std::vector<std::vector<int64_t>>> _int64_map;
  std::map<std::string, std::vector<std::vector<float>>> _float_map;
};

class PredictorRes {
 public:
  PredictorRes() {}
  ~PredictorRes() {}

 public:
  void clear() {
    _models.clear();
    _engine_names.clear();    
  }
  const std::vector<std::vector<int64_t>>& get_int64_by_name(
      const int model_idx, const std::string& name) {
    return _models[model_idx].get_int64_by_name(name);
  }
  const std::vector<std::vector<float>>& get_float_by_name(
      const int model_idx, const std::string& name) {
    return _models[model_idx].get_float_by_name(name);
  }
  void add_model_res(ModelRes&& res) {
    _engine_names.push_back(res.engine_name());
    _models.emplace_back(res);
  }
  void set_variant_tag(const std::string& variant_tag) {
    _variant_tag = variant_tag;
  }
  const std::string& variant_tag() { return _variant_tag; }
  int model_num() {return _models.size();}
  const std::vector<std::string>& get_engine_names() {
    return _engine_names;
  }

 private:
  std::vector<ModelRes> _models;
  std::string _variant_tag;
  std::vector<std::string> _engine_names;
};

class PredictorClient {
 public:
  PredictorClient() {}
  ~PredictorClient() {}

  void init_gflags(std::vector<std::string> argv);

  int init(const std::string& client_conf);

  void set_predictor_conf(const std::string& conf_path,
                          const std::string& conf_file);

  int create_predictor_by_desc(const std::string& sdk_desc);

  int create_predictor();
  int destroy_predictor();

  int predict(const std::vector<std::vector<float>>& float_feed,
              const std::vector<std::string>& float_feed_name,
              const std::vector<std::vector<int64_t>>& int_feed,
              const std::vector<std::string>& int_feed_name,
              const std::vector<std::string>& fetch_name,
              PredictorRes& predict_res,  // NOLINT
              const int& pid);

  int batch_predict(
      const std::vector<std::vector<std::vector<float>>>& float_feed_batch,
      const std::vector<std::string>& float_feed_name,
      const std::vector<std::vector<std::vector<int64_t>>>& int_feed_batch,
      const std::vector<std::string>& int_feed_name,
      const std::vector<std::string>& fetch_name,
      PredictorRes& predict_res_batch,  // NOLINT
      const int& pid);

 private:
  PredictorApi _api;
  Predictor* _predictor;
  std::string _predictor_conf;
  std::string _predictor_path;
  std::string _conf_file;
  std::map<std::string, int> _feed_name_to_idx;
  std::map<std::string, int> _fetch_name_to_idx;
  std::map<std::string, std::string> _fetch_name_to_var_name;
  std::map<std::string, int> _fetch_name_to_type;
  std::vector<std::vector<int>> _shape;
  std::vector<int> _type;
  std::vector<int64_t> _last_request_ts;
};

}  // namespace general_model
}  // namespace paddle_serving
}  // namespace baidu

/* vim: set expandtab ts=4 sw=4 sts=4 tw=100: */