/* Copyright (c) 2018 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 <vector>
#include "common/types.h"
#include "io/paddle_inference_api.h"
#include "io/paddle_mobile.h"

namespace paddle_mobile {

template <typename Device = CPU, typename T = float>
class PaddleMobilePredictor : public PaddlePredictor {
 public:
  PaddleMobilePredictor() = delete;

  explicit PaddleMobilePredictor(const PaddleMobileConfig& config);

  bool Run(const std::vector<PaddleTensor>& inputs,
           std::vector<PaddleTensor>* output_data,
           int batch_size = -1) override;
#ifdef PADDLE_MOBILE_FPGA
  void FeedData(const std::vector<void*>& inputs) override;
  void GetResults(std::vector<void*>* outputs) override;
  void Predict_From_To(int start, int end) override;
  void FeedPaddleTensors(const std::vector<PaddleTensor>& inputs) override;
  void FetchPaddleTensors(std::vector<PaddleTensor>* outputs) override;
#endif

  ~PaddleMobilePredictor() override;

 private:
  std::unique_ptr<PaddleMobile<Device, T>> paddle_mobile_;
  bool Init(const PaddleMobileConfig& config);

  PaddleMobileConfig config_;
};

}  // namespace paddle_mobile