// Copyright (c) 2020 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>
#ifdef BCLOUD
#ifdef WITH_GPU
#include "paddle/paddle_inference_api.h"
#else
#include "paddle/fluid/inference/api/paddle_inference_api.h"
#endif
#else
#include "paddle_inference_api.h"  // NOLINT
#endif
#include <string>

namespace baidu {
namespace paddle_serving {
namespace serving {

static const char* GENERAL_MODEL_NAME = "general_model";

struct GeneralBlob {
  std::vector<paddle::PaddleTensor> tensor_vector;
  double infer_time;
  std::vector<std::string> fetch_name_vector;

  int _batch_size;

  void Clear() {
    size_t tensor_count = tensor_vector.size();
    for (size_t ti = 0; ti < tensor_count; ++ti) {
      tensor_vector[ti].shape.clear();
    }
    tensor_vector.clear();
  }

  int SetBatchSize(int batch_size) { _batch_size = batch_size; }

  int GetBatchSize() const { return _batch_size; }
  /*
  int GetBatchSize() const {
    if (tensor_vector.size() > 0) {
      if (tensor_vector[0].lod.size() == 1) {
        return tensor_vector[0].lod[0].size() - 1;
      } else {
        return tensor_vector[0].shape[0];
      }
    } else {
      return -1;
    }
  }
  */
  std::string ShortDebugString() const { return "Not implemented!"; }
};

}  // namespace serving
}  // namespace paddle_serving
}  // namespace baidu