//   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.

#include "gaussian_sampling.h"

namespace DeepES{

bool GaussianSampling::load_config(const DeepESConfig& config) {
  bool success = true;
  _std = config.gaussian_sampling().std();
  success = set_seed(config.seed());
  return success;
}

bool GaussianSampling::sampling(int* key, float* noise, int64_t size) {
  bool success = true;
  if (noise == nullptr) {
    LOG(ERROR) << "[DeepES] Input noise array cannot be nullptr.";
    success = false;
    return success;
  }
  int rand_key = rand();
  *key = rand_key;
  std::default_random_engine generator(rand_key);
  std::normal_distribution<float> norm;
  for (int64_t i = 0; i < size; ++i) {
    *(noise + i) = norm(generator) * _std;
  }
  return success;
}

bool GaussianSampling::resampling(int key, float* noise, int64_t size) {
  bool success = true;
  if (noise == nullptr) {
    LOG(ERROR) << "[DeepES] Input noise array cannot be nullptr.";
    success = false;
  } else {
    std::default_random_engine generator(key);
    std::normal_distribution<float> norm;
    for (int64_t i = 0; i < size; ++i) {
      *(noise + i) = norm(generator) * _std;
    }
  }
  return success;
}

}