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/*
* Copyright (c) 2020 Samsung Electronics Co., Ltd. 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 "souschef/Data/Gaussian.h"
#include "souschef/LexicalCast.h"
#include <random>
#include <chrono>
#include <cassert>
#include <stdexcept>
namespace souschef
{
template <typename T>
static std::vector<uint8_t> generate_gaussian(int32_t count, float mean, float stddev,
std::minstd_rand::result_type seed)
{
std::minstd_rand rand{static_cast<std::minstd_rand::result_type>(seed)};
std::normal_distribution<float> dist{mean, stddev};
std::vector<uint8_t> res;
constexpr float max_cap = std::numeric_limits<T>::max();
constexpr float min_cap = std::numeric_limits<T>::min();
for (uint32_t n = 0; n < count; ++n)
{
float raw_value = dist(rand);
const float capped_value = std::max(min_cap, std::min(max_cap, raw_value));
auto const value = static_cast<T>(capped_value);
auto const arr = reinterpret_cast<const uint8_t *>(&value);
for (uint32_t b = 0; b < sizeof(T); ++b)
{
res.emplace_back(arr[b]);
}
}
return res;
}
template <typename T>
static std::vector<uint8_t> generate_gaussian(int32_t count, float mean, float stddev)
{
auto time_stamp = std::chrono::system_clock::now().time_since_epoch().count();
// Note this is implementation defined, change if needed.
auto seed = static_cast<std::minstd_rand::result_type>(time_stamp);
return generate_gaussian<T>(count, mean, stddev, seed);
}
std::vector<uint8_t> GaussianFloat32DataChef::generate(int32_t count) const
{
return generate_gaussian<float>(count, _mean, _stddev);
}
std::vector<uint8_t> GaussianInt32DataChef::generate(int32_t count) const
{
return generate_gaussian<int32_t>(count, _mean, _stddev);
}
std::vector<uint8_t> GaussianInt16DataChef::generate(int32_t count) const
{
return generate_gaussian<int16_t>(count, _mean, _stddev);
}
std::vector<uint8_t> GaussianUint8DataChef::generate(int32_t count) const
{
return generate_gaussian<uint8_t>(count, _mean, _stddev);
}
std::unique_ptr<DataChef> GaussianFloat32DataChefFactory::create(const Arguments &args) const
{
if (args.count() != 2)
{
throw std::runtime_error{"invalid argument count: two arguments (mean/stddev) are expected"};
}
auto const mean = to_number<float>(args.value(0));
auto const stddev = to_number<float>(args.value(1));
return std::unique_ptr<DataChef>{new GaussianFloat32DataChef{mean, stddev}};
}
std::unique_ptr<DataChef> GaussianInt32DataChefFactory::create(const Arguments &args) const
{
if (args.count() != 2)
{
throw std::runtime_error{"invalid argument count: two arguments (mean/stddev) are expected"};
}
auto const mean = to_number<float>(args.value(0));
auto const stddev = to_number<float>(args.value(1));
return std::unique_ptr<DataChef>{new GaussianInt32DataChef{mean, stddev}};
}
std::unique_ptr<DataChef> GaussianInt16DataChefFactory::create(const Arguments &args) const
{
if (args.count() != 2)
{
throw std::runtime_error{"invalid argument count: two arguments (mean/stddev) are expected"};
}
auto const mean = to_number<float>(args.value(0));
auto const stddev = to_number<float>(args.value(1));
return std::unique_ptr<DataChef>{new GaussianInt16DataChef{mean, stddev}};
}
std::unique_ptr<DataChef> GaussianUint8DataChefFactory::create(const Arguments &args) const
{
if (args.count() != 2)
{
throw std::runtime_error{"invalid argument count: two arguments (mean/stddev) are expected"};
}
auto const mean = to_number<float>(args.value(0));
auto const stddev = to_number<float>(args.value(1));
return std::unique_ptr<DataChef>{new GaussianUint8DataChef{mean, stddev}};
}
} // namespace souschef
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