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/*
* Copyright (c) 2018 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 "Gaussian.h"
#include "LexicalCast.h"
#include <random>
#include <chrono>
#include <cassert>
#include <stdexcept>
std::vector<uint8_t> GaussianFloat32DataChef::generate(int32_t count) const
{
// TODO Support seed value override
int seed = std::chrono::system_clock::now().time_since_epoch().count();
std::minstd_rand rand{seed};
std::normal_distribution<float> dist{_mean, _stddev};
std::vector<uint8_t> res;
for (uint32_t n = 0; n < count; ++n)
{
auto const value = dist(rand);
auto const arr = reinterpret_cast<const uint8_t *>(&value);
for (uint32_t b = 0; b < sizeof(float); ++b)
{
res.emplace_back(arr[b]);
}
}
return res;
}
std::vector<uint8_t> GaussianInt32DataChef::generate(int32_t count) const
{
// TODO Support seed value override
int seed = std::chrono::system_clock::now().time_since_epoch().count();
std::minstd_rand rand{seed};
std::normal_distribution<float> dist{_mean, _stddev};
std::vector<uint8_t> res;
for (uint32_t n = 0; n < count; ++n)
{
auto const value = static_cast<int32_t>(dist(rand));
auto const arr = reinterpret_cast<const uint8_t *>(&value);
for (uint32_t b = 0; b < sizeof(int32_t); ++b)
{
res.emplace_back(arr[b]);
}
}
return res;
}
std::vector<uint8_t> GaussianUint8DataChef::generate(int32_t count) const
{
// TODO Support seed value override
int seed = std::chrono::system_clock::now().time_since_epoch().count();
std::minstd_rand rand{seed};
std::normal_distribution<float> dist{_mean, _stddev};
std::vector<uint8_t> res;
for (uint32_t n = 0; n < count; ++n)
{
auto const value = static_cast<uint8_t>(dist(rand)); // uint8_t for data type
auto const arr = reinterpret_cast<const uint8_t *>(&value); // uint8_t for byte streaming
for (uint32_t b = 0; b < sizeof(uint8_t); ++b)
{
res.emplace_back(arr[b]);
}
}
return res;
}
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> 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}};
}
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