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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 "misc/RandomGenerator.h"
namespace nnfw
{
namespace misc
{
template <> uint8_t RandomGenerator::generate<uint8_t>(void)
{
// The value of type_range is 255.
float type_range = static_cast<float>(std::numeric_limits<uint8_t>::max()) -
static_cast<float>(std::numeric_limits<uint8_t>::min());
// Most _dist values range from -5.0 to 5.0.
float min_range = -5.0f;
float max_range = 5.0f;
// NOTE shifted_relative_val has Gaussian distribution that origin mean was 0 and standard
// deviation was 2. And then its values are distributed and shift to that mean is 127.5 and range
// is about [0, 255].
float shifted_relative_val = (_dist(_rand) - min_range) * type_range / (max_range - min_range);
// shifted_relative_val is adjusted to be mapped to end points of the range, if it is out of range
// values.
if (shifted_relative_val < 0.0f)
{
return 0;
}
else if (shifted_relative_val > type_range)
{
return 255;
}
// Convert shifted_relative_val from float to uint8
return static_cast<uint8_t>(shifted_relative_val);
}
template <> bool RandomGenerator::generate<bool>(void)
{
std::uniform_int_distribution<> dist(0, 1); // [0, 1]
return dist(_rand);
}
template <> int32_t RandomGenerator::generate<int32_t>(void)
{
// Instead of INT_MAX, 99 is chosen because int32_t input does not mean
// that the model can have any value in int32_t can hold.
// For example, one_hot operation gets indices as int32_t tensor.
// However, we usually expect it would hold a value in [0..depth).
// In our given model, depth was 10137.
const int int32_random_max = 99;
std::uniform_int_distribution<> dist(0, int32_random_max);
return dist(_rand);
}
template <> int64_t RandomGenerator::generate<int64_t>(void)
{
// Instead of INT_MAX, 99 is chosen because int64_t input does not mean
// that the model can have any value in int64_t can hold.
// For example, one_hot operation gets indices as int64_t tensor.
// However, we usually expect it would hold a value in [0..depth).
// In our given model, depth was 10137.
const int64_t int64_random_max = 99;
std::uniform_int_distribution<> dist(0, int64_random_max);
return dist(_rand);
}
} // namespace misc
} // namespace nnfw
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