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/*
* Copyright (c) 2020 Samsung Electronics Co., Ltd. All Rights Reserved
* Copyright 2018 The TensorFlow 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.
*/
#ifndef __NNFW_CKER_RANGE_H__
#define __NNFW_CKER_RANGE_H__
#include "cker/Shape.h"
#include <cmath>
#include <stdexcept>
namespace nnfw
{
namespace cker
{
template <typename T> inline int GetSize(T start, T limit, T delta)
{
if (!((start > limit && delta < 0) || (start < limit && delta > 0)))
{
throw std::runtime_error("Range: invalid input values");
}
int size = (std::is_integral<T>::value
? ((std::abs(limit - start) + std::abs(delta) - 1) / std::abs(delta))
: std::ceil(std::abs((limit - start) / delta)));
return size;
}
template <typename T>
inline void Range(const T *start_data, const T *limit_data, const T *delta_data, T *output_data)
{
const T start_value = *start_data;
const T delta_value = *delta_data;
const T limit_value = *limit_data;
const int num_elements = GetSize<T>(start_value, limit_value, delta_value);
T value = start_value;
for (int i = 0; i < num_elements; ++i)
{
output_data[i] = value;
value += delta_value;
}
}
} // namespace cker
} // namespace nnfw
#endif // __NNFW_CKER_RANGE_H__
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