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/*
* Copyright (c) 2020-2021 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to
* deal in the Software without restriction, including without limitation the
* rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
* sell copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#ifndef SRC_CORE_HELPERS_UTILS_H
#define SRC_CORE_HELPERS_UTILS_H
#include "arm_compute/core/ITensorInfo.h"
namespace arm_compute
{
/** Create a strides object based on the provided strides and the tensor dimensions.
*
* @param[in] info Tensor info object providing the shape of the tensor for unspecified strides.
* @param[in] stride_x Stride to be used in X dimension (in bytes).
* @param[in] fixed_strides Strides to be used in higher dimensions starting at Y (in bytes).
*
* @return Strides object based on the specified strides. Missing strides are
* calculated based on the tensor shape and the strides of lower dimensions.
*/
template <typename T, typename... Ts>
inline Strides compute_strides(const ITensorInfo &info, T stride_x, Ts &&... fixed_strides)
{
const TensorShape &shape = info.tensor_shape();
// Create strides object
Strides strides(stride_x, fixed_strides...);
for(size_t i = 1 + sizeof...(Ts); i < info.num_dimensions(); ++i)
{
strides.set(i, shape[i - 1] * strides[i - 1]);
}
size_t first_zero = std::distance(strides.begin(), std::find_if(strides.begin(), strides.end(), [](uint32_t val)
{
return val == 0U;
}));
if(first_zero > 0)
{
if(first_zero == 1)
{
strides.set(1, strides[0] * (shape[0] + info.padding().left + info.padding().right));
++first_zero;
}
else if(first_zero == 2)
{
strides.set(2, strides[1] * (shape[1] + info.padding().top + info.padding().bottom));
++first_zero;
}
for(size_t i = first_zero; i < Strides::num_max_dimensions; ++i)
{
strides.set(i, strides[first_zero - 1]);
}
}
return strides;
}
/** Create a strides object based on the tensor dimensions.
*
* @param[in] info Tensor info object used to compute the strides.
*
* @return Strides object based on element size and tensor shape.
*/
template <typename... Ts>
inline Strides compute_strides(const ITensorInfo &info)
{
return compute_strides(info, info.element_size());
}
/** Given an integer value, this function returns the next power of two
*
* @param[in] x Input value
*
* @return the next power of two
*/
inline unsigned int get_next_power_two(unsigned int x)
{
// Decrement by 1
x--;
// Shift right by 1
x |= x >> 1u;
// Shift right by 2
x |= x >> 2u;
// Shift right by 4
x |= x >> 4u;
// Shift right by 8
x |= x >> 8u;
// Shift right by 16
x |= x >> 16u;
// Increment by 1
x++;
return x;
}
} // namespace arm_compute
#endif /* SRC_CORE_HELPERS_UTILS_H */
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