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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_WINDOWHELPERS_H
#define SRC_CORE_HELPERS_WINDOWHELPERS_H
#include "arm_compute/core/IAccessWindow.h"
#include "arm_compute/core/Steps.h"
#include "arm_compute/core/Window.h"
namespace arm_compute
{
/** Update window and padding size for each of the access patterns.
*
* First the window size is reduced based on all access patterns that are not
* allowed to modify the padding of the underlying tensor. Then the padding of
* the remaining tensors is increased to match the window.
*
* @param[in] win Window that is used by the kernel.
* @param[in] patterns Access patterns used to calculate the final window and padding.
*
* @return True if the window has been changed. Changes to the padding do not
* influence the returned value.
*/
template <typename... Ts>
bool update_window_and_padding(Window &win, Ts &&... patterns)
{
bool window_changed = false;
utility::for_each([&](const IAccessWindow & w)
{
window_changed |= w.update_window_if_needed(win);
},
patterns...);
bool padding_changed = false;
utility::for_each([&](IAccessWindow & w)
{
padding_changed |= w.update_padding_if_needed(win);
},
patterns...);
return window_changed;
}
/** Intersect multiple valid regions.
*
* @param[in] regions Valid regions.
*
* @return Intersection of all regions.
*/
template <typename... Ts>
ValidRegion intersect_valid_regions(const Ts &... regions)
{
auto intersect = [](const ValidRegion & r1, const ValidRegion & r2) -> ValidRegion
{
ValidRegion region;
for(size_t d = 0; d < std::min(r1.anchor.num_dimensions(), r2.anchor.num_dimensions()); ++d)
{
region.anchor.set(d, std::max(r1.anchor[d], r2.anchor[d]));
}
for(size_t d = 0; d < std::min(r1.shape.num_dimensions(), r2.shape.num_dimensions()); ++d)
{
region.shape.set(d, std::min(r1.shape[d], r2.shape[d]));
}
return region;
};
return utility::foldl(intersect, regions...);
}
#ifndef DOXYGEN_SKIP_THIS
/** Calculate the maximum window for a given tensor shape and border setting
*
* @param[in] valid_region Valid region object defining the shape of the tensor space for which the window is created.
* @param[in] steps (Optional) Number of elements processed for each step.
* @param[in] skip_border (Optional) If true exclude the border region from the window.
* @param[in] border_size (Optional) Border size.
*
* @return The maximum window the kernel can be executed on.
*/
Window calculate_max_window(const ValidRegion &valid_region, const Steps &steps = Steps(), bool skip_border = false, BorderSize border_size = BorderSize());
/** Calculate the maximum window for a given tensor shape and border setting
*
* @param[in] shape Shape of the tensor space
* @param[in] steps (Optional) Number of elements processed for each step.
* @param[in] skip_border (Optional) If true exclude the border region from the window.
* @param[in] border_size (Optional) Border size.
*
* @return The maximum window the kernel can be executed on.
*/
Window calculate_max_window(const TensorShape &shape, const Steps &steps = Steps(), bool skip_border = false, BorderSize border_size = BorderSize());
/** Calculate the maximum window for a given tensor shape and border setting
*
* @param[in] info Tensor info object defining the shape of the object for which the window is created.
* @param[in] steps (Optional) Number of elements processed for each step.
* @param[in] skip_border (Optional) If true exclude the border region from the window.
* @param[in] border_size (Optional) Border size.
*
* @return The maximum window the kernel can be executed on.
*/
inline Window calculate_max_window(const ITensorInfo &info, const Steps &steps = Steps(), bool skip_border = false, BorderSize border_size = BorderSize())
{
return calculate_max_window(info.tensor_shape(), steps, skip_border, border_size);
}
/** Calculate the maximum window used by a horizontal kernel for a given tensor shape and border setting
*
* @param[in] valid_region Valid region object defining the shape of the tensor space for which the window is created.
* @param[in] steps (Optional) Number of elements processed for each step.
* @param[in] skip_border (Optional) If true exclude the border region from the window.
* @param[in] border_size (Optional) Border size. The border region will be excluded from the window.
*
* @return The maximum window the kernel can be executed on.
*/
Window calculate_max_window_horizontal(const ValidRegion &valid_region, const Steps &steps = Steps(), bool skip_border = false, BorderSize border_size = BorderSize());
/** Calculate the maximum window used by a horizontal kernel for a given tensor shape and border setting
*
* @param[in] info Tensor info object defining the shape of the object for which the window is created.
* @param[in] steps (Optional) Number of elements processed for each step.
* @param[in] skip_border (Optional) If true exclude the border region from the window.
* @param[in] border_size (Optional) Border size.
*
* @return The maximum window the kernel can be executed on.
*/
inline Window calculate_max_window_horizontal(const ITensorInfo &info, const Steps &steps = Steps(), bool skip_border = false, BorderSize border_size = BorderSize())
{
return calculate_max_window_horizontal(info.valid_region(), steps, skip_border, border_size);
}
/** Calculate the maximum window for a given tensor shape and border setting. The window will also includes the border.
*
* @param[in] valid_region Valid region object defining the shape of the tensor space for which the window is created.
* @param[in] steps (Optional) Number of elements processed for each step.
* @param[in] border_size (Optional) Border size. The border region will be included in the window.
*
* @return The maximum window the kernel can be executed on.
*/
Window calculate_max_enlarged_window(const ValidRegion &valid_region, const Steps &steps = Steps(), BorderSize border_size = BorderSize());
/** Calculate the maximum window for a given tensor shape and border setting. The window will also includes the border.
*
* @param[in] info Tensor info object defining the shape of the object for which the window is created.
* @param[in] steps (Optional) Number of elements processed for each step.
* @param[in] border_size (Optional) Border size. The border region will be included in the window.
*
* @return The maximum window the kernel can be executed on.
*/
inline Window calculate_max_enlarged_window(const ITensorInfo &info, const Steps &steps = Steps(), BorderSize border_size = BorderSize())
{
return calculate_max_enlarged_window(info.valid_region(), steps, border_size);
}
/** Function to compute the shape of output and window for the given inputs
*
* @param[in] infos Input tensor informations
*
* @return A pair of the shape and window
*/
template <typename... Shapes>
std::pair<TensorShape, Window> compute_output_shape_and_window(const Shapes &... shapes)
{
const TensorShape out_shape = TensorShape::broadcast_shape(shapes...);
return std::make_pair(out_shape, calculate_max_window(out_shape));
}
#endif /* DOXYGEN_SKIP_THIS */
} // namespace arm_compute
#endif /* SRC_CORE_HELPERS_WINDOWHELPERS_H */
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