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/*
* Copyright (c) 2016-2020 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 ARM_COMPUTE_WINDOW_H
#define ARM_COMPUTE_WINDOW_H
#include <algorithm>
#include <array>
#include <cstddef>
#include "arm_compute/core/Coordinates.h"
#include "arm_compute/core/Error.h"
#include "arm_compute/core/ITensorInfo.h"
#include "arm_compute/core/Utils.h"
namespace arm_compute
{
/** Describe a multidimensional execution window. */
class Window
{
public:
/** Alias for dimension 0 also known as X dimension */
static constexpr size_t DimX = 0;
/** Alias for dimension 1 also known as Y dimension */
static constexpr size_t DimY = 1;
/** Alias for dimension 2 also known as Z dimension */
static constexpr size_t DimZ = 2;
/** Alias for dimension 3 also known as W dimension */
static constexpr size_t DimW = 3;
/** Default constructor: create a window containing a single element. */
constexpr Window()
: _dims(), _is_broadcasted(utility::generate_array<bool, Coordinates::num_max_dimensions, false>::value)
{
}
/** Copy constructor
*
* @param[in] src Copy the values from src to a new object
*/
Window(const Window &src);
/** Copy assignment operator
*
* @param[in] rhs Copy the values from rhs to the current object
*
* @return Reference to the updated object
*/
Window &operator=(const Window &rhs);
/** Describe one of the image's dimensions with a start, end and step.
*
* Iteration through the elements of the dimension is done like this:
* for(int v = start(); v < end(); v += step())
* {
* ...
* }
*/
class Dimension
{
public:
/** Constructor, by default creates a dimension of 1.
*
* @param[in] start Start of the dimension
* @param[in] end End of the dimension
* @param[in] step Step between two elements of the dimension when iterating.
*
*/
constexpr Dimension(int start = 0, int end = 1, int step = 1)
: _start(start), _end(end), _step(step)
{
}
/** Default assignment operator to allow dimensions to be copied */
Dimension &operator=(const Dimension &d) = default;
/** Return the start of the dimension */
constexpr int start() const
{
return _start;
}
/** Return the end of the dimension */
constexpr int end() const
{
return _end;
}
/** Return the step of the dimension */
constexpr int step() const
{
return _step;
}
/** Set the dimension's step
*
* @param[in] step The new step
*/
void set_step(int step)
{
_step = step;
}
/** Set the dimension's end
*
* @param[in] end The new end
*/
void set_end(int end)
{
_end = end;
}
private:
int _start; /**< Start of the dimension */
int _end; /**< End of the dimension */
int _step;
};
/** Read only access to a given dimension of the window
*
* @note Precondition: dimension < Coordinates::num_max_dimensions
*
* @param[in] dimension The dimension to access
*
* @return The requested dimension
*/
constexpr const Dimension &operator[](size_t dimension) const;
/** Alias to access the first dimension of the window
*
* @return First dimension of the window
*/
constexpr const Dimension &x() const
{
return _dims.at(Window::DimX);
}
/** Alias to access the second dimension of the window
*
* @return Second dimension of the window
*/
constexpr const Dimension &y() const
{
return _dims.at(Window::DimY);
}
/** Alias to access the third dimension of the window
*
* @return Third dimension of the window
*/
constexpr const Dimension &z() const
{
return _dims.at(Window::DimZ);
}
/** Set the values of a given dimension
*
* @param[in] dimension The dimension to set
* @param[in] dim The values to set the dimension to
*/
void set(size_t dimension, const Dimension &dim);
/** Set the dimension as broadcasted dimension
*
* @param[in] dimension The dimension to set
*/
void set_broadcasted(size_t dimension);
/** Return whether a dimension has been broadcasted
*
* @param[in] dimension The requested dimension
*
* @return true if the dimension has been broadcasted
*/
bool is_broadcasted(size_t dimension) const;
/** Use the tensor's dimensions to fill the window dimensions.
*
* @param[in] shape @ref TensorShape to copy the dimensions from.
* @param[in] first_dimension Only copy dimensions which are greater or equal to this value.
*/
void use_tensor_dimensions(const TensorShape &shape, size_t first_dimension = Window::DimX);
/** Shift the values of a given dimension by the given shift_value
*
* @param[in] dimension The dimension to shift
* @param[in] shift_value Value to shift the start and end values of.
*/
void shift(size_t dimension, int shift_value);
/** Shift down all the dimensions of a window
*
* i.e new_dims[n] = old_dims[n+shift_value].
*
* @param[in] shift_value Number of dimensions to shift the window by.
*
* @return The window with the shifted dimensions.
*/
Window shift_dimensions(unsigned int shift_value) const;
/** Adjust the start or end of a given dimension by the given value
*
* @param[in] dimension The dimension to adjust
* @param[in] adjust_value The adjusted value.
* @param[in] is_at_start The flag to indicate whether adjust the start or end of the dimension.
*/
void adjust(size_t dimension, int adjust_value, bool is_at_start);
/** Scale the values of a given dimension by the given scale_value
*
* @note The end of the window is rounded up to be a multiple of step after the scaling.
*
* @param[in] dimension The dimension to scale
* @param[in] scale_value Value to scale the start, end and step values of.
*/
void scale(size_t dimension, float scale_value);
/** Set the step of a given dimension.
*
* @param[in] dimension Dimension to update
* @param[in] step The new dimension's step value
*/
void set_dimension_step(size_t dimension, int step);
/** Will validate all the window's dimensions' values when asserts are enabled
*
* No-op when asserts are disabled
*/
void validate() const;
/** Return the number of iterations needed to iterate through a given dimension
*
* @param[in] dimension The requested dimension
*
* @return The number of iterations
*/
constexpr size_t num_iterations(size_t dimension) const;
/** Return the total number of iterations needed to iterate through the entire window
*
* @return Number of total iterations
*/
size_t num_iterations_total() const;
/** Return the shape of the window in number of steps */
TensorShape shape() const;
/** Split a window into a set of sub windows along a given dimension
*
* For example to split a window into 3 sub-windows along the Y axis, you would have to do:<br/>
* Window sub0 = window.split_window( 1, 0, 3);<br/>
* Window sub1 = window.split_window( 1, 1, 3);<br/>
* Window sub2 = window.split_window( 1, 2, 3);<br/>
*
* @param[in] dimension Dimension along which the split will be performed
* @param[in] id Id of the sub-window to return. Must be in the range (0, total-1)
* @param[in] total Total number of sub-windows the window will be split into.
*
* @return The subwindow "id" out of "total"
*/
Window split_window(size_t dimension, size_t id, size_t total) const;
/** First 1D slice of the window
*
* @return The first slice of the window.
*/
Window first_slice_window_1D() const
{
return first_slice_window<1>();
};
/** First 2D slice of the window
*
* @return The first slice of the window.
*/
Window first_slice_window_2D() const
{
return first_slice_window<2>();
};
/** First 3D slice of the window
*
* @return The first slice of the window.
*/
Window first_slice_window_3D() const
{
return first_slice_window<3>();
};
/** First 4D slice of the window
*
* @return The first slice of the window.
*/
Window first_slice_window_4D() const
{
return first_slice_window<4>();
};
/** Slide the passed 1D window slice.
*
* If slice contains the last slice then it will remain unchanged and false will be returned.
*
* @param[in,out] slice Current slice, to be updated to the next slice.
*
* @return true if slice contains a new slice, false if slice already contained the last slice
*/
bool slide_window_slice_1D(Window &slice) const
{
return slide_window_slice<1>(slice);
}
/** Slide the passed 2D window slice.
*
* If slice contains the last slice then it will remain unchanged and false will be returned.
*
* @param[in,out] slice Current slice, to be updated to the next slice.
*
* @return true if slice contains a new slice, false if slice already contained the last slice
*/
bool slide_window_slice_2D(Window &slice) const
{
return slide_window_slice<2>(slice);
}
/** Slide the passed 3D window slice.
*
* If slice contains the last slice then it will remain unchanged and false will be returned.
*
* @param[in,out] slice Current slice, to be updated to the next slice.
*
* @return true if slice contains a new slice, false if slice already contained the last slice
*/
bool slide_window_slice_3D(Window &slice) const
{
return slide_window_slice<3>(slice);
}
/** Slide the passed 4D window slice.
*
* If slice contains the last slice then it will remain unchanged and false will be returned.
*
* @param[in,out] slice Current slice, to be updated to the next slice.
*
* @return true if slice contains a new slice, false if slice already contained the last slice
*/
bool slide_window_slice_4D(Window &slice) const
{
return slide_window_slice<4>(slice);
}
/** Collapse the dimensions between @p first and @p last if possible.
*
* A dimension is collapsable if it starts from 0 and matches the corresponding dimension in the full_window
*
* @param[in] full_window Full window @p window has been created from.
* @param[in] first Start dimension into which the following are collapsed.
* @param[in] last End (exclusive) dimension to collapse.
* @param[out] has_collapsed (Optional) Whether the window was collapsed.
*
* @return Collapsed window.
*/
Window collapse_if_possible(const Window &full_window, size_t first, size_t last, bool *has_collapsed = nullptr) const;
/** Collapse the dimensions higher than @p first if possible.
*
* A dimension is collapsable if it starts from 0 and matches the corresponding dimension in the full_window
*
* @param[in] full_window Full window @p window has been created from.
* @param[in] first Start dimension into which the following are collapsed.
* @param[out] has_collapsed (Optional) Whether the window was collapsed.
*
* @return Collapsed window.
*/
Window collapse_if_possible(const Window &full_window, size_t first, bool *has_collapsed = nullptr) const
{
return collapse_if_possible(full_window, first, Coordinates::num_max_dimensions, has_collapsed);
}
/** Collapse the dimensions between @p first and @p last.
*
* A dimension is collapsable if it starts from 0 and matches the corresponding dimension in the full_window
*
* @param[in] full_window Full window @p window has been created from.
* @param[in] first Start dimension into which the following are collapsed.
* @param[in] last End (exclusive) dimension to collapse.
*
* @return Collapsed window if successful.
*/
Window collapse(const Window &full_window, size_t first, size_t last = Coordinates::num_max_dimensions) const;
/** Don't advance in the dimension where @p shape is less equal to 1.
*
* @param[in] shape A TensorShape.
*
* @return Broadcast window.
*/
Window broadcast_if_dimension_le_one(const TensorShape &shape) const;
/** Don't advance in the dimension where shape of @p info is less equal to 1.
*
* @param[in] info An ITensorInfo.
*
* @return Broadcast window.
*/
Window broadcast_if_dimension_le_one(const ITensorInfo &info) const
{
return broadcast_if_dimension_le_one(info.tensor_shape());
}
/** Friend function that swaps the contents of two windows
*
* @param[in] lhs First window to swap.
* @param[in] rhs Second window to swap.
*/
friend void swap(Window &lhs, Window &rhs);
private:
/** First slice of the window
*
* @return The first slice of the window.
*/
template <unsigned int window_dimension>
Window first_slice_window() const;
/** Slide the passed window slice.
*
* If slice contains the last slice then it will remain unchanged and false will be returned.
*
* @param[in,out] slice Current slice, to be updated to the next slice.
*
* @return true if slice contains a new slice, false if slice already contained the last slice
*/
template <unsigned int window_dimension>
bool slide_window_slice(Window &slice) const;
private:
std::array<Dimension, Coordinates::num_max_dimensions> _dims;
std::array<bool, Coordinates::num_max_dimensions> _is_broadcasted;
};
} // namespace arm_compute
#include "Window.inl"
#endif /*ARM_COMPUTE_WINDOW_H */