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/*
* Copyright (c) 2017 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.
*/
#include "arm_compute/core/CL/kernels/CLGEMMLowpReductionKernel.h"
#include "arm_compute/core/AccessWindowStatic.h"
#include "arm_compute/core/CL/ICLTensor.h"
#include "arm_compute/core/Error.h"
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/TensorInfo.h"
#include "arm_compute/core/Types.h"
#include "arm_compute/core/Utils.h"
#include "arm_compute/core/Validate.h"
#include "arm_compute/core/Window.h"
#include "support/ToolchainSupport.h"
#include <cstddef>
#include <cstdint>
using namespace arm_compute;
namespace arm_compute
{
class Coordinates;
} // namespace arm_compute
ICLGEMMLowpReductionKernel::ICLGEMMLowpReductionKernel()
: _input(), _output()
{
}
void CLGEMMLowpMatrixAReductionKernel::configure(const ICLTensor *mtx_a, ICLTensor *vector_sum_row)
{
ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(mtx_a, 1, DataType::QASYMM8);
ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(vector_sum_row, 1, DataType::S32);
_input = mtx_a;
_output = vector_sum_row;
// Set the arguments to pass at compile time
CLBuildOptions build_opts;
build_opts.add_option("-DCOLS_A=" + support::cpp11::to_string(mtx_a->info()->dimension(0)));
// Create kernel
_kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("gemmlowp_matrix_a_reduction", build_opts.options()));
const unsigned int num_elems_processed_per_iteration = 1;
// Configure kernel window
Window win = calculate_max_window(*_output->info(), Steps(num_elems_processed_per_iteration));
AccessWindowStatic input_access(_input->info(), 0, 0, ceil_to_multiple(_input->info()->dimension(0), 16), _input->info()->dimension(1));
AccessWindowHorizontal output_access(_output->info(), 0, num_elems_processed_per_iteration);
update_window_and_padding(win,
input_access,
output_access);
output_access.set_valid_region(win, ValidRegion(Coordinates(0, 0), _output->info()->tensor_shape()));
ICLKernel::configure(win);
}
void CLGEMMLowpMatrixAReductionKernel::run(const Window &window, cl::CommandQueue &queue)
{
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window);
Window collapsed = window.collapse_if_possible(ICLKernel::window(), Window::DimY);
Window slice_in = collapsed.first_slice_window_2D();
Window slice_out = collapsed.first_slice_window_2D();
// Setup input slice. Its dimensions are increased in the cl kernel.
slice_in.set(Window::DimX, Window::Dimension(0, 0, 0));
slice_in.set(Window::DimY, Window::Dimension(0, 0, 0));
slice_in.set(Window::DimZ, Window::Dimension(0, 0, 0));
do
{
unsigned int idx = 0;
add_3D_tensor_argument(idx, _input, slice_in);
add_2D_tensor_argument(idx, _output, slice_out);
enqueue(queue, *this, slice_out);
}
while(collapsed.slide_window_slice_2D(slice_out));
}
void CLGEMMLowpMatrixBReductionKernel::configure(const ICLTensor *mtx_b, ICLTensor *vector_sum_col)
{
ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(mtx_b, 1, DataType::QASYMM8);
ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(vector_sum_col, 1, DataType::S32);
_input = mtx_b;
_output = vector_sum_col;
// Set the arguments to pass at compile time
CLBuildOptions build_opts;
build_opts.add_option("-DCOLS_B=" + support::cpp11::to_string(mtx_b->info()->dimension(0)));
build_opts.add_option("-DROWS_B=" + support::cpp11::to_string(mtx_b->info()->dimension(1)));
// Create kernel
_kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("gemmlowp_matrix_b_reduction", build_opts.options()));
constexpr unsigned int num_elems_processed_per_iteration = 16;
// Configure kernel window
Window win = calculate_max_window(*vector_sum_col->info(), Steps(num_elems_processed_per_iteration));
AccessWindowStatic input_access(_input->info(), 0, 0, ceil_to_multiple(_input->info()->dimension(0), 16), _input->info()->dimension(1));
AccessWindowHorizontal output_access(_output->info(), 0, num_elems_processed_per_iteration);
update_window_and_padding(win,
input_access,
output_access);
output_access.set_valid_region(win, ValidRegion(Coordinates(0, 0), _output->info()->tensor_shape()));
ICLKernel::configure(win);
}
void CLGEMMLowpMatrixBReductionKernel::run(const Window &window, cl::CommandQueue &queue)
{
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window);
Window collapsed = window.collapse_if_possible(IKernel::window(), Window::DimY);
Window slice_out = collapsed.first_slice_window_2D();
Window slice_in = slice_out;
slice_in.set(Window::DimY, Window::Dimension(0, 1, 1));
slice_in.set(Window::DimZ, Window::Dimension(0, 1, 1));
do
{
unsigned int idx = 0;
add_3D_tensor_argument(idx, _input, slice_in);
add_2D_tensor_argument(idx, _output, slice_out);
enqueue(queue, *this, slice_out);
}
while(collapsed.slide_window_slice_2D(slice_out));
}