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/*
* Copyright (c) 2017-2020 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.
*/
#include "arm_compute/core/GLES_COMPUTE/kernels/GCGEMMMatrixAccumulateBiasesKernel.h"
#include "arm_compute/core/AccessWindowStatic.h"
#include "arm_compute/core/Error.h"
#include "arm_compute/core/GLES_COMPUTE/GCHelpers.h"
#include "arm_compute/core/GLES_COMPUTE/GCKernelLibrary.h"
#include "arm_compute/core/GLES_COMPUTE/IGCTensor.h"
#include "arm_compute/core/GLES_COMPUTE/OpenGLES.h"
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/Types.h"
#include "arm_compute/core/Utils.h"
#include "arm_compute/core/Validate.h"
#include "support/StringSupport.h"
using namespace arm_compute;
GCGEMMMatrixAccumulateBiasesKernel::GCGEMMMatrixAccumulateBiasesKernel()
: _accum(nullptr), _biases(nullptr), _lws(gles::NDRange(1U, 1U, 1U))
{
}
void GCGEMMMatrixAccumulateBiasesKernel::configure(IGCTensor *accum, const IGCTensor *biases)
{
ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(accum, 1, DataType::F16, DataType::F32);
ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(biases, accum);
ARM_COMPUTE_ERROR_ON(biases->info()->num_dimensions() != 1);
_biases = biases;
_accum = accum;
std::set<std::string> build_opts;
build_opts.emplace("#define LOCAL_SIZE_X " + support::cpp11::to_string(_lws[0]));
build_opts.emplace("#define LOCAL_SIZE_Y " + support::cpp11::to_string(_lws[1]));
build_opts.emplace("#define LOCAL_SIZE_Z " + support::cpp11::to_string(_lws[2]));
// Create kernel
build_opts.emplace("#define GEMM_ACCUMULATE_BIASES");
#define ACCUM_PROCESS_4X
#if defined(ACCUM_PROCESS_4X)
build_opts.emplace("#define ACCUM_PROCESS_4X");
#elif defined(ACCUM_PROCESS_8X) /* ACCUM_PROCESS_4X */
build_opts.emplace("#define ACCUM_PROCESS_8X");
#endif /* ACCUM_PROCESS_4X */
std::string dt_name = (accum->info()->data_type() == DataType::F32) ? "DATA_TYPE_FP32" : "DATA_TYPE_FP16";
build_opts.emplace(("#define " + dt_name));
_kernel = GCKernelLibrary::get().create_kernel("gemm_accumulate_biases", build_opts);
// Configure kernel window
unsigned int num_elems_processed_per_iteration = 1;
if(_accum->info()->data_type() == DataType::F32)
{
num_elems_processed_per_iteration = 16;
}
else if(_accum->info()->data_type() == DataType::F16)
{
#if defined(ACCUM_PROCESS_4X)
num_elems_processed_per_iteration = 4;
#elif defined(ACCUM_PROCESS_8X) /* ACCUM_PROCESS_4X */
num_elems_processed_per_iteration = 8;
#endif /* ACCUM_PROCESS_4X */
}
const int accum_width = accum->info()->dimension(0);
const int accum_padding_right = ceil_to_multiple(accum_width, num_elems_processed_per_iteration * _lws[0]) - accum_width;
BorderSize border = BorderSize(0, accum_padding_right, 0, 0);
Window win = calculate_max_enlarged_window(*_accum->info(), Steps(num_elems_processed_per_iteration), border);
AccessWindowStatic biases_access(biases->info(), 0, 0, ceil_to_multiple(biases->info()->dimension(0), num_elems_processed_per_iteration * _lws[0]), biases->info()->dimension(1));
AccessWindowStatic accum_access(_accum->info(), 0, 0, accum_width + accum_padding_right, _accum->info()->dimension(1));
update_window_and_padding(win, biases_access, accum_access);
IGCKernel::configure(win);
}
void GCGEMMMatrixAccumulateBiasesKernel::run(const Window &window)
{
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
ARM_COMPUTE_ERROR_ON_MISMATCHING_WINDOWS(IGCKernel::window(), window);
_kernel.use();
Window accum_slice = window.first_slice_window_2D();
Window biases_slice(accum_slice);
biases_slice.set(Window::DimY, Window::Dimension(0, 1, 1));
// Run kernel
do
{
// Set arguments
unsigned int idx = 0;
add_2D_tensor_argument(idx, _accum, 1, accum_slice);
add_1D_tensor_argument(idx, _biases, 2, biases_slice);
_kernel.update_shader_params();
enqueue(*this, accum_slice, _lws);
}
while(window.slide_window_slice_2D(accum_slice));
}
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