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/*
* Copyright (c) 2018-2020 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/CL/kernels/CLTileKernel.h"
#include "arm_compute/core/CL/ICLTensor.h"
#include "arm_compute/core/Error.h"
#include "arm_compute/core/utils/misc/ShapeCalculator.h"
#include "support/StringSupport.h"
namespace arm_compute
{
namespace
{
Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, const Multiples &multiples)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
ARM_COMPUTE_RETURN_ERROR_ON(input->data_type() == DataType::UNKNOWN);
ARM_COMPUTE_RETURN_ERROR_ON(multiples.size() > 4);
ARM_COMPUTE_RETURN_ERROR_ON(multiples.empty());
ARM_COMPUTE_RETURN_ERROR_ON(std::any_of(multiples.begin(), multiples.end(), [](uint32_t e)
{
return e == 0;
}));
// Validate output if initialized
if(output->total_size() != 0)
{
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(misc::shape_calculator::compute_tiled_shape(input->tensor_shape(), multiples), output->tensor_shape());
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
}
return Status{};
}
} // namespace
CLTileKernel::CLTileKernel()
: _input(nullptr), _output(nullptr)
{
}
void CLTileKernel::configure(const ICLTensor *input, ICLTensor *output, const Multiples &multiples)
{
configure(CLKernelLibrary::get().get_compile_context(), input, output, multiples);
}
void CLTileKernel::configure(const CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const Multiples &multiples)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
// Auto initialize output
TensorShape tiled_shape = misc::shape_calculator::compute_tiled_shape(input->info()->tensor_shape(), multiples);
auto_init_if_empty(*output->info(), tiled_shape, 1, input->info()->data_type());
// Validate
ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), multiples));
_input = input;
_output = output;
const DataType data_type = input->info()->data_type();
const int vec_size_x = 16 / input->info()->element_size();
const int input_width_x = input->info()->tensor_shape().x();
const unsigned int offset = ceil_to_multiple(input_width_x, vec_size_x) - input_width_x;
const bool multi_access_x = (input_width_x / vec_size_x > 0);
// Create kernel
CLBuildOptions build_opts;
build_opts.add_option("-DDATA_TYPE=" + get_cl_unsigned_type_from_element_size(data_size_from_type(data_type)));
build_opts.add_option("-DSRC_WIDTH=" + support::cpp11::to_string(input_width_x));
build_opts.add_option("-DSRC_HEIGHT=" + support::cpp11::to_string(input->info()->dimension(1)));
build_opts.add_option("-DSRC_DEPTH=" + support::cpp11::to_string(input->info()->dimension(2)));
build_opts.add_option("-DSRC_BATCHES=" + support::cpp11::to_string(input->info()->dimension(3)));
build_opts.add_option("-DDST_DEPTH=" + support::cpp11::to_string(output->info()->dimension(2)));
build_opts.add_option_if(multi_access_x, "-DOFFSET=" + support::cpp11::to_string(offset));
build_opts.add_option_if(multi_access_x, "-DVEC_SIZE=" + support::cpp11::to_string(vec_size_x));
_kernel = create_kernel(compile_context, "tile", build_opts.options());
// Configure window without padding
Window win = calculate_max_window(*output->info());
if(multi_access_x)
{
// If multi-access is enabled, no thread should cross the tile boundaries. This means we need
// as many threads as those to cover a single tile times multiples[0]. Note that if threads
// do not cross the boundaries of the tiles, they won't cross the boundaries of the last tile, and
// we don't need to pad the output
const unsigned int size_win_x = ceil_to_multiple(input->info()->dimension(0), vec_size_x) * multiples[0];
win.set(Window::DimX,
Window::Dimension(win.x().start(), size_win_x, vec_size_x));
}
ICLKernel::configure_internal(win);
// Set config_id for enabling LWS tuning
_config_id = "tile";
_config_id += "_";
_config_id += lower_string(string_from_data_type(input->info()->data_type()));
for(unsigned int i = 0; i < multiples.size(); ++i)
{
_config_id += "_";
_config_id += support::cpp11::to_string(input->info()->dimension(i));
_config_id += "_";
_config_id += support::cpp11::to_string(multiples[i]);
}
}
Status CLTileKernel::validate(const ITensorInfo *input, const ITensorInfo *output, const Multiples &multiples)
{
ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, multiples));
return Status{};
}
void CLTileKernel::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::DimZ);
Window slice = collapsed.first_slice_window_4D();
do
{
unsigned int idx = 0;
add_4D_tensor_argument(idx, _input, slice);
add_4D_tensor_argument(idx, _output, slice);
enqueue(queue, *this, slice, lws_hint());
}
while(collapsed.slide_window_slice_4D(slice));
}
} // namespace arm_compute
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