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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/CLWidthConcatenate2TensorsKernel.h"
#include "arm_compute/core/AccessWindowStatic.h"
#include "arm_compute/core/CL/CLHelpers.h"
#include "arm_compute/core/CL/CLKernelLibrary.h"
#include "arm_compute/core/CL/CLValidate.h"
#include "arm_compute/core/CL/ICLTensor.h"
#include "arm_compute/core/CL/OpenCL.h"
#include "arm_compute/core/Error.h"
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/IAccessWindow.h"
#include "arm_compute/core/TensorInfo.h"
#include "arm_compute/core/Utils.h"
#include "arm_compute/core/Window.h"
#include "arm_compute/core/utils/helpers/tensor_info.h"
#include "arm_compute/core/utils/misc/ShapeCalculator.h"
#include "support/StringSupport.h"
namespace arm_compute
{
namespace
{
constexpr unsigned int num_elems_processed_per_iteration = 8;
std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output)
{
// The window needs to be based on the output
Window win = calculate_max_window(*output, Steps(num_elems_processed_per_iteration));
AccessWindowStatic input1_access(input1, 0, 0, ceil_to_multiple(input1->dimension(0), num_elems_processed_per_iteration), input1->dimension(1));
const unsigned int input2_right_padding = ((output->dimension(0) / num_elems_processed_per_iteration) * num_elems_processed_per_iteration - input1->dimension(0) - input2->dimension(
0)) % num_elems_processed_per_iteration;
AccessWindowStatic input2_access(input2, -(input1->dimension(0) % num_elems_processed_per_iteration),
0, input2->dimension(0) + input2_right_padding, input2->dimension(1));
AccessWindowHorizontal output_access(output, 0, num_elems_processed_per_iteration);
bool window_changed = update_window_and_padding(win, input1_access, input2_access, output_access);
Window win_collapsed = win.collapse(win, Window::DimZ);
Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{};
return std::make_pair(err, win_collapsed);
}
Status validate_arguments(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input1, input2, output);
ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input1);
ARM_COMPUTE_RETURN_ERROR_ON(input1->data_type() == DataType::UNKNOWN);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input1, input2, output);
ARM_COMPUTE_RETURN_ERROR_ON(input1->dimension(0) + input2->dimension(0) > output->dimension(0));
for(size_t i = 1; i < Coordinates::num_max_dimensions; ++i)
{
ARM_COMPUTE_RETURN_ERROR_ON(input1->dimension(i) != output->dimension(i));
ARM_COMPUTE_RETURN_ERROR_ON(input2->dimension(i) != output->dimension(i));
}
ARM_COMPUTE_RETURN_ERROR_ON(input1->num_dimensions() > 4);
return Status{};
}
} // namespace
CLWidthConcatenate2TensorsKernel::CLWidthConcatenate2TensorsKernel()
: _input1(nullptr), _input2(nullptr), _output(nullptr)
{
}
Status CLWidthConcatenate2TensorsKernel::validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output)
{
ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input1, input2, output));
ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input1->clone().get(), input2->clone().get(), output->clone().get()).first);
return Status{};
}
void CLWidthConcatenate2TensorsKernel::configure(const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output)
{
configure(CLKernelLibrary::get().get_compile_context(), input1, input2, output);
}
void CLWidthConcatenate2TensorsKernel::configure(const CLCompileContext &compile_context, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input1, input2, output);
ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input1->info(), input2->info(), output->info()));
_input1 = input1;
_input2 = input2;
_output = output;
// Add build options
CLBuildOptions build_opts;
build_opts.add_option("-DDATA_TYPE=" + get_underlying_cl_type_from_data_type(input1->info()->data_type()));
build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(num_elems_processed_per_iteration));
build_opts.add_option("-DDEPTH=" + support::cpp11::to_string(input1->info()->dimension(2)));
build_opts.add_option("-DINPUT1_WIDTH=" + support::cpp11::to_string(input1->info()->dimension(0)));
build_opts.add_option("-DELEMENT_SIZE=" + support::cpp11::to_string(input1->info()->element_size()));
// If input have different quantization info set quantization parameters needed for the re-quantization process
const bool have_different_qinfo = helpers::tensor_info::tensors_have_different_quantization_info(output->info(), input1->info(), input2->info());
if(is_data_type_quantized_asymmetric(input1->info()->data_type()) && have_different_qinfo)
{
const UniformQuantizationInfo iq1_info = input1->info()->quantization_info().uniform();
const UniformQuantizationInfo iq2_info = input2->info()->quantization_info().uniform();
const UniformQuantizationInfo oq_info = output->info()->quantization_info().uniform();
build_opts.add_option("-DOFFSET_IN1=" + float_to_string_with_full_precision(iq1_info.offset));
build_opts.add_option("-DSCALE_IN1=" + float_to_string_with_full_precision(iq1_info.scale));
build_opts.add_option("-DOFFSET_IN2=" + float_to_string_with_full_precision(iq2_info.offset));
build_opts.add_option("-DSCALE_IN2=" + float_to_string_with_full_precision(iq2_info.scale));
build_opts.add_option("-DOFFSET_OUT=" + float_to_string_with_full_precision(oq_info.offset));
build_opts.add_option("-DSCALE_OUT=" + float_to_string_with_full_precision(oq_info.scale));
}
// Create kernel
_kernel = create_kernel(compile_context, "concatenate_width_x2", build_opts.options());
// Configure kernel window
auto win_config = validate_and_configure_window(input1->info(), input2->info(), output->info());
ARM_COMPUTE_ERROR_THROW_ON(std::get<0>(win_config));
ICLKernel::configure_internal(std::get<1>(win_config));
// Set output valid region
output->info()->set_valid_region(ValidRegion(Coordinates(), output->info()->tensor_shape()));
// Pass paddings as arguments to the kernel
const unsigned int input1_width = input1->info()->dimension(0);
const unsigned int input1_right_padding = ceil_to_multiple(input1_width, num_elems_processed_per_iteration) - input1_width;
const unsigned int input2_left_padding = input1_width % num_elems_processed_per_iteration;
unsigned int idx0 = 3 * num_arguments_per_4D_tensor();
_kernel.setArg<cl_uint>(idx0++, input1_right_padding);
_kernel.setArg<cl_uint>(idx0++, input2_left_padding);
// Set config_id for enabling LWS tuning
_config_id = "concatenate_width_x2_";
_config_id += lower_string(string_from_data_type(input1->info()->data_type()));
_config_id += "_";
_config_id += support::cpp11::to_string(input1->info()->dimension(0));
_config_id += "_";
_config_id += support::cpp11::to_string(input1->info()->dimension(1));
_config_id += "_";
_config_id += support::cpp11::to_string(input2->info()->dimension(0));
_config_id += "_";
_config_id += support::cpp11::to_string(input2->info()->dimension(1));
}
void CLWidthConcatenate2TensorsKernel::run(const Window &window, cl::CommandQueue &queue)
{
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window);
Window slice = window.first_slice_window_4D();
do
{
unsigned int idx = 0;
add_4D_tensor_argument(idx, _input1, slice);
add_4D_tensor_argument(idx, _input2, slice);
add_4D_tensor_argument(idx, _output, slice);
enqueue(queue, *this, window, lws_hint());
}
while(window.slide_window_slice_4D(slice));
}
} // namespace arm_compute
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