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/*
* Copyright (c) 2019-2020 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/CLBatchConcatenateLayerKernel.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 "support/StringSupport.h"
#include <map>
using namespace arm_compute;
namespace
{
std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, unsigned int batch_offset, ITensorInfo *output)
{
ARM_COMPUTE_UNUSED(batch_offset);
const unsigned int num_elems_processed_per_iteration = 16 / input->element_size();
// The window needs to be based on output, except for the batch size
Window win = calculate_max_window(*output, Steps(num_elems_processed_per_iteration));
// The total batch size is the concatenation of the batch size of the inputs
win.set(3, Window::Dimension(0, input->tensor_shape()[3], 1));
AccessWindowHorizontal input_access(input, 0, num_elems_processed_per_iteration);
AccessWindowHorizontal output_access(output, 0, num_elems_processed_per_iteration);
bool window_changed = update_window_and_padding(win, input_access, output_access);
output_access.set_valid_region(win, ValidRegion(Coordinates(), output->tensor_shape()));
Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{};
return std::make_pair(err, win);
}
Status validate_arguments(const ITensorInfo *input, unsigned int batch_offset, const ITensorInfo *output)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input);
ARM_COMPUTE_RETURN_ERROR_ON(input->data_type() == DataType::UNKNOWN);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(Window::DimX) != output->dimension(Window::DimX));
ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(Window::DimY) != output->dimension(Window::DimY));
ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(Window::DimZ) != output->dimension(Window::DimZ));
ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(3) + batch_offset > output->dimension(3));
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(4, input, output);
return Status{};
}
} // namespace
CLBatchConcatenateLayerKernel::CLBatchConcatenateLayerKernel()
: _input(nullptr), _output(nullptr), _batch_offset(0)
{
}
void CLBatchConcatenateLayerKernel::configure(const ICLTensor *input, unsigned int batch_offset, ICLTensor *output)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), batch_offset, output->info()));
_input = input;
_output = output;
_batch_offset = batch_offset;
const unsigned int num_elems_processed_per_iteration = 16 / input->info()->element_size();
// Add build options
CLBuildOptions build_opts;
build_opts.add_option("-DDATA_TYPE=" + get_underlying_cl_type_from_data_type(input->info()->data_type()));
build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(num_elems_processed_per_iteration));
if(is_data_type_quantized_asymmetric(input->info()->data_type()) && input->info()->quantization_info() != output->info()->quantization_info())
{
const UniformQuantizationInfo iq_info = input->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(iq_info.offset));
build_opts.add_option("-DOFFSET_OUT=" + float_to_string_with_full_precision(oq_info.offset));
build_opts.add_option("-DSCALE_IN1=" + float_to_string_with_full_precision(iq_info.scale));
build_opts.add_option("-DSCALE_OUT=" + float_to_string_with_full_precision(oq_info.scale));
}
// Create kernel
_kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("concatenate", build_opts.options()));
// Configure kernel window
auto win_config = validate_and_configure_window(input->info(), batch_offset, 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()));
// Set config_id for enabling LWS tuning
_config_id = "concatenate_";
_config_id += support::cpp11::to_string(3);
_config_id += "_";
_config_id += support::cpp11::to_string(batch_offset);
_config_id += "_";
_config_id += support::cpp11::to_string(input->info()->dimension(0));
_config_id += "_";
_config_id += support::cpp11::to_string(input->info()->dimension(1));
_config_id += "_";
_config_id += support::cpp11::to_string(input->info()->dimension(2));
_config_id += "_";
_config_id += support::cpp11::to_string(input->info()->dimension(3));
}
Status CLBatchConcatenateLayerKernel::validate(const arm_compute::ITensorInfo *input,
unsigned int batch_offset,
const arm_compute::ITensorInfo *output)
{
ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, batch_offset, output));
ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), batch_offset, output->clone().get()).first);
return Status{};
}
void CLBatchConcatenateLayerKernel::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_3D();
const int offset_to_first_elements_in_bytes = _batch_offset * _output->info()->strides_in_bytes()[3];
unsigned int idx = 2 * num_arguments_per_3D_tensor(); // Skip the input and output parameters
_kernel.setArg<cl_int>(idx, offset_to_first_elements_in_bytes);
do
{
unsigned int idx = 0;
add_3D_tensor_argument(idx, _input, slice);
add_3D_tensor_argument(idx, _output, slice);
enqueue(queue, *this, slice, lws_hint());
}
while(window.slide_window_slice_3D(slice));
}