blob: 281d1903814908b4dd1cc0eb7ea78949d8c765c4 [file] [log] [blame]
/*
* Copyright (c) 2018-2021 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 "src/core/gpu/cl/kernels/ClWidthConcatenate4TensorsKernel.h"
#include "arm_compute/core/CL/CLHelpers.h"
#include "arm_compute/core/CL/CLKernelLibrary.h"
#include "arm_compute/core/CL/ICLTensor.h"
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/Utils.h"
#include "src/core/CL/CLValidate.h"
#include "src/core/helpers/WindowHelpers.h"
#include "src/core/utils/helpers/tensor_info.h"
#include "support/Cast.h"
#include "support/StringSupport.h"
namespace arm_compute
{
namespace opencl
{
namespace kernels
{
namespace
{
Status validate_arguments(const ITensorInfo *src1, const ITensorInfo *src2, const ITensorInfo *src3, const ITensorInfo *src4, const ITensorInfo *dst)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(src1, src2, src3, src4, dst);
ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(src1);
ARM_COMPUTE_RETURN_ERROR_ON(src1->data_type() == DataType::UNKNOWN);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(src1, src2, src3, src4, dst);
ARM_COMPUTE_RETURN_ERROR_ON(src1->dimension(0) + src2->dimension(0) + src3->dimension(0) + src4->dimension(0) > dst->dimension(0));
for(size_t i = 1; i < Coordinates::num_max_dimensions; ++i)
{
ARM_COMPUTE_RETURN_ERROR_ON(src1->dimension(i) != dst->dimension(i));
ARM_COMPUTE_RETURN_ERROR_ON(src2->dimension(i) != dst->dimension(i));
ARM_COMPUTE_RETURN_ERROR_ON(src3->dimension(i) != dst->dimension(i));
ARM_COMPUTE_RETURN_ERROR_ON(src4->dimension(i) != dst->dimension(i));
}
ARM_COMPUTE_RETURN_ERROR_ON(src1->num_dimensions() > 4);
return Status{};
}
} // namespace
ClWidthConcatenate4TensorsKernel::ClWidthConcatenate4TensorsKernel()
{
}
Status ClWidthConcatenate4TensorsKernel::validate(const ITensorInfo *src1, const ITensorInfo *src2, const ITensorInfo *src3, const ITensorInfo *src4, const ITensorInfo *dst)
{
ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(src1, src2, src3, src4, dst));
return Status{};
}
void ClWidthConcatenate4TensorsKernel::configure(const CLCompileContext &compile_context,
ITensorInfo *src1, ITensorInfo *src2,
ITensorInfo *src3, ITensorInfo *src4,
ITensorInfo *dst)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(src1, src2, src3, src4, dst);
ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(src1, src2, src3, src4, dst));
auto padding_info = get_padding_info({ src1, src2, src3, src4, dst });
const unsigned int min_dimension = std::min(std::min(src1->dimension(0), src2->dimension(0)), std::min(src3->dimension(0), src4->dimension(0)));
const unsigned int num_elems_processed_per_iteration = adjust_vec_size(8, min_dimension);
const unsigned int vec_size_leftover = dst->dimension(0) % num_elems_processed_per_iteration;
// Add build options
CLBuildOptions build_opts;
build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(src1->data_type()));
build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(num_elems_processed_per_iteration));
build_opts.add_option("-DVEC_SIZE_LEFTOVER=" + support::cpp11::to_string(vec_size_leftover));
build_opts.add_option("-DDEPTH=" + support::cpp11::to_string(src1->dimension(2)));
build_opts.add_option("-DINPUT1_WIDTH=" + support::cpp11::to_string(src1->dimension(0)));
build_opts.add_option("-DINPUT2_WIDTH=" + support::cpp11::to_string(src2->dimension(0)));
build_opts.add_option("-DINPUT3_WIDTH=" + support::cpp11::to_string(src3->dimension(0)));
build_opts.add_option("-DINPUT4_WIDTH=" + support::cpp11::to_string(src4->dimension(0)));
build_opts.add_option("-DELEMENT_SIZE=" + support::cpp11::to_string(src1->element_size()));
build_opts.add_option("-DINPUT1_ROTATE_N=" + support::cpp11::to_string((src1->dimension(0) - vec_size_leftover) % num_elems_processed_per_iteration));
build_opts.add_option("-DINPUT2_ROTATE_N=" + support::cpp11::to_string((src1->dimension(0) + src2->dimension(0) - vec_size_leftover) % num_elems_processed_per_iteration));
build_opts.add_option("-DINPUT3_ROTATE_N=" + support::cpp11::to_string((src1->dimension(0) + src2->dimension(0) + src3->dimension(0) - vec_size_leftover) % num_elems_processed_per_iteration));
// If soources 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(dst, src1, src2, src3, src4);
if(is_data_type_quantized_asymmetric(src1->data_type()) && have_different_qinfo)
{
const UniformQuantizationInfo iq1_info = src1->quantization_info().uniform();
const UniformQuantizationInfo iq2_info = src2->quantization_info().uniform();
const UniformQuantizationInfo iq3_info = src3->quantization_info().uniform();
const UniformQuantizationInfo iq4_info = src4->quantization_info().uniform();
const UniformQuantizationInfo oq_info = dst->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_IN3=" + float_to_string_with_full_precision(iq3_info.offset));
build_opts.add_option("-DSCALE_IN3=" + float_to_string_with_full_precision(iq3_info.scale));
build_opts.add_option("-DOFFSET_IN4=" + float_to_string_with_full_precision(iq4_info.offset));
build_opts.add_option("-DSCALE_IN4=" + float_to_string_with_full_precision(iq4_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_x4", build_opts.options());
// Configure kernel window
Window win = calculate_max_window(*dst, Steps(num_elems_processed_per_iteration));
ICLKernel::configure_internal(win.collapse(win, Window::DimZ));
ARM_COMPUTE_ERROR_ON(has_padding_changed(padding_info));
// Set config_id for enabling LWS tuning
_config_id = "concatenate_width_x4_";
_config_id += lower_string(string_from_data_type(src1->data_type()));
_config_id += "_";
_config_id += support::cpp11::to_string(src1->dimension(0));
_config_id += "_";
_config_id += support::cpp11::to_string(src1->dimension(1));
_config_id += "_";
_config_id += support::cpp11::to_string(src2->dimension(0));
_config_id += "_";
_config_id += support::cpp11::to_string(src2->dimension(1));
_config_id += "_";
_config_id += support::cpp11::to_string(src3->dimension(0));
_config_id += "_";
_config_id += support::cpp11::to_string(src3->dimension(1));
_config_id += "_";
_config_id += support::cpp11::to_string(src4->dimension(0));
_config_id += "_";
_config_id += support::cpp11::to_string(src4->dimension(1));
}
void ClWidthConcatenate4TensorsKernel::run_op(ITensorPack &tensors, const Window &window, ::cl::CommandQueue &queue)
{
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window);
const auto src0 = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC_VEC));
const auto src1 = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC_VEC + 1));
const auto src2 = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC_VEC + 2));
const auto src3 = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC_VEC + 3));
auto dst = utils::cast::polymorphic_downcast<ICLTensor *>(tensors.get_tensor(TensorType::ACL_DST));
Window slice = window.first_slice_window_4D();
do
{
unsigned int idx = 0;
add_4D_tensor_argument(idx, src0, slice);
add_4D_tensor_argument(idx, src1, slice);
add_4D_tensor_argument(idx, src2, slice);
add_4D_tensor_argument(idx, src3, slice);
add_4D_tensor_argument(idx, dst, slice);
enqueue(queue, *this, window, lws_hint());
}
while(window.slide_window_slice_4D(slice));
}
} // namespace kernels
} // namespace opencl
} // namespace arm_compute