blob: 8632bdf623286d660c87573c1b2e565fda056b8f [file] [log] [blame]
/*
* Copyright (c) 2019-2023 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/CL/kernels/CLMeanStdDevNormalizationKernel.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/CL/OpenCL.h"
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/TensorInfo.h"
#include "arm_compute/core/utils/helpers/AdjustVecSize.h"
#include "arm_compute/core/utils/StringUtils.h"
#include "src/core/CL/CLValidate.h"
#include "src/core/helpers/AutoConfiguration.h"
#include "src/core/helpers/WindowHelpers.h"
#include "support/StringSupport.h"
namespace arm_compute
{
namespace
{
Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, float epsilon)
{
ARM_COMPUTE_UNUSED(epsilon);
ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input);
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input);
ARM_COMPUTE_RETURN_ERROR_ON_MSG(input->num_dimensions() > 2, "Input tensor cannot have more than 2 dimensions");
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32);
// Checks performed when output is configured
if ((output != nullptr) && (output->total_size() != 0))
{
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
}
return Status{};
}
} // namespace
CLMeanStdDevNormalizationKernel::CLMeanStdDevNormalizationKernel()
: _input(nullptr), _output(nullptr), _run_in_place(false)
{
_type = CLKernelType::ELEMENTWISE;
}
void CLMeanStdDevNormalizationKernel::configure(ICLTensor *input, ICLTensor *output, float epsilon)
{
configure(CLKernelLibrary::get().get_compile_context(), input, output, epsilon);
}
void CLMeanStdDevNormalizationKernel::configure(const CLCompileContext &compile_context,
ICLTensor *input,
ICLTensor *output,
float epsilon)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input);
_run_in_place = (output == nullptr) || (output == input);
ARM_COMPUTE_ERROR_THROW_ON(CLMeanStdDevNormalizationKernel::validate(
input->info(), (output != nullptr) ? output->info() : nullptr, epsilon));
if (output != nullptr)
{
auto_init_if_empty(*output->info(), *input->info());
}
_input = input;
_output = output;
const unsigned int num_elems_processed_per_iteration =
adjust_vec_size(16 / input->info()->element_size(), input->info()->dimension(0));
// Set build options
CLBuildOptions build_opts;
build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type()));
build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(num_elems_processed_per_iteration));
build_opts.add_option("-DEPSILON=" + float_to_string_with_full_precision(epsilon));
build_opts.add_option("-DWIDTH=" + support::cpp11::to_string(input->info()->dimension(0)));
build_opts.add_option_if(input->info()->data_type() == DataType::F16, "-DMEANSTDNORM_HALF");
build_opts.add_option_if(_run_in_place, "-DIN_PLACE");
// Create kernel
_kernel = create_kernel(compile_context, "mean_stddev_normalization", build_opts.options());
// Configure kernel window
Window win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration));
ICLKernel::configure_internal(win);
// Set config_id for enabling LWS tuning
_config_id = "mean_stddev_normalization_layer_";
_config_id += lower_string(string_from_data_type(input->info()->data_type()));
_config_id += "_";
_config_id += support::cpp11::to_string(input->info()->dimension(0));
_config_id += "_";
_config_id += support::cpp11::to_string(input->info()->dimension(1));
}
Status CLMeanStdDevNormalizationKernel::validate(const ITensorInfo *input, const ITensorInfo *output, float epsilon)
{
ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, epsilon));
return Status{};
}
void CLMeanStdDevNormalizationKernel::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_2D();
// Set slice step equal to width to force gws[0] to 1, as each thread normalizes across all rows
slice.set_dimension_step(Window::DimX, _input->info()->dimension(0));
do
{
unsigned int idx = 0;
add_2D_tensor_argument(idx, _input, slice);
add_2D_tensor_argument_if((!_run_in_place), idx, _output, slice);
enqueue(queue, *this, slice, lws_hint());
} while (window.slide_window_slice_2D(slice));
}
} // namespace arm_compute