blob: 8a493209cab1f074b54c7b9bde265fe09e2bb777 [file] [log] [blame]
/*
* Copyright (c) 2017 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/CLMinMaxLocationKernel.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/Validate.h"
#include "arm_compute/core/Window.h"
#include <climits>
using namespace arm_compute;
CLMinMaxKernel::CLMinMaxKernel()
: _input(nullptr), _min_max(), _data_type_max_min()
{
}
void CLMinMaxKernel::configure(const ICLImage *input, cl::Buffer *min_max)
{
ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8, DataType::S16);
ARM_COMPUTE_ERROR_ON_TENSOR_NOT_2D(input);
ARM_COMPUTE_ERROR_ON(min_max == nullptr);
_input = input;
_min_max = min_max;
const unsigned int num_elems_processed_per_iteration = input->info()->dimension(0);
switch(input->info()->data_type())
{
case DataType::U8:
_data_type_max_min[0] = UCHAR_MAX;
_data_type_max_min[1] = 0;
break;
case DataType::S16:
_data_type_max_min[0] = SHRT_MAX;
_data_type_max_min[1] = SHRT_MIN;
break;
default:
ARM_COMPUTE_ERROR("You called with the wrong image data types");
}
// Set kernel build options
std::set<std::string> build_opts;
build_opts.emplace("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type()));
build_opts.emplace("-DDATA_TYPE_MAX=" + support::cpp11::to_string(_data_type_max_min[0]));
build_opts.emplace("-DDATA_TYPE_MIN=" + support::cpp11::to_string(_data_type_max_min[1]));
build_opts.emplace((0 != (num_elems_processed_per_iteration % max_cl_vector_width)) ? "-DNON_MULTIPLE_OF_16" : "");
// Create kernel
_kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("minmax", build_opts));
// Set fixed arguments
unsigned int idx = num_arguments_per_2D_tensor(); //Skip the input and output parameters
_kernel.setArg(idx++, *_min_max);
_kernel.setArg<cl_uint>(idx++, input->info()->dimension(0));
// Configure kernel window
Window win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration));
update_window_and_padding(win, AccessWindowHorizontal(input->info(), 0, num_elems_processed_per_iteration));
ICLKernel::configure(win);
}
void CLMinMaxKernel::run(const Window &window, cl::CommandQueue &queue)
{
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window);
// Reset mininum and maximum values
queue.enqueueWriteBuffer(*_min_max, CL_FALSE /* blocking */, 0, _data_type_max_min.size() * sizeof(int), _data_type_max_min.data());
Window slice = window.first_slice_window_2D();
do
{
unsigned int idx = 0;
add_2D_tensor_argument(idx, _input, slice);
enqueue(queue, *this, slice);
}
while(window.slide_window_slice_2D(slice));
}
CLMinMaxLocationKernel::CLMinMaxLocationKernel()
: _input(nullptr), _min_max_count(nullptr)
{
}
void CLMinMaxLocationKernel::configure(const ICLImage *input, cl::Buffer *min_max, cl::Buffer *min_max_count, ICLCoordinates2DArray *min_loc, ICLCoordinates2DArray *max_loc)
{
ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8, DataType::S16);
ARM_COMPUTE_ERROR_ON_TENSOR_NOT_2D(input);
ARM_COMPUTE_ERROR_ON(min_max == nullptr);
ARM_COMPUTE_ERROR_ON(min_max_count == nullptr && min_loc == nullptr && max_loc == nullptr);
_input = input;
_min_max_count = min_max_count;
// Set kernel build options
std::set<std::string> build_opts;
build_opts.emplace("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type()));
build_opts.emplace((min_max_count != nullptr) ? "-DCOUNT_MIN_MAX" : "");
build_opts.emplace((min_loc != nullptr) ? "-DLOCATE_MIN" : "");
build_opts.emplace((max_loc != nullptr) ? "-DLOCATE_MAX" : "");
// Create kernel
_kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("minmaxloc", build_opts));
// Set static arguments
unsigned int idx = num_arguments_per_2D_tensor(); //Skip the input and output parameters
_kernel.setArg(idx++, *min_max);
_kernel.setArg(idx++, *min_max_count);
if(min_loc != nullptr)
{
_kernel.setArg(idx++, min_loc->cl_buffer());
_kernel.setArg<cl_uint>(idx++, min_loc->max_num_values());
}
if(max_loc != nullptr)
{
_kernel.setArg(idx++, max_loc->cl_buffer());
_kernel.setArg<cl_uint>(idx++, max_loc->max_num_values());
}
// Configure kernel window
constexpr unsigned int num_elems_processed_per_iteration = 1;
Window win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration));
update_window_and_padding(win, AccessWindowHorizontal(input->info(), 0, num_elems_processed_per_iteration));
ICLKernel::configure(win);
}
void CLMinMaxLocationKernel::run(const Window &window, cl::CommandQueue &queue)
{
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window);
static const unsigned int zero_count = 0;
queue.enqueueWriteBuffer(*_min_max_count, CL_FALSE, 0 * sizeof(zero_count), sizeof(zero_count), &zero_count);
queue.enqueueWriteBuffer(*_min_max_count, CL_FALSE, 1 * sizeof(zero_count), sizeof(zero_count), &zero_count);
Window slice = window.first_slice_window_2D();
do
{
unsigned int idx = 0;
add_2D_tensor_argument(idx, _input, slice);
enqueue(queue, *this, slice);
}
while(window.slide_window_slice_2D(slice));
}