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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/CLSelectKernel.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/Helpers.h"
#include "arm_compute/core/TensorInfo.h"
#include "arm_compute/core/Utils.h"
#include "arm_compute/core/Window.h"
#include "support/StringSupport.h"
namespace arm_compute
{
namespace
{
Status validate_arguments(const ITensorInfo *c, const ITensorInfo *x, const ITensorInfo *y, const ITensorInfo *output)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(c, x, y);
ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(x);
ARM_COMPUTE_RETURN_ERROR_ON(x->data_type() == DataType::UNKNOWN);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(x, y);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(x, y);
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(c, 1, DataType::U8);
const bool is_same_rank = (c->tensor_shape().num_dimensions() == x->tensor_shape().num_dimensions());
ARM_COMPUTE_RETURN_ERROR_ON(is_same_rank && (x->tensor_shape() != c->tensor_shape()));
ARM_COMPUTE_RETURN_ERROR_ON(!is_same_rank && ((c->tensor_shape().num_dimensions() > 1) || (c->tensor_shape().x() != x->tensor_shape()[x->tensor_shape().num_dimensions() - 1])));
if(output != nullptr && output->total_size() != 0)
{
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(x, output);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(x, output);
}
return Status{};
}
std::pair<Status, Window> validate_and_configure_window(ITensorInfo *c, ITensorInfo *x, ITensorInfo *y, ITensorInfo *output)
{
if(output != nullptr)
{
// Output tensor auto initialization if not yet initialized
auto_init_if_empty(*output, *x->clone());
}
const bool is_same_rank = (c->tensor_shape().num_dimensions() == x->tensor_shape().num_dimensions());
const unsigned int num_elems_processed_per_iteration = 16 / x->element_size();
// Configure kernel window
Window win = calculate_max_window(*x, Steps(num_elems_processed_per_iteration));
AccessWindowHorizontal x_access(x, 0, num_elems_processed_per_iteration);
AccessWindowHorizontal y_access(y, 0, num_elems_processed_per_iteration);
bool window_changed = update_window_and_padding(win, x_access, y_access);
// Update window for condition
if(is_same_rank)
{
AccessWindowHorizontal c_access(c, 0, num_elems_processed_per_iteration);
window_changed = window_changed || update_window_and_padding(win, c_access);
}
// Update window for output
if(output != nullptr)
{
AccessWindowHorizontal output_access(output, 0, num_elems_processed_per_iteration);
window_changed = window_changed || update_window_and_padding(win, output_access);
output_access.set_valid_region(win, x->valid_region());
}
Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{};
return std::make_pair(err, win);
}
} // namespace
CLSelectKernel::CLSelectKernel()
: _c(nullptr), _x(nullptr), _y(nullptr), _output(nullptr), _has_same_rank(false)
{
}
void CLSelectKernel::configure(const ICLTensor *c, const ICLTensor *x, const ICLTensor *y, ICLTensor *output)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(c, x, y, output);
ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(c->info(), x->info(), y->info(), output->info()));
_c = c;
_x = x;
_y = y;
_output = output;
_has_same_rank = (c->info()->tensor_shape().num_dimensions() == x->info()->tensor_shape().num_dimensions());
const unsigned int num_elems_processed_per_iteration = 16 / x->info()->element_size();
// Set build options
CLBuildOptions build_opts;
build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(x->info()->data_type()));
build_opts.add_option("-DSELECT_DATA_TYPE=" + get_cl_select_type_from_data_type(x->info()->data_type()));
build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(num_elems_processed_per_iteration));
// Create kernel
std::string kernel_name = "select";
if(_has_same_rank)
{
kernel_name += "_same_rank";
}
else
{
const bool is_input_rank_greater_than_two = x->info()->tensor_shape().num_dimensions() > 2;
if(is_input_rank_greater_than_two)
{
const size_t width = x->info()->tensor_shape().x();
const size_t height = x->info()->tensor_shape().y();
const size_t outer_size = x->info()->tensor_shape()[x->info()->tensor_shape().num_dimensions() - 1];
const size_t depth_size = x->info()->tensor_shape().total_size() / (width * height * outer_size);
build_opts.add_option("-DDEPTH_SIZE=" + support::cpp11::to_string(depth_size));
}
kernel_name += "_different_rank";
kernel_name += is_input_rank_greater_than_two ? "_n" : "_2";
}
_kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
// Configure kernel window
auto win_config = validate_and_configure_window(c->info(), x->info(), y->info(), output->info());
ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
ICLKernel::configure_internal(win_config.second);
_config_id = "select_";
_config_id += string_from_data_type(x->info()->data_type());
_config_id += "_";
_config_id += support::cpp11::to_string(x->info()->dimension(0));
_config_id += "_";
_config_id += support::cpp11::to_string(x->info()->dimension(1));
_config_id += "_";
_config_id += support::cpp11::to_string(x->info()->dimension(2));
}
Status CLSelectKernel::validate(const ITensorInfo *c, const ITensorInfo *x, const ITensorInfo *y, const ITensorInfo *output)
{
ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(c, x, y, output));
ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(c->clone().get(), x->clone().get(), y->clone().get(), output->clone().get()).first);
return Status{};
}
void CLSelectKernel::run(const arm_compute::Window &window, cl::CommandQueue &queue)
{
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window);
Window collapsed = window.collapse_if_possible(ICLKernel::window(), Window::DimZ);
Window slice = collapsed.first_slice_window_3D();
if(!_has_same_rank)
{
Window vector_slice = window.first_slice_window_1D();
vector_slice.set(Window::DimX, Window::Dimension(0, 0, 0));
unsigned int idx = 0;
add_1D_tensor_argument(idx, _c, vector_slice);
}
do
{
unsigned int idx = _has_same_rank ? 0 : num_arguments_per_1D_tensor();
if(_has_same_rank)
{
add_3D_tensor_argument(idx, _c, slice);
}
add_3D_tensor_argument(idx, _x, slice);
add_3D_tensor_argument(idx, _y, slice);
add_3D_tensor_argument(idx, _output, slice);
enqueue(queue, *this, slice, lws_hint());
}
while(collapsed.slide_window_slice_3D(slice));
}
} // namespace arm_compute