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/*
* Copyright (c) 2018 Samsung Electronics Co., Ltd. All Rights Reserved
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
/*
* Copyright (c) 2016-2018 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/CLCastKernel.h"
#include "arm_compute/core/CL/CLHelpers.h"
#include "arm_compute/core/CL/CLKernelLibraryEx.h"
#include "arm_compute/core/CL/ICLTensor.h"
using namespace arm_compute;
CLCastKernel::CLCastKernel() : _input(nullptr), _output(nullptr) {}
void CLCastKernel::configure(const ICLTensor *input, ICLTensor *output, SubDataType input_subtype)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8, DataType::QASYMM8,
DataType::S16, DataType::S32, DataType::F16,
DataType::F32);
ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U8, DataType::QASYMM8,
DataType::S16, DataType::S32, DataType::F16,
DataType::F32);
ARM_COMPUTE_ERROR_ON_MISMATCHING_SHAPES(input, output);
_input = input;
_output = output;
constexpr unsigned int num_elems_processed_per_iteration = 16;
// Set kernel build options
CLBuildOptions build_opts;
build_opts.add_option("-DDATA_TYPE_IN=" + get_cl_type_from_data_type(input->info()->data_type()));
build_opts.add_option("-DDATA_TYPE_OUT=" +
get_cl_type_from_data_type(output->info()->data_type()));
build_opts.add_option(
("-DVEC_SIZE=" + support::cpp11::to_string(num_elems_processed_per_iteration)));
// Create kernel
if (is_data_type_quantized_asymmetric(input->info()->data_type()))
{
UniformQuantizationInfo qinfo = input->info()->quantization_info().uniform();
const float scale_in = qinfo.scale;
const int offset_in = qinfo.offset;
build_opts.add_option("-DSCALE=" + float_to_string_with_full_precision(scale_in));
build_opts.add_option("-DOFFSET=" + support::cpp11::to_string(offset_in));
_kernel = static_cast<cl::Kernel>(
CLKernelLibraryEx::get().create_kernel("cast_qasymm_in", build_opts.options()));
}
else if (is_data_type_quantized_asymmetric(output->info()->data_type()))
{
UniformQuantizationInfo qinfo = output->info()->quantization_info().uniform();
const float scale_in = qinfo.scale;
const float offset_in = qinfo.offset;
build_opts.add_option("-DSCALE=" + float_to_string_with_full_precision(scale_in));
build_opts.add_option("-DOFFSET=" + support::cpp11::to_string(offset_in));
_kernel = static_cast<cl::Kernel>(
CLKernelLibraryEx::get().create_kernel("cast_qasymm_out", build_opts.options()));
}
else
{
build_opts.add_option_if(input_subtype == SubDataType::BOOL, "-DBOOL_INPUT");
_kernel = static_cast<cl::Kernel>(
CLKernelLibraryEx::get().create_kernel("cast", build_opts.options()));
}
// Configure kernel window
Window win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration));
AccessWindowHorizontal input_access(input->info(), 0, num_elems_processed_per_iteration);
AccessWindowHorizontal output_access(output->info(), 0, num_elems_processed_per_iteration);
update_window_and_padding(win, input_access, output_access);
output_access.set_valid_region(win, input->info()->valid_region());
ICLKernel::configure_internal(win);
}
void CLCastKernel::run(const 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();
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 (collapsed.slide_window_slice_3D(slice));
}
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