src/core/CL/kernels/CLChannelShuffleLayerKernel.cpp

/*
 * Copyright (c) 2018-2019 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/CLChannelShuffleLayerKernel.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/Error.h"
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/TensorInfo.h"
#include "arm_compute/core/Window.h"

namespace arm_compute
{
namespace
{
Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, unsigned int num_groups)
{
    ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input);
    ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8, DataType::S8, DataType::QASYMM8,
                                                         DataType::U16, DataType::S16,
                                                         DataType::U32, DataType::S32,
                                                         DataType::F16, DataType::F32);
    ARM_COMPUTE_RETURN_ERROR_ON_MSG(num_groups < 2, "Channel shuffling with less than 2 groups would be inefficient");

    const unsigned int channels = input->dimension(get_data_layout_dimension_index(input->data_layout(), DataLayoutDimension::CHANNEL));

    ARM_COMPUTE_RETURN_ERROR_ON_MSG(num_groups == channels, "Channel shuffling with same number of groups as number of channels would be inefficient");
    // There cannot be more groups than channels
    ARM_COMPUTE_RETURN_ERROR_ON(num_groups > channels);
    ARM_COMPUTE_RETURN_ERROR_ON_MSG((channels % num_groups) != 0, "The number of channels must be a multiple of the number of groups");

    // Checks performed when output is configured
    if(output->total_size() != 0)
    {
        ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output);
        ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_QUANTIZATION_INFO(input, output);
        ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
    }

    return Status{};
}

std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *output)
{
    // Output tensor auto initialization if not yet initialized
    auto_init_if_empty(*output, *input->clone());

    const bool             is_nhwc                             = input->data_layout() == DataLayout::NHWC;
    const unsigned int     num_elems_processed_per_iteration_x = is_nhwc ? 4 : max_cl_vector_width / input->element_size();
    constexpr unsigned int num_elems_processed_per_iteration_y = 2;

    // Configure kernel window
    Window                win = calculate_max_window(*input, Steps(num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y));
    AccessWindowRectangle input_access(input, 0, 0, num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y);
    AccessWindowRectangle output_access(output, 0, 0, num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y);

    const bool window_changed = update_window_and_padding(win, input_access, output_access);
    output_access.set_valid_region(win, input->valid_region());

    Window win_collapsed = win.collapse(win, Window::DimZ);

    Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{};
    return std::make_pair(err, win_collapsed);
}
} // namespace

CLChannelShuffleLayerKernel::CLChannelShuffleLayerKernel()
    : _input(nullptr), _output(nullptr)
{
}

void CLChannelShuffleLayerKernel::configure(const ICLTensor *input, ICLTensor *output, unsigned int num_groups)
{
    ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);

    _input  = input;
    _output = output;

    ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), num_groups));

    const DataLayout   data_layout = input->info()->data_layout();
    const bool         is_nhwc     = data_layout == DataLayout::NHWC;
    const unsigned int channels    = input->info()->dimension(get_data_layout_dimension_index(data_layout, DataLayoutDimension::CHANNEL));
    const unsigned int vec_size    = is_nhwc ? 4 : max_cl_vector_width / input->info()->element_size();

    // Set kernel build options
    CLBuildOptions build_opts;
    build_opts.add_option("-DNUM_GROUPS=" + support::cpp11::to_string(num_groups));
    build_opts.add_option("-DK=" + support::cpp11::to_string(channels / num_groups));
    build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(vec_size));
    build_opts.add_option("-DSRC_DIM_Z=" + support::cpp11::to_string(input->info()->dimension(2)));
    build_opts.add_option("-DLAST_ACCESSED=" + support::cpp11::to_string(std::max(static_cast<int>(channels - vec_size), 0)));

    switch(input->info()->element_size())
    {
        case 1:
            build_opts.add_option("-DDATA_TYPE=uchar");
            break;
        case 2:
            build_opts.add_option("-DDATA_TYPE=ushort");
            break;
        case 4:
            build_opts.add_option("-DDATA_TYPE=uint");
            break;
        default:
            ARM_COMPUTE_ERROR("Data type not supported");
    }

    // Create kernel
    std::string kernel_name = "channel_shuffle_" + lower_string(string_from_data_layout(data_layout));
    ;
    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));

    // Configure kernel window
    auto win_config = validate_and_configure_window(input->info(), output->info());
    ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
    ICLKernel::configure_internal(win_config.second);

    // Set config_id for enabling LWS tuning
    _config_id = kernel_name;
    _config_id += "_";
    _config_id += lower_string(string_from_data_type(input->info()->data_type()));
    _config_id += "_";
    _config_id += support::cpp11::to_string(num_groups);
    _config_id += "_";
    _config_id += support::cpp11::to_string(input->info()->dimension(0));
    _config_id += "_";
    _config_id += support::cpp11::to_string(input->info()->dimension(1));
    _config_id += "_";
    _config_id += support::cpp11::to_string(input->info()->dimension(2));
    _config_id += "_";
    _config_id += support::cpp11::to_string(output->info()->dimension(0));
    _config_id += "_";
    _config_id += support::cpp11::to_string(output->info()->dimension(1));
    _config_id += "_";
    _config_id += support::cpp11::to_string(output->info()->dimension(2));
}

Status CLChannelShuffleLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *output, unsigned int num_groups)
{
    ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, num_groups));
    ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), output->clone().get()).first);

    return Status{};
}

void CLChannelShuffleLayerKernel::run(const Window &window, cl::CommandQueue &queue)
{
    ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
    ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window);

    unsigned int idx = 0;
    add_4D_tensor_argument(idx, _input, window);
    add_4D_tensor_argument(idx, _output, window);
    enqueue(queue, *this, window, lws_hint());
}
} // namespace arm_compute