src/core/CL/kernels/CLWinogradInputTransformKernel.cpp

/*
 * 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 "src/core/CL/kernels/CLWinogradInputTransformKernel.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/Error.h"
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/Types.h"
#include "arm_compute/core/Utils.h"
#include "arm_compute/core/utils/misc/ShapeCalculator.h"
#include "src/core/AccessWindowStatic.h"
#include "src/core/CL/CLValidate.h"
#include "src/core/helpers/AutoConfiguration.h"
#include "src/core/helpers/WindowHelpers.h"
#include "support/StringSupport.h"

using namespace arm_compute;

namespace
{
Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, const WinogradInfo &winograd_info)
{
    ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F32, DataType::F16);
    ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input);

    const PadStrideInfo conv_info        = winograd_info.convolution_info;
    const Size2D        output_tile_size = winograd_info.output_tile_size;
    const Size2D        kernel_size      = winograd_info.kernel_size;
    ARM_COMPUTE_RETURN_ERROR_ON_MSG(conv_info.stride().first != 1 || conv_info.stride().second != 1, "Winograd input transform only supports unit strides");
    ARM_COMPUTE_RETURN_ERROR_ON_MSG(!cl_winograd_convolution_layer_supported(output_tile_size, kernel_size, input->data_layout()), "Winograd input transform not supported");

    ARM_COMPUTE_UNUSED(conv_info);
    ARM_COMPUTE_UNUSED(output_tile_size);
    ARM_COMPUTE_UNUSED(kernel_size);

    // Validate configured output
    if(output->total_size() != 0)
    {
        const TensorShape output_shape = misc::shape_calculator::compute_winograd_input_transform_shape(*input, winograd_info);

        ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(), output_shape);
        ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
    }

    return Status{};
}

std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *output, const WinogradInfo &winograd_info)
{
    ARM_COMPUTE_UNUSED(output);
    ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);

    bool   window_changed = false;
    Window win            = calculate_max_window(*input, Steps(1, 1));

    if(input->data_layout() == DataLayout::NCHW)
    {
        const PadStrideInfo conv_info        = winograd_info.convolution_info;
        const Size2D        output_tile_size = winograd_info.output_tile_size;
        const Size2D        kernel_size      = winograd_info.kernel_size;

        unsigned int num_elems_read_per_iteration_x = output_tile_size.width + kernel_size.width - 1;
        unsigned int num_elems_read_per_iteration_y = output_tile_size.height + kernel_size.height - 1;

        AccessWindowRectangle input_access(input, -conv_info.pad_left(), -conv_info.pad_top(), num_elems_read_per_iteration_x, num_elems_read_per_iteration_y);
        window_changed = update_window_and_padding(win, input_access);
    }

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

CLWinogradInputTransformKernel::CLWinogradInputTransformKernel()
    : _border_size(0), _input(nullptr), _output(nullptr), _data_layout(DataLayout::UNKNOWN), _num_tiles_x(0), _num_tiles_y(0), _step_z(1)
{
}

BorderSize CLWinogradInputTransformKernel::border_size() const
{
    return _border_size;
}

void CLWinogradInputTransformKernel::configure(const ICLTensor *input, ICLTensor *output, const WinogradInfo &winograd_info)
{
    configure(CLKernelLibrary::get().get_compile_context(), input, output, winograd_info);
}

void CLWinogradInputTransformKernel::configure(const CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const WinogradInfo &winograd_info)
{
    ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
    ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), winograd_info));

    auto padding_info = get_padding_info({ input, output });

    const PadStrideInfo conv_info        = winograd_info.convolution_info;
    const Size2D        output_tile_size = winograd_info.output_tile_size;
    const Size2D        kernel_size      = winograd_info.kernel_size;

    _data_layout = input->info()->data_layout();

    const size_t idx_w = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::WIDTH);
    const size_t idx_h = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::HEIGHT);

    // Compute the number of output tiles along the x and y direction of size "output_tile_size"
    const Size2D num_tiles = compute_winograd_convolution_tiles(Size2D(input->info()->dimension(idx_w), input->info()->dimension(idx_h)),
                                                                kernel_size,
                                                                output_tile_size,
                                                                conv_info);

    _input       = input;
    _output      = output;
    _num_tiles_x = num_tiles.width;
    _num_tiles_y = num_tiles.height;

    const TensorShape output_shape = misc::shape_calculator::compute_winograd_input_transform_shape(*input->info(), winograd_info);

    // Output auto initialization if not yet initialized
    auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(output_shape));

    ARM_COMPUTE_ERROR_ON(_num_tiles_x * _num_tiles_y != static_cast<int>(output->info()->dimension(1)));
    const size_t total_batches = input->info()->tensor_shape().total_size_upper(3);

    CLBuildOptions build_opts;
    build_opts.add_option("-DNUM_TILES_X=" + support::cpp11::to_string(_num_tiles_x));
    build_opts.add_option("-DPAD_LEFT=" + support::cpp11::to_string(conv_info.pad_left()));
    build_opts.add_option("-DPAD_TOP=" + support::cpp11::to_string(conv_info.pad_top()));
    build_opts.add_option("-DOUTPUT_TILE_W=" + support::cpp11::to_string(output_tile_size.width));
    build_opts.add_option("-DOUTPUT_TILE_H=" + support::cpp11::to_string(output_tile_size.height));
    build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type()));
    build_opts.add_option_if(winograd_info.kernel_size.height == 1, "-DWINOGRAD_INPUT_TRANSFORM_HORIZONTAL");
    build_opts.add_option_if(winograd_info.kernel_size.width == 1, "-DWINOGRAD_INPUT_TRANSFORM_VERTICAL");
    if(_data_layout == DataLayout::NHWC)
    {
        build_opts.add_option_if(total_batches > 1, "-DNUM_TILES_Y=" + support::cpp11::to_string(_num_tiles_y));
        build_opts.add_option("-DSRC_DIM_1=" + support::cpp11::to_string(_input->info()->dimension(1)));
        build_opts.add_option("-DSRC_DIM_2=" + support::cpp11::to_string(_input->info()->dimension(2)));
    }
    else
    {
        build_opts.add_option_if(total_batches > 1, "-DSRC_DEPTH=" + support::cpp11::to_string(_input->info()->dimension(2)));
    }

    // Create kernel
    std::string kernel_name = "winograd_input_transform_" + output_tile_size.to_string() + "_" + kernel_size.to_string();

    // Get the maximum dimension from the tile size
    const unsigned int tile_max_dim = std::max(output_tile_size.width, output_tile_size.height);

    // Check optimized kernel if output_dims == 2x2
    if((tile_max_dim == 2) && (_data_layout == DataLayout::NCHW))
    {
        _step_z = (_input->info()->dimension(2) % 2) != 0 ? 1 : 2;
    }

    // Append stepz and data layout
    kernel_name += "_stepz";
    kernel_name += support::cpp11::to_string(_step_z);
    kernel_name += "_" + lower_string(string_from_data_layout(_data_layout));

    _kernel = create_kernel(compile_context, kernel_name, build_opts.options());

    // Create window and update padding
    auto win_config = validate_and_configure_window(input->info(), output->info(), winograd_info);
    ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
    ICLKernel::configure_internal(win_config.second, cl::NDRange(1, 1, 8));

    _border_size = BorderSize(_input->info()->padding());

    ARM_COMPUTE_ERROR_ON((input->info()->data_layout() == DataLayout::NHWC) && has_padding_changed(padding_info));

    _config_id = kernel_name;
    _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(conv_info.pad_left());
    _config_id += "_";
    _config_id += support::cpp11::to_string(conv_info.pad_top());
    _config_id += "_";
    _config_id += lower_string(string_from_data_layout(_data_layout));
}

Status CLWinogradInputTransformKernel::validate(const ITensorInfo *input, const ITensorInfo *output, const WinogradInfo &winograd_info)
{
    ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
    ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, winograd_info));
    ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), output->clone().get(), winograd_info).first);

    return Status{};
}

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

    const size_t idx_w         = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::WIDTH);
    const size_t idx_h         = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::HEIGHT);
    const size_t idx_c         = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::CHANNEL);
    const size_t total_batches = window.shape().total_size_upper(3);

    // Collapse window
    Window window_collapsed = window.collapse_if_possible(ICLKernel::window(), Window::DimZ);

    Window slice = window_collapsed.first_slice_window_3D();
    slice.set(idx_w, Window::Dimension(0, _num_tiles_x, 1));
    slice.set(idx_h, Window::Dimension(0, _num_tiles_y, 1));
    if(_data_layout == DataLayout::NHWC)
    {
        slice.set(idx_h, Window::Dimension(0, _num_tiles_y * total_batches, 1));
    }

    ARM_COMPUTE_ERROR_ON(((slice[idx_c].end() - slice[idx_c].start()) % _step_z) != 0);
    slice.set(idx_c, Window::Dimension(slice[idx_c].start(), slice[idx_c].end(), _step_z));

    unsigned int idx = 2 * num_arguments_per_3D_tensor();
    _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_input->info()->strides_in_bytes()[3]));
    _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_output->info()->strides_in_bytes()[3]));

    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(window_collapsed.slide_window_slice_3D(slice));
}