src/core/GLES_COMPUTE/kernels/GCTransposeKernel.cpp

/*
 * 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/GLES_COMPUTE/kernels/GCTransposeKernel.h"

#include "arm_compute/core/AccessWindowTranspose.h"
#include "arm_compute/core/Error.h"
#include "arm_compute/core/GLES_COMPUTE/GCHelpers.h"
#include "arm_compute/core/GLES_COMPUTE/GCKernelLibrary.h"
#include "arm_compute/core/GLES_COMPUTE/IGCTensor.h"
#include "arm_compute/core/GLES_COMPUTE/OpenGLES.h"
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/Types.h"

#include <set>
#include <string>

using namespace arm_compute;

void GCTransposeKernel::configure(const IGCTensor *input, IGCTensor *output)
{
    ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32);
    ARM_COMPUTE_ERROR_ON_NULLPTR(output);

    TensorShape  output_shape{ input->info()->tensor_shape() };
    const size_t w_out = input->info()->dimension(1);
    const size_t h_out = input->info()->dimension(0);
    output_shape.set(0, w_out);
    output_shape.set(1, h_out);

    // Output tensor auto inizialitation if not yet initialized
    auto_init_if_empty(*output->info(), output_shape, 1, input->info()->data_type(), input->info()->fixed_point_position());

    ARM_COMPUTE_ERROR_ON_MISMATCHING_DIMENSIONS(output->info()->tensor_shape(), output_shape);
    ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);

    _input  = input;
    _output = output;

    std::set<std::string> build_opts;
    std::string           dt_name = (input->info()->data_type() == DataType::F32) ? "DATA_TYPE_FP32" : "DATA_TYPE_FP16";
    build_opts.emplace(("#define " + dt_name));
    build_opts.emplace("#define LOCAL_SIZE_X " + support::cpp11::to_string(1));
    build_opts.emplace("#define LOCAL_SIZE_Y " + support::cpp11::to_string(1));
    build_opts.emplace("#define LOCAL_SIZE_Z " + support::cpp11::to_string(1));

    // Create kernel
    _kernel = static_cast<GCKernel>(GCKernelLibrary::get().create_kernel("transpose", build_opts));

    // Configure kernel window
    const unsigned int num_elems_processed_per_iteration = 4;

    Window win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration, num_elems_processed_per_iteration));

    AccessWindowRectangle input_access(input->info(), 0, 0, num_elems_processed_per_iteration, num_elems_processed_per_iteration);
    AccessWindowTranspose output_access(output->info(), 0, 0, num_elems_processed_per_iteration, num_elems_processed_per_iteration);
    update_window_and_padding(win, input_access, output_access);

    output_access.set_valid_region(win, input->info()->valid_region());

    IGCKernel::configure(win);
}

void GCTransposeKernel::run(const Window &window)
{
    ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
    ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IGCKernel::window(), window);

    _kernel.use();

    Window slice = window.first_slice_window_2D();

    do
    {
        unsigned int idx = 0;
        if(_input->info()->data_type() == DataType::F32)
        {
            add_2D_tensor_argument(idx, _input, 1, slice);
            add_2D_tensor_argument(idx, _output, 2, slice);
        }
        else if(_input->info()->data_type() == DataType::F16)
        {
            add_2D_tensor_argument(idx, _input, BufferParam(1, 3), slice);
            add_2D_tensor_argument(idx, _output, BufferParam(2, 3), slice);
        }

        _kernel.update_shader_params();
        enqueue(*this, slice);
    }
    while(window.slide_window_slice_2D(slice));
}