ClGemmLowpQuantizeDownInt32ScaleByFixedPointKernel.cpp

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/*
 * Copyright (c) 2020-2023 Arm Limited.
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#include "src/gpu/cl/kernels/ClGemmLowpQuantizeDownInt32ScaleByFixedPointKernel.h"
 
#include "arm_compute/core/CL/CLHelpers.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/helpers/AdjustVecSize.h"
#include "arm_compute/core/utils/misc/ShapeCalculator.h"
#include "arm_compute/core/utils/quantization/AsymmHelpers.h"
#include "arm_compute/core/utils/StringUtils.h"
#include "arm_compute/core/Validate.h"
 
#include "src/core/helpers/AutoConfiguration.h"
#include "src/core/helpers/WindowHelpers.h"
#include "support/Cast.h"
#include "support/StringSupport.h"
 
namespace arm_compute
{
namespace opencl
{
namespace kernels
{
namespace
{
Status validate_arguments(const ITensorInfo             *src,
                          const ITensorInfo             *bias,
                          const ITensorInfo             *dst,
                          const GEMMLowpOutputStageInfo *info)
{
    ARM_COMPUTE_UNUSED(info);
    ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(src, 1, DataType::S32);
 
    // Check biases if exist
    if (bias != nullptr)
    {
        ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(src, bias);
        ARM_COMPUTE_RETURN_ERROR_ON(bias->num_dimensions() > 1);
        ARM_COMPUTE_RETURN_ERROR_ON(src->dimension(0) != bias->dimension(0));
    }
 
    if (dst->total_size() != 0)
    {
        ARM_COMPUTE_RETURN_ERROR_ON_MSG(dst->data_type() != info->output_data_type, "Mismatching dst data type");
        ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(src, dst);
    }
 
    return Status{};
}
} // namespace
 
ClGemmLowpQuantizeDownInt32ScaleByFixedPointKernel::ClGemmLowpQuantizeDownInt32ScaleByFixedPointKernel()
{
    _type = CLKernelType::ELEMENTWISE;
}
 
Status ClGemmLowpQuantizeDownInt32ScaleByFixedPointKernel::validate(const ITensorInfo             *src,
                                                                    const ITensorInfo             *bias,
                                                                    const ITensorInfo             *dst,
                                                                    const GEMMLowpOutputStageInfo *info)
{
    ARM_COMPUTE_ERROR_ON_NULLPTR(src, dst);
    ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(src, bias, dst, info));
 
    return Status{};
}
 
void ClGemmLowpQuantizeDownInt32ScaleByFixedPointKernel::configure(const CLCompileContext        &compile_context,
                                                                   const ITensorInfo             *src,
                                                                   const ITensorInfo             *bias,
                                                                   ITensorInfo                   *dst,
                                                                   const GEMMLowpOutputStageInfo *info)
{
    // Perform validate step
    ARM_COMPUTE_ERROR_ON_NULLPTR(src, dst);
    ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(src, bias, dst, info));
 
    auto padding_info = get_padding_info({src, bias, dst});
 
    // dst auto inizialitation if not yet initialized
    auto_init_if_empty(*dst, src->clone()->set_data_type(info->output_data_type));
 
    const unsigned int num_elems_processed_per_iteration = adjust_vec_size(4, src->dimension(0));
 
    // Set the arguments to pass at compile time
    auto           min = info->gemmlowp_min_bound;
    auto           max = info->gemmlowp_max_bound;
    CLBuildOptions build_opts;
    build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(num_elems_processed_per_iteration));
    build_opts.add_option("-DVEC_SIZE_LEFTOVER=" +
                          support::cpp11::to_string(src->dimension(0) % num_elems_processed_per_iteration));
    build_opts.add_option("-DRESULT_OFFSET_AFTER_SHIFT=" + support::cpp11::to_string(info->gemmlowp_offset));
    build_opts.add_option("-DRESULT_FIXEDPOINT_MULTIPLIER=" + support::cpp11::to_string(info->gemmlowp_multiplier));
    build_opts.add_option("-DRESULT_SHIFT=" + support::cpp11::to_string(info->gemmlowp_shift));
    build_opts.add_option("-DOUTPUT_DATA_TYPE=" + get_cl_type_from_data_type(dst->data_type()));
    build_opts.add_option_if(
        (min > std::get<0>(quantization::get_min_max_values_from_quantized_data_type(info->output_data_type))) &&
            (min != max),
        "-DMIN_BOUND=" + support::cpp11::to_string(min));
    build_opts.add_option_if(
        (max < std::get<1>(quantization::get_min_max_values_from_quantized_data_type(info->output_data_type))) &&
            (min != max),
        "-DMAX_BOUND=" + support::cpp11::to_string(max));
    build_opts.add_option_if(bias != nullptr, "-DADD_BIAS");
 
    // Create kernel
    const std::string kernel_name = (info->output_data_type == DataType::QSYMM16)
                                        ? "gemmlowp_output_stage_quantize_down_fixedpoint_qsymm16"
                                        : "gemmlowp_output_stage_quantize_down_fixedpoint";
 
    // A macro guard to compile ONLY the kernel of interest
    build_opts.add_option("-D" + upper_string(kernel_name));
 
    _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
 
    // Configure kernel window
    auto win = calculate_max_window(*dst, Steps(num_elems_processed_per_iteration));
    ICLKernel::configure_internal(win);
 
    ARM_COMPUTE_ERROR_ON(has_padding_changed(padding_info));
}
 
void ClGemmLowpQuantizeDownInt32ScaleByFixedPointKernel::run_op(ITensorPack      &tensors,
                                                                const Window     &window,
                                                                cl::CommandQueue &queue)
{
    ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
    ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window);
 
    const auto src =
        utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC));
    const auto bias =
        utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_BIAS));
    auto dst = utils::cast::polymorphic_downcast<ICLTensor *>(tensors.get_tensor(TensorType::ACL_DST));
 
    // Create src window
    Window collapsed = window.collapse_if_possible(ICLKernel::window(), Window::DimZ);
    Window slice     = collapsed.first_slice_window_3D();
 
    // Setup bias slice
    unsigned int idx1 = num_arguments_per_3D_tensor();
    if (bias != nullptr)
    {
        Window biases_slice(slice);
        biases_slice.set(Window::DimY, Window::Dimension(0, 1, 1));
        biases_slice.set(Window::DimZ, Window::Dimension(0, 1, 1));
        add_1D_tensor_argument(idx1, bias, biases_slice);
    }
 
    do
    {
        unsigned int idx = 0;
        add_3D_tensor_argument(idx, src, slice);
        add_3D_tensor_argument(idx1, dst, slice);
        enqueue(queue, *this, slice, lws_hint());
    } while (collapsed.slide_window_slice_3D(slice));
}
} // namespace kernels
} // namespace opencl
} // namespace arm_compute