Make ClDirectConvolutionKernel stateless

ClDirectorConvolution triggers ClActivation (if enabled)

Remove static tuner as the interface need to be changed base on new api. Remove functions in ClScaleKernel specific for static Tuner.

Solves: COMPMID-4010

Signed-off-by: Sheri Zhang <sheri.zhang@arm.com>
Change-Id: I7861c3462fda323a6fe1891834068a462245cb1b
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/5262
Reviewed-by: Sang-Hoon Park <sang-hoon.park@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>

1 files changed, 0 insertions, 585 deletions

diff --git a/src/core/CL/kernels/CLDirectConvolutionLayerKernel.cpp b/src/core/CL/kernels/CLDirectConvolutionLayerKernel.cpp
deleted file mode 100644
index 2fc3c60f67..0000000000
--- a/src/core/CL/kernels/CLDirectConvolutionLayerKernel.cpp
+++ /dev/null
@@ -1,585 +0,0 @@
-/*
- * Copyright (c) 2017-2021 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/CLDirectConvolutionLayerKernel.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/Helpers.h"
-#include "arm_compute/core/ITensor.h"
-#include "arm_compute/core/PixelValue.h"
-#include "arm_compute/core/Utils.h"
-#include "arm_compute/core/utils/misc/ShapeCalculator.h"
-#include "arm_compute/core/utils/quantization/AsymmHelpers.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"
-
-namespace arm_compute
-{
-namespace
-{
-Status validate_arguments(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info)
-{
-    ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input);
-    ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8_SIGNED, DataType::QASYMM8, DataType::F16, DataType::F32);
-    ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights);
-
-    const DataLayout data_layout = input->data_layout();
-    const int        width_idx   = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH);
-    const int        height_idx  = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT);
-    const int        channel_idx = get_data_layout_dimension_index(data_layout, DataLayoutDimension::CHANNEL);
-
-    ARM_COMPUTE_RETURN_ERROR_ON_MSG(weights->dimension(width_idx) != weights->dimension(height_idx), "Weights should have same width and height");
-    ARM_COMPUTE_RETURN_ERROR_ON_MSG(weights->dimension(channel_idx) != input->dimension(channel_idx),
-                                    "Weights feature map dimension should match the respective input's one");
-    ARM_COMPUTE_RETURN_ERROR_ON_MSG(weights->num_dimensions() > 4, "Weights can be at most 4 dimensional");
-    ARM_COMPUTE_RETURN_ERROR_ON_MSG((weights->dimension(width_idx) == 1) && std::get<0>(conv_info.stride()) > 3, "Strides larger than 3 not supported for 1x1 convolution.");
-    ARM_COMPUTE_RETURN_ERROR_ON_MSG((weights->dimension(width_idx) == 3 || weights->dimension(width_idx) == 5 || weights->dimension(width_idx) == 9)
-                                    && std::get<0>(conv_info.stride()) > 2,
-                                    "Strides larger than 2 not supported for 3x3, 5x5, 9x9 convolution.");
-
-    if(data_layout == DataLayout::NCHW)
-    {
-        if(is_data_type_quantized(input->data_type()))
-        {
-            ARM_COMPUTE_RETURN_ERROR_ON_MSG(weights->dimension(width_idx) != 1 && weights->dimension(width_idx) != 3 && weights->dimension(width_idx) != 5 && weights->dimension(width_idx) != 9,
-                                            "Kernel sizes other than 1x1, 3x3, 5x5 or 9x9 are not supported with quantized data types");
-        }
-        else
-        {
-            ARM_COMPUTE_RETURN_ERROR_ON_MSG(weights->dimension(width_idx) != 1 && weights->dimension(width_idx) != 3 && weights->dimension(width_idx) != 5,
-                                            "Kernel sizes other than 1x1, 3x3 or 5x5 are not supported with float data types");
-        }
-    }
-
-    if(biases != nullptr)
-    {
-        if(is_data_type_quantized_asymmetric(input->data_type()))
-        {
-            ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(biases, 1, DataType::S32);
-        }
-        else
-        {
-            ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(weights, biases);
-        }
-        ARM_COMPUTE_RETURN_ERROR_ON_MSG(biases->dimension(0) != weights->dimension(3),
-                                        "Biases size and number of input feature maps should match");
-        ARM_COMPUTE_RETURN_ERROR_ON_MSG(biases->num_dimensions() > 1,
-                                        "Biases should be one dimensional");
-    }
-
-    // Checks performed when output is configured
-    if(output->total_size() != 0)
-    {
-        ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(),
-                                                           misc::shape_calculator::compute_deep_convolution_shape(*input, *weights, conv_info));
-        ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
-    }
-
-    const auto data_type = input->data_type();
-    if(is_data_type_quantized(data_type))
-    {
-        const UniformQuantizationInfo iqinfo = input->quantization_info().uniform();
-        const UniformQuantizationInfo wqinfo = weights->quantization_info().uniform();
-        const UniformQuantizationInfo oqinfo = output->quantization_info().uniform();
-
-        float multiplier        = iqinfo.scale * wqinfo.scale / oqinfo.scale;
-        int   output_multiplier = 0;
-        int   output_shift      = 0;
-        ARM_COMPUTE_RETURN_ON_ERROR(quantization::calculate_quantized_multiplier(multiplier, &output_multiplier, &output_shift));
-    }
-    return Status{};
-}
-
-inline bool can_run_optimized_kernel_for_bifrost_nchw(GPUTarget gpu_target, unsigned int conv_stride_x, unsigned int conv_stride_y, unsigned int kernel_size,
-                                                      DataType data_type, DataLayout data_layout)
-{
-    return gpu_target_is_in(gpu_target,
-                            GPUTarget::G71, GPUTarget::G72, GPUTarget::G76,
-                            GPUTarget::G51, GPUTarget::G51BIG, GPUTarget::G51LIT,
-                            GPUTarget::G52, GPUTarget::G52LIT)
-           && (kernel_size <= 5)
-           && (conv_stride_x == 1) && (conv_stride_y == 1)
-           && (data_type == DataType::F32)
-           && (data_layout == DataLayout::NCHW);
-}
-
-inline void setup_num_elems_nchw(unsigned int &num_elems_read_per_iteration_x, unsigned int &num_elems_read_per_iteration_y,
-                                 unsigned int &num_elems_written_per_iteration_x, unsigned int &num_elems_written_per_iteration_y,
-                                 unsigned int kernel_size, const PadStrideInfo &conv_info, const GPUTarget target, ITensorInfo *input)
-{
-    const DataType   data_type     = input->data_type();
-    const DataLayout data_layout   = input->data_layout();
-    unsigned int     conv_stride_x = std::get<0>(conv_info.stride());
-    unsigned int     conv_stride_y = std::get<1>(conv_info.stride());
-
-    const bool run_optimized_bifrost = can_run_optimized_kernel_for_bifrost_nchw(target, conv_stride_x, conv_stride_y, kernel_size, data_type, data_layout);
-
-    if(run_optimized_bifrost)
-    {
-        // Configure kernel window
-        switch(kernel_size)
-        {
-            case 1:
-            {
-                num_elems_read_per_iteration_x    = 4;
-                num_elems_read_per_iteration_y    = 4;
-                num_elems_written_per_iteration_x = 4;
-                num_elems_written_per_iteration_y = 4;
-                break;
-            }
-            case 3:
-            {
-                num_elems_read_per_iteration_x    = 6;
-                num_elems_read_per_iteration_y    = 5;
-                num_elems_written_per_iteration_x = 4;
-                num_elems_written_per_iteration_y = 3;
-                break;
-            }
-            case 5:
-            {
-                num_elems_read_per_iteration_x    = 8;
-                num_elems_read_per_iteration_y    = 6;
-                num_elems_written_per_iteration_x = 4;
-                num_elems_written_per_iteration_y = 2;
-                break;
-            }
-            default:
-            {
-                ARM_COMPUTE_ERROR("Kernel size not optimized for Bifrost");
-            }
-        }
-    }
-    else
-    {
-        num_elems_read_per_iteration_y    = kernel_size;
-        num_elems_written_per_iteration_x = 8;
-        num_elems_written_per_iteration_y = 1;
-        switch(kernel_size)
-        {
-            case 1:
-                switch(conv_stride_x)
-                {
-                    case 1:
-                        num_elems_read_per_iteration_x = 8;
-                        break;
-                    case 2:
-                        num_elems_read_per_iteration_x = 16;
-                        break;
-                    case 3:
-                        switch(input->element_size())
-                        {
-                            case 1:
-                                num_elems_read_per_iteration_x = 28;
-                                break;
-                            case 2:
-                                num_elems_read_per_iteration_x = 24;
-                                break;
-                            case 4:
-                                num_elems_read_per_iteration_x = 22;
-                                break;
-                            default:
-                                ARM_COMPUTE_ERROR("Invalid data size");
-                        }
-                        break;
-                    default:
-                        ARM_COMPUTE_ERROR("Invalid convolution stride X");
-                }
-                break;
-            case 3:
-                switch(conv_stride_x)
-                {
-                    case 1:
-                        num_elems_read_per_iteration_x = 10;
-                        break;
-                    case 2:
-                        num_elems_read_per_iteration_x = 17;
-                        break;
-                    default:
-                        ARM_COMPUTE_ERROR("Invalid convolution stride X");
-                }
-                break;
-            case 5:
-                switch(conv_stride_x)
-                {
-                    case 1:
-                        num_elems_read_per_iteration_x = 12;
-                        break;
-                    case 2:
-                        num_elems_read_per_iteration_x = 20;
-                        break;
-                    default:
-                        ARM_COMPUTE_ERROR("Invalid convolution stride X");
-                }
-                break;
-            case 9:
-                switch(conv_stride_x)
-                {
-                    case 1:
-                        num_elems_read_per_iteration_x = 16;
-                        break;
-                    case 2:
-                        num_elems_read_per_iteration_x = 24;
-                        break;
-                    default:
-                        ARM_COMPUTE_ERROR("Invalid convolution stride X");
-                }
-                break;
-            default:
-                ARM_COMPUTE_ERROR("Invalid direct convolution size");
-        }
-    }
-}
-
-std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *weights, ITensorInfo *output, const PadStrideInfo &conv_info, const GPUTarget target)
-{
-    const DataLayout data_layout = input->data_layout();
-
-    // Get output shape
-    TensorShape output_shape = misc::shape_calculator::compute_deep_convolution_shape(*input, *weights, conv_info);
-
-    // Output auto inizialitation if not yet initialized
-    auto_init_if_empty(*output, output_shape,
-                       1,
-                       input->data_type(),
-                       input->quantization_info());
-
-    if(data_layout == DataLayout::NHWC)
-    {
-        const unsigned int vec_size = std::min(static_cast<unsigned int>(output->tensor_shape()[0]), 4u);
-
-        // Create window and update padding
-        Window win = calculate_max_window(*output, Steps(vec_size, 1U));
-        output->set_valid_region(ValidRegion(Coordinates(), output->tensor_shape()));
-        Status err = Status{};
-        return std::make_pair(err, win);
-    }
-    else if(data_layout == DataLayout::NCHW)
-    {
-        const int          width_idx   = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH);
-        const unsigned int kernel_size = weights->dimension(width_idx);
-
-        unsigned int num_elems_read_per_iteration_x    = 0;
-        unsigned int num_elems_read_per_iteration_y    = 0;
-        unsigned int num_elems_written_per_iteration_x = 0;
-        unsigned int num_elems_written_per_iteration_y = 0;
-
-        unsigned int conv_pad_left = conv_info.pad_left();
-        unsigned int conv_pad_top  = conv_info.pad_top();
-        unsigned int conv_stride_x = std::get<0>(conv_info.stride());
-        unsigned int conv_stride_y = std::get<1>(conv_info.stride());
-
-        setup_num_elems_nchw(num_elems_read_per_iteration_x, num_elems_read_per_iteration_y,
-                             num_elems_written_per_iteration_x, num_elems_written_per_iteration_y,
-                             kernel_size, conv_info, target, input);
-
-        // Create window and update padding
-        bool   window_changed = false;
-        Window win            = calculate_max_window(*output, Steps(num_elems_written_per_iteration_x, num_elems_written_per_iteration_y));
-
-        AccessWindowRectangle input_access(input, -conv_pad_left, -conv_pad_top, num_elems_read_per_iteration_x, num_elems_read_per_iteration_y, conv_stride_x, conv_stride_y);
-        AccessWindowStatic    weights_access(weights, 0, 0, kernel_size, kernel_size);
-        AccessWindowRectangle output_access(output, 0, 0, num_elems_written_per_iteration_x, num_elems_written_per_iteration_y);
-        window_changed = update_window_and_padding(win, input_access, weights_access, output_access);
-        output_access.set_valid_region(win, ValidRegion(Coordinates(), output->tensor_shape()));
-        Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{};
-        return std::make_pair(err, win);
-    }
-    else
-    {
-        ARM_COMPUTE_ERROR("Not supported");
-    }
-}
-} // namespace
-
-CLDirectConvolutionLayerKernel::CLDirectConvolutionLayerKernel()
-    : _input(nullptr), _biases(nullptr), _weights(nullptr), _output(nullptr), _data_layout(DataLayout::UNKNOWN), _border_size(0), _conv_stride_x(0), _conv_stride_y(0), _conv_info()
-{
-}
-
-BorderSize CLDirectConvolutionLayerKernel::border_size() const
-{
-    return _border_size;
-}
-
-void CLDirectConvolutionLayerKernel::configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info)
-{
-    configure(CLKernelLibrary::get().get_compile_context(), input, weights, biases, output, conv_info);
-}
-
-void CLDirectConvolutionLayerKernel::configure(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output,
-                                               const PadStrideInfo &conv_info)
-{
-    ARM_COMPUTE_ERROR_ON_NULLPTR(input, weights, output);
-
-    // Perform validation
-    ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(),
-                                                  weights->info(),
-                                                  (biases != nullptr) ? biases->info() : nullptr,
-                                                  output->info(),
-                                                  conv_info));
-
-    _conv_stride_x = std::get<0>(conv_info.stride());
-    _conv_stride_y = std::get<1>(conv_info.stride());
-    _data_layout   = input->info()->data_layout();
-    _input         = input;
-    _weights       = weights;
-    _output        = output;
-    _biases        = biases;
-    _conv_info     = conv_info;
-
-    const unsigned int width_idx   = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::WIDTH);
-    const unsigned int height_idx  = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::HEIGHT);
-    const unsigned int channel_idx = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::CHANNEL);
-    const unsigned int kernel_size = weights->info()->dimension(width_idx);
-    const DataType     data_type   = input->info()->data_type();
-
-    const GPUTarget gpu_target = get_target();
-
-    // Configure kernel window
-    auto win_config = validate_and_configure_window(input->info(), weights->info(), output->info(), conv_info, gpu_target);
-    ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
-    ICLKernel::configure_internal(win_config.second);
-
-    std::stringstream kernel_name;
-    CLBuildOptions    build_options;
-
-    if(_data_layout == DataLayout::NHWC)
-    {
-        _border_size = BorderSize();
-
-        kernel_name << "direct_convolution_nhwc";
-
-        const unsigned int n0               = win_config.second.x().step();
-        const unsigned int m0               = win_config.second.y().step();
-        const unsigned int k0               = adjust_vec_size(16u, _input->info()->dimension(channel_idx));
-        const unsigned int partial_store_n0 = _output->info()->dimension(channel_idx) % n0;
-        const unsigned int partial_store_m0 = (_output->info()->dimension(width_idx) * _output->info()->dimension(height_idx)) % m0;
-        const unsigned int pad_left         = conv_info.pad_left();
-        const unsigned int pad_top          = conv_info.pad_top();
-
-        if(_biases != nullptr)
-        {
-            build_options.add_option(std::string("-DHAS_BIAS"));
-            build_options.add_option(std::string("-DBIA_DATA_TYPE=" + get_cl_type_from_data_type(_biases->info()->data_type())));
-        }
-        build_options.add_option("-DSRC_WIDTH=" + support::cpp11::to_string(_input->info()->dimension(width_idx)));
-        build_options.add_option("-DSRC_HEIGHT=" + support::cpp11::to_string(_input->info()->dimension(height_idx)));
-        build_options.add_option("-DSRC_CHANNELS=" + support::cpp11::to_string(_input->info()->dimension(channel_idx)));
-        build_options.add_option("-DSRC_DATA_TYPE=" + get_cl_type_from_data_type(_input->info()->data_type()));
-        build_options.add_option("-DDST_WIDTH=" + support::cpp11::to_string(_output->info()->dimension(width_idx)));
-        build_options.add_option("-DDST_HEIGHT=" + support::cpp11::to_string(_output->info()->dimension(height_idx)));
-        build_options.add_option("-DDST_CHANNELS=" + support::cpp11::to_string(_output->info()->dimension(channel_idx)));
-        build_options.add_option("-DDST_DATA_TYPE=" + get_cl_type_from_data_type(_output->info()->data_type()));
-        build_options.add_option("-DWEI_WIDTH=" + support::cpp11::to_string(_weights->info()->dimension(width_idx)));
-        build_options.add_option("-DWEI_HEIGHT=" + support::cpp11::to_string(_weights->info()->dimension(height_idx)));
-        build_options.add_option("-DWEI_DATA_TYPE=" + get_cl_type_from_data_type(_weights->info()->data_type()));
-        build_options.add_option("-DSTRIDE_X=" + support::cpp11::to_string(_conv_stride_x));
-        build_options.add_option("-DSTRIDE_Y=" + support::cpp11::to_string(_conv_stride_y));
-        build_options.add_option("-DPAD_LEFT=" + support::cpp11::to_string(pad_left));
-        build_options.add_option("-DPAD_TOP=" + support::cpp11::to_string(pad_top));
-        build_options.add_option("-DN0=" + support::cpp11::to_string(n0));
-        build_options.add_option("-DM0=" + support::cpp11::to_string(m0));
-        build_options.add_option("-DK0=" + support::cpp11::to_string(k0));
-        build_options.add_option("-DPARTIAL_STORE_N0=" + support::cpp11::to_string(partial_store_n0));
-        build_options.add_option("-DPARTIAL_STORE_M0=" + support::cpp11::to_string(partial_store_m0));
-
-        if(is_data_type_quantized(data_type))
-        {
-            const UniformQuantizationInfo iqinfo = _input->info()->quantization_info().uniform();
-            const UniformQuantizationInfo wqinfo = _weights->info()->quantization_info().uniform();
-            const UniformQuantizationInfo oqinfo = _output->info()->quantization_info().uniform();
-
-            PixelValue zero_value = PixelValue(0, input->info()->data_type(), input->info()->quantization_info());
-            int        zero_value_s32;
-            zero_value.get(zero_value_s32);
-
-            float multiplier        = iqinfo.scale * wqinfo.scale / oqinfo.scale;
-            int   output_multiplier = 0;
-            int   output_shift      = 0;
-            quantization::calculate_quantized_multiplier(multiplier, &output_multiplier, &output_shift);
-            build_options.add_option("-DIS_QUANTIZED");
-            build_options.add_option("-DDST_MULTIPLIER=" + support::cpp11::to_string(output_multiplier));
-            build_options.add_option("-DDST_SHIFT=" + support::cpp11::to_string(output_shift));
-            build_options.add_option("-DSRC_OFFSET=" + support::cpp11::to_string(-iqinfo.offset));
-            build_options.add_option("-DWEI_OFFSET=" + support::cpp11::to_string(-wqinfo.offset));
-            build_options.add_option("-DDST_OFFSET=" + support::cpp11::to_string(oqinfo.offset));
-            build_options.add_option("-DZERO_VALUE=" + support::cpp11::to_string(zero_value_s32));
-            build_options.add_option("-DACC_DATA_TYPE=" + get_cl_type_from_data_type(DataType::S32));
-        }
-        else
-        {
-            build_options.add_option("-DACC_DATA_TYPE=" + get_cl_type_from_data_type(data_type));
-            build_options.add_option("-DSRC_OFFSET=" + support::cpp11::to_string(0));
-            build_options.add_option("-DWEI_OFFSET=" + support::cpp11::to_string(0));
-            build_options.add_option("-DDST_OFFSET=" + support::cpp11::to_string(0));
-        }
-    }
-    else
-    {
-        _border_size = BorderSize(_input->info()->padding());
-
-        kernel_name << "direct_convolution" << kernel_size << "x" << kernel_size;
-
-        build_options.add_option_if(_biases != nullptr, std::string("-DHAS_BIAS"));
-
-        const bool run_optimized_for_bifrost = can_run_optimized_kernel_for_bifrost_nchw(gpu_target, _conv_stride_x, _conv_stride_y, kernel_size, data_type, _data_layout);
-
-        if(run_optimized_for_bifrost)
-        {
-            build_options.add_option(std::string("-DWEIGHTS_DEPTH=" + support::cpp11::to_string(_weights->info()->dimension(channel_idx))));
-
-            kernel_name << "_f32_bifrost";
-        }
-        else
-        {
-            build_options.add_option(std::string("-DDATA_TYPE=" + get_cl_type_from_data_type(data_type)));
-            build_options.add_option(std::string("-DDATA_SIZE=" + get_data_size_from_data_type(data_type)));
-            build_options.add_option(std::string("-DWEIGHTS_DEPTH=" + support::cpp11::to_string(_weights->info()->dimension(channel_idx))));
-            build_options.add_option(std::string("-DSTRIDE_X=" + support::cpp11::to_string(_conv_stride_x)));
-            build_options.add_option(std::string("-DDATA_TYPE_PROMOTED=" + get_cl_type_from_data_type(data_type)));
-
-            if(is_data_type_quantized(data_type))
-            {
-                const UniformQuantizationInfo iqinfo = _input->info()->quantization_info().uniform();
-                const UniformQuantizationInfo wqinfo = _weights->info()->quantization_info().uniform();
-                const UniformQuantizationInfo oqinfo = _output->info()->quantization_info().uniform();
-
-                float multiplier        = iqinfo.scale * wqinfo.scale / oqinfo.scale;
-                int   output_multiplier = 0;
-                int   output_shift      = 0;
-                quantization::calculate_quantized_multiplier(multiplier, &output_multiplier, &output_shift);
-                build_options.add_option("-DOUTPUT_MULTIPLIER=" + support::cpp11::to_string(output_multiplier));
-                build_options.add_option("-DOUTPUT_SHIFT=" + support::cpp11::to_string(output_shift));
-                build_options.add_option("-DKERNEL_SIZE=" + support::cpp11::to_string(kernel_size));
-                build_options.add_option("-DINPUT_OFFSET=" + support::cpp11::to_string(-iqinfo.offset));
-                build_options.add_option("-DWEIGHTS_OFFSET=" + support::cpp11::to_string(-wqinfo.offset));
-                build_options.add_option("-DOUTPUT_OFFSET=" + support::cpp11::to_string(oqinfo.offset));
-
-                kernel_name.str("direct_convolution_quantized");
-            }
-        }
-    }
-
-    _kernel = create_kernel(compile_context, kernel_name.str(), build_options.options());
-
-    // Set config_id for enabling LWS tuning
-    _config_id = kernel_name.str();
-    _config_id += "_";
-    _config_id += lower_string(string_from_data_type(data_type));
-    _config_id += "_";
-    _config_id += support::cpp11::to_string(kernel_size);
-    _config_id += "_";
-    _config_id += support::cpp11::to_string(border_size().left);
-    _config_id += "_";
-    _config_id += support::cpp11::to_string(border_size().top);
-    _config_id += "_";
-    _config_id += support::cpp11::to_string(border_size().right);
-    _config_id += "_";
-    _config_id += support::cpp11::to_string(border_size().bottom);
-    _config_id += "_";
-    _config_id += support::cpp11::to_string(_conv_stride_x);
-    _config_id += "_";
-    _config_id += support::cpp11::to_string(_conv_stride_y);
-    _config_id += "_";
-    _config_id += support::cpp11::to_string(output->info()->dimension(width_idx));
-    _config_id += "_";
-    _config_id += support::cpp11::to_string(output->info()->dimension(height_idx));
-    _config_id += "_";
-    _config_id += lower_string(string_from_data_layout(_data_layout));
-}
-
-Status CLDirectConvolutionLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info,
-                                                const GPUTarget target)
-{
-    ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, weights, biases, output, conv_info));
-    ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), weights->clone().get(), output->clone().get(), conv_info, target).first);
-
-    return Status{};
-}
-
-void CLDirectConvolutionLayerKernel::run(const Window &window, cl::CommandQueue &queue)
-{
-    ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
-    ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window);
-
-    // Get initial windows
-    Window slice = window.first_slice_window_3D();
-
-    if(_data_layout == DataLayout::NHWC)
-    {
-        slice.set(Window::DimY, Window::Dimension(0, _output->info()->dimension(1) * _output->info()->dimension(2), 1));
-        slice.set(Window::DimZ, Window::Dimension(0, _output->info()->dimension(3), 1));
-
-        unsigned int idx = 0;
-        add_3D_tensor_argument(idx, _input, slice);
-        add_3D_tensor_argument(idx, _output, slice);
-        add_3D_tensor_argument(idx, _weights, slice);
-        if(_biases != nullptr)
-        {
-            add_1D_tensor_argument(idx, _biases, slice);
-        }
-        _kernel.setArg(idx++, static_cast<unsigned int>(_weights->info()->strides_in_bytes()[3]));
-        enqueue(queue, *this, slice, lws_hint());
-    }
-    else
-    {
-        Window win_in = window;
-
-        win_in.adjust(Window::DimX, -_conv_info.pad_left(), true);
-        win_in.adjust(Window::DimY, -_conv_info.pad_top(), true);
-
-        const int width_idx  = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::WIDTH);
-        const int height_idx = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::HEIGHT);
-
-        win_in.set_dimension_step(width_idx, window[width_idx].step() * _conv_stride_x);
-        win_in.set_dimension_step(height_idx, window[height_idx].step() * _conv_stride_y);
-
-        Window       slice_in = win_in.first_slice_window_3D();
-        unsigned int idx1     = 2 * num_arguments_per_3D_tensor();
-        add_3D_tensor_argument(idx1, _weights, slice);
-
-        if(_biases != nullptr)
-        {
-            Window slice_biases;
-            slice_biases.use_tensor_dimensions(_biases->info()->tensor_shape());
-            add_1D_tensor_argument(idx1, _biases, slice_biases);
-        }
-
-        _kernel.setArg(idx1++, static_cast<unsigned int>(_weights->info()->strides_in_bytes()[3]));
-
-        do
-        {
-            unsigned int idx = 0;
-            add_3D_tensor_argument(idx, _input, slice_in);
-            add_3D_tensor_argument(idx, _output, slice);
-            enqueue(queue, *this, slice, lws_hint());
-        }
-        while(window.slide_window_slice_3D(slice) && win_in.slide_window_slice_3D(slice_in));
-    }
-}
-} // namespace arm_compute