diff options
Diffstat (limited to 'src/core/CL/kernels/CLDirectConvolutionLayerKernel.cpp')
| -rw-r--r-- | src/core/CL/kernels/CLDirectConvolutionLayerKernel.cpp | 638 |
1 files changed, 0 insertions, 638 deletions
diff --git a/src/core/CL/kernels/CLDirectConvolutionLayerKernel.cpp b/src/core/CL/kernels/CLDirectConvolutionLayerKernel.cpp deleted file mode 100644 index 2fcc82fbd3..0000000000 --- a/src/core/CL/kernels/CLDirectConvolutionLayerKernel.cpp +++ /dev/null @@ -1,638 +0,0 @@ -/* - * Copyright (c) 2017-2020 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 "arm_compute/core/CL/kernels/CLDirectConvolutionLayerKernel.h" - -#include "arm_compute/core/AccessWindowStatic.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/IAccessWindow.h" -#include "arm_compute/core/ITensor.h" -#include "arm_compute/core/Types.h" -#include "arm_compute/core/Utils.h" -#include "arm_compute/core/utils/misc/ShapeCalculator.h" -#include "arm_compute/core/utils/quantization/AsymmHelpers.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(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"); - 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) && std::get<0>(conv_info.stride()) > 2, - "Strides larger than 2 not supported for 3x3 convolution."); - - const auto data_type = input->data_type(); - - if(weights->dimension(width_idx) == 9) - { - const auto supported_data_layout = is_data_type_quantized(data_type) ? DataLayout::NCHW : DataLayout::NHWC; - const auto error_message = std::string("Only " + string_from_data_layout(supported_data_layout) + " layout is supported for 9x9 convolution with " + string_from_data_type( - data_type) - + " type"); - - ARM_COMPUTE_RETURN_ERROR_ON_MSG((supported_data_layout != data_layout), error_message.c_str()); - } - - 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); - } - - 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(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 bool can_run_optimized_kernel_for_bifrost_nhwc(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 == 9) - && (conv_stride_x == 1) && (conv_stride_y == 1) - && (data_type == DataType::F32) - && (data_layout == DataLayout::NHWC); -} - -inline void setup_num_elems(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(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 if(data_layout == DataLayout::NCHW) - { - 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"); - } - } - else // data_layout == NHWC - { - const bool run_optimized_bifrost_nhwc = can_run_optimized_kernel_for_bifrost_nhwc(target, conv_stride_x, conv_stride_y, kernel_size, data_type, data_layout); - - num_elems_written_per_iteration_x = 1; - - if(run_optimized_bifrost_nhwc) - { - num_elems_read_per_iteration_x = 4; - } - else - { - num_elems_read_per_iteration_x = 1; - } - - switch(kernel_size) - { - case 1: - switch(conv_stride_x) - { - case 1: - num_elems_read_per_iteration_y = 8; - num_elems_written_per_iteration_y = 8; - break; - case 2: - num_elems_read_per_iteration_y = 16; - num_elems_written_per_iteration_y = 8; - break; - default: - ARM_COMPUTE_ERROR("Invalid convolution stride X"); - } - break; - case 3: - switch(conv_stride_x) - { - case 1: - num_elems_read_per_iteration_y = 10; - num_elems_written_per_iteration_y = 8; - break; - case 2: - num_elems_read_per_iteration_y = 17; - num_elems_written_per_iteration_y = 8; - break; - default: - ARM_COMPUTE_ERROR("Invalid convolution stride X"); - } - break; - case 5: - switch(conv_stride_x) - { - case 1: - num_elems_read_per_iteration_y = 12; - num_elems_written_per_iteration_y = 8; - break; - case 2: - num_elems_read_per_iteration_y = 20; - num_elems_written_per_iteration_y = 8; - break; - default: - ARM_COMPUTE_ERROR("Invalid convolution stride X"); - } - break; - case 9: - switch(conv_stride_x) - { - case 1: - num_elems_read_per_iteration_y = 16; - num_elems_written_per_iteration_y = 8; - break; - case 2: - num_elems_read_per_iteration_y = 24; - num_elems_written_per_iteration_y = 8; - break; - default: - ARM_COMPUTE_ERROR("Invalid convolution stride X"); - } - break; - default: - ARM_COMPUTE_ERROR("Not implemented."); - break; - } - } -} - -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(); - const int width_idx = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH); - const unsigned int kernel_size = weights->dimension(width_idx); - - // Get convolved dimensions - TensorShape output_shape = misc::shape_calculator::compute_deep_convolution_shape(*input, *weights, conv_info); - - // Output auto inizialitation if not yet initialized - // TODO(COMPMID-2078): input->clone()->set_tensor_shape(output_shape) doesn't work with subtensors for grouped direct convolutions (AlexNet). - auto_init_if_empty(*output, output_shape, - 1, - input->data_type(), - input->quantization_info()); - - 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(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)); - - if(data_layout == DataLayout::NHWC) - { - AccessWindowStatic input_access(input, 0, -conv_pad_left, - ceil_to_multiple(input->dimension(0), num_elems_read_per_iteration_x), - ceil_to_multiple(input->dimension(1) + conv_info.pad_right(), num_elems_read_per_iteration_y)); - AccessWindowStatic weights_access(weights, 0, 0, weights->dimension(0), weights->dimension(1)); - 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 if(data_layout == DataLayout::NCHW) - { - 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) -{ -} - -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); - - _data_layout = input->info()->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); - - const unsigned int kernel_size = weights->info()->dimension(width_idx); - const DataType data_type = input->info()->data_type(); - - // Get convolved dimensions - TensorShape output_shape = misc::shape_calculator::compute_deep_convolution_shape(*input->info(), *weights->info(), conv_info); - - // Output auto inizialitation if not yet initialized - // TODO(COMPMID-2078): input->clone()->set_tensor_shape(output_shape) doesn't work with subtensors for grouped direct convolutions (AlexNet). - auto_init_if_empty(*output->info(), - output_shape, - 1, - input->info()->data_type(), - input->info()->quantization_info()); - - // Perform validation step - 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()); - - if(_data_layout == DataLayout::NHWC) - { - _border_size = BorderSize(conv_info.pad_left(), 0, conv_info.pad_right(), 0); - } - else if(_data_layout == DataLayout::NCHW) - { - _border_size = BorderSize(conv_info.pad_top(), conv_info.pad_right(), conv_info.pad_bottom(), conv_info.pad_left()); - } - else - { - ARM_COMPUTE_ERROR("Not supported"); - } - - _input = input; - _weights = weights; - _output = output; - _biases = biases; - - const GPUTarget gpu_target = get_target(); - - std::stringstream kernel_name; - kernel_name << "direct_convolution" << kernel_size << "x" << kernel_size; - if(_data_layout == DataLayout::NHWC) - { - kernel_name << "_" << lower_string(string_from_data_layout(_data_layout)); - } - - CLBuildOptions build_options; - build_options.add_option_if(_biases != nullptr, std::string("-DHAS_BIAS")); - - const bool run_optimized_for_bifrost = can_run_optimized_kernel_for_bifrost(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"; - _kernel = create_kernel(compile_context, kernel_name.str(), build_options.options()); - } - 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))); - if(_data_layout == DataLayout::NHWC) - { - const bool run_optimized_for_bifrost_nhwc = can_run_optimized_kernel_for_bifrost_nhwc(gpu_target, _conv_stride_x, _conv_stride_y, kernel_size, data_type, _data_layout); - build_options.add_option(std::string("-DDATA_LAYOUT_NHWC=1")); - build_options.add_option(std::string("-DDST_HEIGHT=" + support::cpp11::to_string(_output->info()->dimension(height_idx)))); - build_options.add_option(std::string("-DDST_WIDTH=" + support::cpp11::to_string(_output->info()->dimension(width_idx)))); - build_options.add_option(std::string("-DSRC_HEIGHT=" + support::cpp11::to_string(_input->info()->dimension(height_idx)))); - build_options.add_option(std::string("-DSRC_WIDTH=" + support::cpp11::to_string(_input->info()->dimension(width_idx)))); - build_options.add_option(std::string("-DPAD_LEFT=" + support::cpp11::to_string(conv_info.pad_left()))); - build_options.add_option(std::string("-DPAD_TOP=" + support::cpp11::to_string(conv_info.pad_top()))); - build_options.add_option(std::string("-DPAD_BOTTOM=" + support::cpp11::to_string(conv_info.pad_bottom()))); - build_options.add_option(std::string("-DSTRIDE_Y=" + support::cpp11::to_string(_conv_stride_y))); - if(run_optimized_for_bifrost_nhwc) - { - const unsigned int num_elems_read_per_iteration_x = 4; - _border_size.right = num_elems_read_per_iteration_x; - build_options.add_option("-DVEC_SIZE=" + support::cpp11::to_string(num_elems_read_per_iteration_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)); - - // Create kernel - _kernel = create_kernel(compile_context, "direct_convolution_quantized", build_options.options()); - - // Set static kernel arguments - unsigned int idx = 3 * num_arguments_per_3D_tensor() + ((_biases != nullptr) ? num_arguments_per_1D_tensor() : 0) + 1; - _kernel.setArg(idx++, -iqinfo.offset); - _kernel.setArg(idx++, -wqinfo.offset); - _kernel.setArg(idx++, oqinfo.offset); - } - else - { - // Create kernel - _kernel = create_kernel(compile_context, kernel_name.str(), build_options.options()); - } - } - - // 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); - - // Set config_id for enabling LWS tuning - _config_id = "direct_convolution_"; - _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(); - Window win_in = window; - - win_in.adjust(Window::DimX, -_border_size.left, true); - win_in.adjust(Window::DimY, -_border_size.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 |