| /* |
| * 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/CLNormalizationLayerKernel.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/TensorInfo.h" |
| #include "arm_compute/core/Utils.h" |
| #include "arm_compute/core/Window.h" |
| #include "src/core/AccessWindowStatic.h" |
| #include "src/core/CL/CLValidate.h" |
| #include "src/core/helpers/AutoConfiguration.h" |
| #include "src/core/helpers/NormalizationHelpers.h" |
| #include "src/core/helpers/WindowHelpers.h" |
| #include "support/StringSupport.h" |
| |
| using namespace arm_compute; |
| |
| namespace |
| { |
| constexpr unsigned int num_elems_processed_per_iteration = 4; |
| Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, NormalizationLayerInfo norm_info) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input); |
| ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32); |
| ARM_COMPUTE_RETURN_ERROR_ON_DATA_LAYOUT_NOT_IN(input, DataLayout::NCHW, DataLayout::NHWC); |
| ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(output); |
| |
| ARM_COMPUTE_RETURN_ERROR_ON_MSG(!(norm_info.norm_size() % 2), "Normalization size should be odd"); |
| |
| // Checks performed when output is configured |
| if(output->total_size() != 0) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(input, output); |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output); |
| } |
| |
| return Status{}; |
| } |
| |
| std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *output, NormalizationLayerInfo norm_info) |
| { |
| // Output tensor auto initialization if not yet initialized |
| auto_init_if_empty(*output, *input->clone()); |
| |
| const unsigned int norm_idx = get_normalization_dimension_index(input->data_layout(), norm_info); |
| const bool is_norm_accross_width = norm_idx == 0; |
| |
| const unsigned int border_width = is_norm_accross_width ? num_elems_processed_per_iteration - 1 : 0; |
| const BorderSize border_size = BorderSize(0, border_width); |
| |
| Window win = calculate_max_window(*input, Steps(num_elems_processed_per_iteration)); |
| bool window_changed = false; |
| |
| // We do not use a Rectangle window for IN_MAP_2D as we clamp the top and bottom accesses inside the kernel, avoiding padding |
| // Reads can occur within the valid region of the input |
| if(is_norm_accross_width) |
| { |
| AccessWindowStatic input_access(input, -border_size.left, 0, input->dimension(0) + border_size.right, 0); |
| window_changed = window_changed || update_window_and_padding(win, input_access); |
| } |
| else |
| { |
| AccessWindowHorizontal input_access(input, -border_size.left, num_elems_processed_per_iteration); |
| window_changed = window_changed || update_window_and_padding(win, input_access); |
| } |
| |
| AccessWindowHorizontal output_access(output, 0, num_elems_processed_per_iteration); |
| window_changed = window_changed || update_window_and_padding(win, output_access); |
| output_access.set_valid_region(win, input->valid_region()); |
| |
| Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{}; |
| return std::make_pair(err, win); |
| } |
| } // namespace |
| |
| CLNormalizationLayerKernel::CLNormalizationLayerKernel() |
| : _input(nullptr), _output(nullptr), _border_size(0), _is_norm_across_width(false) |
| { |
| } |
| |
| BorderSize CLNormalizationLayerKernel::border_size() const |
| { |
| return _border_size; |
| } |
| |
| void CLNormalizationLayerKernel::configure(const ICLTensor *input, ICLTensor *output, NormalizationLayerInfo norm_info) |
| { |
| configure(CLKernelLibrary::get().get_compile_context(), input, output, norm_info); |
| } |
| |
| void CLNormalizationLayerKernel::configure(const CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, NormalizationLayerInfo norm_info) |
| { |
| ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); |
| |
| // Output tensor auto initialization if not yet initialized |
| auto_init_if_empty(*output->info(), *input->info()->clone()); |
| |
| // Perform validation step |
| ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), norm_info)); |
| |
| _input = input; |
| _output = output; |
| |
| const DataLayout data_layout = input->info()->data_layout(); |
| const unsigned int norm_idx = get_normalization_dimension_index(data_layout, norm_info); |
| _is_norm_across_width = norm_idx == 0; |
| const unsigned int border_width = _is_norm_across_width ? num_elems_processed_per_iteration - 1 : 0; |
| _border_size = BorderSize(0, border_width); |
| |
| const bool is_in_map_2D = (norm_info.type() == NormType::IN_MAP_2D); |
| |
| // Set build options |
| CLBuildOptions build_opts; |
| build_opts.add_option(("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type()))); |
| build_opts.add_option(("-DCOEFF=" + float_to_string_with_full_precision(norm_info.scale_coeff()))); |
| build_opts.add_option(("-DBETA=" + float_to_string_with_full_precision(norm_info.beta()))); |
| build_opts.add_option(("-DKAPPA=" + float_to_string_with_full_precision(norm_info.kappa()))); |
| build_opts.add_option(("-DVEC_SIZE=" + support::cpp11::to_string(num_elems_processed_per_iteration))); |
| build_opts.add_option(("-DRADIUS=" + support::cpp11::to_string(norm_info.norm_size() / 2))); |
| build_opts.add_option(("-DNUM_SLICES=" + support::cpp11::to_string(input->info()->dimension(2)))); |
| build_opts.add_option_if(is_in_map_2D, "-DIN_MAP_2D"); |
| build_opts.add_option_if(norm_info.is_in_map() || (data_layout == DataLayout::NHWC && norm_info.is_cross_map()), "-DWIDTH_SIZE=" + support::cpp11::to_string(input->info()->dimension(0))); |
| |
| // Create kernel |
| std::string kernel_name; |
| if(norm_info.is_in_map()) |
| { |
| kernel_name = "normalization_layer_in_map_" + lower_string(string_from_data_layout(data_layout)); |
| } |
| else |
| { |
| if(data_layout == DataLayout::NCHW) |
| { |
| kernel_name = "normalization_layer_cross_map"; |
| } |
| else |
| { |
| // 1D Cross-Map normalization in NHWC is the same as 1D In-Map normalization in NCHW |
| kernel_name = "normalization_layer_in_map_nchw"; |
| } |
| } |
| _kernel = create_kernel(compile_context, kernel_name, build_opts.options()); |
| |
| // Configure kernel window |
| auto win_config = validate_and_configure_window(input->info(), output->info(), norm_info); |
| ARM_COMPUTE_ERROR_THROW_ON(win_config.first); |
| ICLKernel::configure_internal(win_config.second); |
| |
| // Set config_id for enabling LWS tuning |
| _config_id = "normalization_layer_"; |
| _config_id += lower_string(string_from_data_type(input->info()->data_type())); |
| _config_id += "_"; |
| _config_id += support::cpp11::to_string(static_cast<std::underlying_type<NormType>::type>(norm_info.type())); |
| _config_id += "_"; |
| _config_id += support::cpp11::to_string(norm_info.norm_size()); |
| _config_id += "_"; |
| _config_id += support::cpp11::to_string(input->info()->dimension(0)); |
| _config_id += "_"; |
| _config_id += support::cpp11::to_string(input->info()->dimension(1)); |
| } |
| |
| Status CLNormalizationLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *output, NormalizationLayerInfo norm_info) |
| { |
| ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, norm_info)); |
| ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), output->clone().get(), norm_info).first); |
| |
| return Status{}; |
| } |
| |
| void CLNormalizationLayerKernel::run(const Window &window, cl::CommandQueue &queue) |
| { |
| ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); |
| ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window); |
| |
| const int collapsed_dimension = _is_norm_across_width ? Window::DimZ : 4; |
| Window window_collapsed = window.collapse_if_possible(ICLKernel::window(), collapsed_dimension); |
| Window slice = window_collapsed.first_slice_window_3D(); |
| |
| 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)); |
| } |