/* * 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/CLL2NormalizeLayerKernel.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/Helpers.h" #include "arm_compute/core/TensorInfo.h" #include "arm_compute/core/Utils.h" #include "arm_compute/core/Validate.h" #include "arm_compute/core/Window.h" #include "support/StringSupport.h" namespace arm_compute { namespace { constexpr int max_input_tensor_dim = 3; constexpr unsigned int num_elems_processed_per_iteration = 16; Status validate_arguments(const ITensorInfo *input, const ITensorInfo *sum, const ITensorInfo *output, int axis, float epsilon) { ARM_COMPUTE_UNUSED(epsilon); const uint32_t actual_axis = wrap_around(axis, max_input_tensor_dim); ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, sum, output); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, sum); 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_MSG(actual_axis > 2, "Actual axis greater than 2 is not supported"); ARM_COMPUTE_RETURN_ERROR_ON_MSG(actual_axis >= TensorShape::num_max_dimensions, "Actual normalization axis greater than max number of dimensions"); // Reduce shape on axis TensorShape sum_shape = input->tensor_shape(); sum_shape.set(actual_axis, 1); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(sum->tensor_shape(), sum_shape); if(output->total_size() != 0) { ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(input, output); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(input->tensor_shape(), output->tensor_shape()); } return Status{}; } std::tuple validate_and_configure_window(ITensorInfo *input, ITensorInfo *output) { Window win = calculate_max_window(*input, Steps(num_elems_processed_per_iteration)); // Output tensor auto initialization if not yet initialized auto_init_if_empty(*output, input->tensor_shape(), 1, input->data_type()); AccessWindowHorizontal input_access(input, 0, num_elems_processed_per_iteration); AccessWindowHorizontal output_access(output, 0, num_elems_processed_per_iteration); bool window_changed = update_window_and_padding(win, input_access, 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_tuple(err, win); } } // namespace CLL2NormalizeLayerKernel::CLL2NormalizeLayerKernel() : _input(nullptr), _sum(nullptr), _output(nullptr), _actual_axis(0), _epsilon(1e-12) { } void CLL2NormalizeLayerKernel::configure(const ICLTensor *input, const ICLTensor *sum, ICLTensor *output, int axis, float epsilon) { configure(CLKernelLibrary::get().get_compile_context(), input, sum, output, axis, epsilon); } void CLL2NormalizeLayerKernel::configure(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *sum, ICLTensor *output, int axis, float epsilon) { ARM_COMPUTE_ERROR_ON_NULLPTR(input, sum, output); ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), sum->info(), output->info(), axis, epsilon)); _input = input; _sum = sum; _output = output; _actual_axis = wrap_around(axis, max_input_tensor_dim); _epsilon = epsilon; // Set build options std::set build_opts; build_opts.emplace(("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type()))); build_opts.emplace(("-DVEC_SIZE=" + support::cpp11::to_string(num_elems_processed_per_iteration))); // Create kernel std::string kernel_name; unsigned int idx = 0; switch(_actual_axis) { case 0: kernel_name = "x"; idx = num_arguments_per_2D_tensor() * 3; break; case 1: kernel_name = "y"; idx = num_arguments_per_2D_tensor() * 3; break; case 2: kernel_name = "z"; idx = num_arguments_per_3D_tensor() * 3; break; default: ARM_COMPUTE_ERROR("Axis not supported"); } _kernel = create_kernel(compile_context, "l2_normalize_" + kernel_name, build_opts); // Set epsilon argument if(input->info()->data_type() == DataType::F32) { _kernel.setArg(idx, _epsilon); } else { _kernel.setArg(idx, _epsilon); } // Configure kernel window auto win_config = validate_and_configure_window(_input->info(), _output->info()); ARM_COMPUTE_ERROR_THROW_ON(std::get<0>(win_config)); ICLKernel::configure_internal(std::get<1>(win_config)); } Status CLL2NormalizeLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *sum, const ITensorInfo *output, int axis, float epsilon) { ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, sum, output, axis, epsilon)); ARM_COMPUTE_RETURN_ON_ERROR(std::get<0>(validate_and_configure_window(input->clone().get(), output->clone().get()))); return Status{}; } void CLL2NormalizeLayerKernel::run(const Window &window, cl::CommandQueue &queue) { ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window); Window window_sum(window); switch(_actual_axis) { case 0: { window_sum.set(Window::DimX, Window::Dimension(0, 0, 0)); Window in_slice = window.first_slice_window_2D(); Window sum_slice = window_sum.first_slice_window_2D(); do { unsigned int idx = 0; add_2D_tensor_argument(idx, _input, in_slice); add_2D_tensor_argument(idx, _sum, sum_slice); add_2D_tensor_argument(idx, _output, in_slice); enqueue(queue, *this, in_slice, lws_hint()); } while(window.slide_window_slice_2D(in_slice) && window.slide_window_slice_2D(sum_slice)); } break; case 1: { window_sum.set(Window::DimY, Window::Dimension(0, 0, 0)); Window in_slice = window.first_slice_window_2D(); Window sum_slice = window_sum.first_slice_window_2D(); do { unsigned int idx = 0; add_2D_tensor_argument(idx, _input, in_slice); add_2D_tensor_argument(idx, _sum, sum_slice); add_2D_tensor_argument(idx, _output, in_slice); enqueue(queue, *this, in_slice, lws_hint()); } while(window.slide_window_slice_2D(in_slice) && window.slide_window_slice_2D(sum_slice)); } break; case 2: { window_sum.set(Window::DimZ, Window::Dimension(0, 0, 0)); Window in_slice = window.first_slice_window_3D(); Window sum_slice = window_sum.first_slice_window_3D(); do { unsigned int idx = 0; add_3D_tensor_argument(idx, _input, in_slice); add_3D_tensor_argument(idx, _sum, sum_slice); add_3D_tensor_argument(idx, _output, in_slice); enqueue(queue, *this, in_slice, lws_hint()); } while(window.slide_window_slice_3D(in_slice) && window.slide_window_slice_3D(sum_slice)); } break; default: ARM_COMPUTE_ERROR("Not supported"); } } } // namespace arm_compute