/* * Copyright (c) 2017 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/CLSoftmaxLayerKernel.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/ICLTensor.h" #include "arm_compute/core/CL/OpenCL.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 #include using namespace arm_compute; void CLLogits1DMaxKernel::configure(const ICLTensor *input, ICLTensor *output) { ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QS8, DataType::QS16, DataType::F16, DataType::F32); ARM_COMPUTE_ERROR_ON_NULLPTR(output); // Softmax across the x dimension TensorShape output_shape{ input->info()->tensor_shape() }; output_shape.set(0, 1); // Output auto initialization if not yet initialized auto_init_if_empty(*output->info(), output_shape, 1, input->info()->data_type(), input->info()->fixed_point_position()); ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); ARM_COMPUTE_ERROR_ON_MISMATCHING_FIXED_POINT_POSITION(input, output); ARM_COMPUTE_ERROR_ON_MISMATCHING_DIMENSIONS(output->info()->tensor_shape(), output_shape); _input = input; _output = output; // The kernel loops over all elements in steps of 16 const unsigned int num_elems_processed_per_iteration = ceil_to_multiple(input->info()->dimension(0), 16); // Set build options std::set build_opts; build_opts.emplace(("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type()))); if(is_data_type_fixed_point(input->info()->data_type())) { build_opts.emplace(("-DFIXED_POINT_POSITION=" + support::cpp11::to_string(input->info()->fixed_point_position()))); } else if(input->info()->data_type() == DataType::F16) { build_opts.emplace("-DUSE_F16"); } // Tell the kernel that the width is not a multiple of 16 if((input->info()->dimension(0) % max_cl_vector_width) != 0) { build_opts.emplace("-DNON_MULTIPLE_OF_16"); } // Create kernel _kernel = static_cast(CLKernelLibrary::get().create_kernel("softmax_layer_max", build_opts)); // Set fixed arguments unsigned int idx = 2 * num_arguments_per_3D_tensor(); //Skip the input and output parameters _kernel.setArg(idx++, input->info()->dimension(0)); // Configure kernel window constexpr unsigned int num_elems_written_per_iteration = 1; Window win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration)); AccessWindowHorizontal input_access(input->info(), 0, num_elems_processed_per_iteration); AccessWindowHorizontal output_access(output->info(), 0, num_elems_written_per_iteration); update_window_and_padding(win, input_access, output_access); output_access.set_valid_region(win, ValidRegion(Coordinates(), output->info()->tensor_shape())); ICLKernel::configure(win); } CLLogits1DShiftExpSumKernel::CLLogits1DShiftExpSumKernel() : _input(nullptr), _max(nullptr), _output(nullptr), _sum(nullptr) { } void CLLogits1DShiftExpSumKernel::configure(const ICLTensor *input, const ICLTensor *max, ICLTensor *output, ICLTensor *sum, float beta) { ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QS8, DataType::QS16, DataType::F16, DataType::F32); ARM_COMPUTE_ERROR_ON_NULLPTR(max, sum, output); ARM_COMPUTE_ERROR_ON(beta != 1.0f && input->info()->data_type() != DataType::F32); // Output auto initialization if not yet initialized auto_init_if_empty(*sum->info(), max->info()->tensor_shape(), 1, input->info()->data_type(), input->info()->fixed_point_position()); auto_init_if_empty(*output->info(), input->info()->tensor_shape(), 1, input->info()->data_type(), input->info()->fixed_point_position()); ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output, max, sum); ARM_COMPUTE_ERROR_ON_MISMATCHING_FIXED_POINT_POSITION(input, output, max, sum); ARM_COMPUTE_ERROR_ON_MISMATCHING_SHAPES(input, output); ARM_COMPUTE_ERROR_ON_MISMATCHING_SHAPES(max, sum); _input = input; _max = max; _output = output; _sum = sum; // The kernel loops over all elements in steps of 16 const unsigned int num_elems_processed_per_iteration = ceil_to_multiple(input->info()->dimension(0), 16); // Set build options std::set build_opts; build_opts.emplace(("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type()))); if(is_data_type_fixed_point(input->info()->data_type())) { build_opts.emplace(("-DFIXED_POINT_POSITION=" + support::cpp11::to_string(input->info()->fixed_point_position()))); } else if(input->info()->data_type() == DataType::F16) { build_opts.emplace("-DUSE_F16"); } // Tell the kernel that the width is not a multiple of 16 if((input->info()->dimension(0) % max_cl_vector_width) != 0) { build_opts.emplace("-DNON_MULTIPLE_OF_16"); } if(beta != 1.0f) { build_opts.emplace(("-DBETA=" + float_to_string_with_full_precision(beta))); } // Create kernel _kernel = static_cast(CLKernelLibrary::get().create_kernel("softmax_layer_shift_exp_sum", build_opts)); // Set fixed arguments unsigned int idx = 4 * num_arguments_per_3D_tensor(); //Skip the input and output parameters _kernel.setArg(idx++, input->info()->dimension(0)); // Configure window Window win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration)); AccessWindowHorizontal input_access(input->info(), 0, num_elems_processed_per_iteration); AccessWindowHorizontal max_access(max->info(), 0, 1); AccessWindowHorizontal output_access(output->info(), 0, num_elems_processed_per_iteration); AccessWindowHorizontal sum_access(sum->info(), 0, 1); update_window_and_padding(win, input_access, max_access, output_access, sum_access); output_access.set_valid_region(win, input->info()->valid_region()); sum_access.set_valid_region(win, ValidRegion(Coordinates(), sum->info()->tensor_shape())); ICLKernel::configure(win); } void CLLogits1DShiftExpSumKernel::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_collapsed = window.collapse_if_possible(ICLKernel::window(), Window::DimZ); Window slice = window_collapsed.first_slice_window_3D(); do { unsigned int idx = 0; // Set inputs add_3D_tensor_argument(idx, _input, slice); add_3D_tensor_argument(idx, _max, slice); add_3D_tensor_argument(idx, _output, slice); add_3D_tensor_argument(idx, _sum, slice); enqueue(queue, *this, slice); } while(window_collapsed.slide_window_slice_3D(slice)); } CLLogits1DNormKernel::CLLogits1DNormKernel() : _input(nullptr), _sum(nullptr), _output(nullptr) { } void CLLogits1DNormKernel::configure(const ICLTensor *input, const ICLTensor *sum, ICLTensor *output) { ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QS8, DataType::QS16, DataType::F16, DataType::F32); ARM_COMPUTE_ERROR_ON_NULLPTR(sum, output); // Output auto initialization if not yet initialized auto_init_if_empty(*output->info(), input->info()->tensor_shape(), 1, input->info()->data_type(), input->info()->fixed_point_position()); ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, sum, output); ARM_COMPUTE_ERROR_ON_MISMATCHING_FIXED_POINT_POSITION(input, sum, output); ARM_COMPUTE_ERROR_ON_MISMATCHING_SHAPES(input, output); _input = input; _sum = sum; _output = output; // Set build options std::set build_opts; build_opts.emplace(("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type()))); if(is_data_type_fixed_point(input->info()->data_type())) { build_opts.emplace(("-DFIXED_POINT_POSITION=" + support::cpp11::to_string(input->info()->fixed_point_position()))); } // Create kernel _kernel = static_cast(CLKernelLibrary::get().create_kernel("softmax_layer_norm", build_opts)); // Configure window constexpr unsigned int num_elems_processed_per_iteration = 16; Window win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration)); AccessWindowHorizontal input_access(input->info(), 0, num_elems_processed_per_iteration); AccessWindowStatic sum_access(sum->info(), 0, 0, 1, sum->info()->dimension(1)); AccessWindowHorizontal output_access(output->info(), 0, num_elems_processed_per_iteration); update_window_and_padding(win, input_access, sum_access, output_access); output_access.set_valid_region(win, input->info()->valid_region()); ICLKernel::configure(win); } void CLLogits1DNormKernel::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_collapsed = window.collapse_if_possible(ICLKernel::window(), Window::DimZ); Window slice = window_collapsed.first_slice_window_3D(); do { Window sum_slice = slice; sum_slice.set(Window::DimX, Window::Dimension(0, 1, 1)); unsigned int idx = 0; // Set inputs add_3D_tensor_argument(idx, _input, slice); add_3D_tensor_argument(idx, _sum, sum_slice); add_3D_tensor_argument(idx, _output, slice); enqueue(queue, *this, slice); } while(window_collapsed.slide_window_slice_3D(slice)); }