| /* |
| * Copyright (c) 2017-2019 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/CLGEMMInterleave4x4Kernel.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/CL/OpenCL.h" |
| #include "arm_compute/core/Error.h" |
| #include "arm_compute/core/Helpers.h" |
| #include "arm_compute/core/TensorInfo.h" |
| #include "arm_compute/core/Types.h" |
| #include "arm_compute/core/Utils.h" |
| #include "arm_compute/core/Window.h" |
| #include "arm_compute/core/utils/misc/ShapeCalculator.h" |
| |
| using namespace arm_compute; |
| using namespace arm_compute::misc::shape_calculator; |
| |
| namespace |
| { |
| Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, int mult_interleave4x4_height, bool reinterpret_input_as_3d) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON(mult_interleave4x4_height < 1); |
| ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input); |
| ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::U8, DataType::S8, |
| DataType::U16, DataType::S16, DataType::U32, DataType::S32, |
| DataType::F16, DataType::F32); |
| |
| if(output->total_size() != 0) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(), compute_interleaved_shape(*input, mult_interleave4x4_height, reinterpret_input_as_3d)); |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_QUANTIZATION_INFO(input, output); |
| } |
| |
| return Status{}; |
| } |
| |
| std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *output, int mult_interleave4x4_height, bool reinterpret_input_as_3d) |
| { |
| constexpr unsigned int num_elems_processed_per_iteration_x = 4; |
| constexpr unsigned int num_elems_processed_per_iteration_y = 4; |
| const unsigned int num_elems_written_per_iteration = num_elems_processed_per_iteration_x * num_elems_processed_per_iteration_y * mult_interleave4x4_height; |
| bool window_changed = false; |
| |
| TensorInfo tmp_info(*input); |
| |
| if(reinterpret_input_as_3d) |
| { |
| // Since the input tensor has to be reinterpreted as 3D and the execute window is based on a 2D interleave, |
| // the window needs to be constructed on the 2D collapsed version of the tensor |
| TensorShape tmp_shape(input->tensor_shape()); |
| tmp_shape.collapse(2U, 1U); |
| tmp_info.set_tensor_shape(tmp_shape); |
| } |
| |
| // Output auto inizialitation if not yet initialized |
| auto_init_if_empty(*output, input->clone()->set_tensor_shape(compute_interleaved_shape(*input, mult_interleave4x4_height))); |
| |
| // Configure window |
| const float scale_x = 4.0f * static_cast<float>(mult_interleave4x4_height); |
| const float scale_y = 1.0f / (scale_x); |
| |
| // Note: bottom paddings are calculated manually as the input can be reinterpreted as 3D tensor |
| // The only way to set properly the paddings, it is to set those explicitly through the AccessWindowStatic |
| const int m = reinterpret_input_as_3d ? input->tensor_shape()[1] * input->tensor_shape()[2] : input->tensor_shape()[1]; |
| const int bottom_pad = (num_elems_processed_per_iteration_y - (m % num_elems_processed_per_iteration_y)) % num_elems_processed_per_iteration_y; |
| |
| Window win = calculate_max_window(tmp_info, Steps(num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y)); |
| Window win_in = calculate_max_window(*input, Steps(num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y)); |
| |
| AccessWindowStatic input_access(input, 0, 0, |
| ceil_to_multiple(input->dimension(0), num_elems_processed_per_iteration_x), |
| input->dimension(1) + bottom_pad); |
| AccessWindowRectangle output_access(output, 0, 0, num_elems_written_per_iteration, 1, scale_x, scale_y); |
| |
| window_changed = update_window_and_padding(win_in, input_access) || // window used by the execute_window_loop |
| update_window_and_padding(win, output_access); // window used to update the padding requirements of output tensor |
| output_access.set_valid_region(win, ValidRegion(Coordinates(0, 0), output->tensor_shape())); |
| |
| // Collapse along the Z direction |
| // This collapse needs to be here in order to tune the Z dimension of LWS |
| Window collapsed = win.collapse(win, Window::DimZ); |
| |
| Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{}; |
| return std::make_pair(err, collapsed); |
| } |
| } // namespace |
| |
| CLGEMMInterleave4x4Kernel::CLGEMMInterleave4x4Kernel() |
| : _input(nullptr), _output(nullptr), _reinterpret_input_as_3d(false) |
| { |
| } |
| |
| void CLGEMMInterleave4x4Kernel::configure(const ICLTensor *input, ICLTensor *output, int mult_interleave4x4_height, bool reinterpret_input_as_3d, bool unroll_block) |
| { |
| ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); |
| |
| // Output auto inizialitation if not yet initialized |
| auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(compute_interleaved_shape(*input->info(), mult_interleave4x4_height, reinterpret_input_as_3d))); |
| |
| // Perform validate step |
| ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), mult_interleave4x4_height, reinterpret_input_as_3d)); |
| |
| _input = input; |
| _output = output; |
| _reinterpret_input_as_3d = reinterpret_input_as_3d; |
| |
| // Create build options |
| CLBuildOptions build_opts; |
| build_opts.add_option("-DMULT_INTERLEAVE4X4_HEIGHT=" + support::cpp11::to_string(mult_interleave4x4_height)); |
| build_opts.add_option_if(unroll_block, "-DUNROLL_BLOCK"); |
| build_opts.add_option_if(_reinterpret_input_as_3d, "-DREINTERPRET_INPUT_AS_3D"); |
| build_opts.add_option_if(_reinterpret_input_as_3d, "-DHEIGHT_GEMM3D=" + support::cpp11::to_string(input->info()->dimension(1))); |
| build_opts.add_option_if(_reinterpret_input_as_3d, "-DDEPTH_GEMM3D=" + support::cpp11::to_string(input->info()->dimension(2))); |
| |
| switch(input->info()->element_size()) |
| { |
| case 1: |
| build_opts.add_option("-DDATA_TYPE=uchar"); |
| break; |
| case 2: |
| build_opts.add_option("-DDATA_TYPE=ushort"); |
| break; |
| case 4: |
| build_opts.add_option("-DDATA_TYPE=uint"); |
| break; |
| default: |
| ARM_COMPUTE_ERROR("Data type not supported"); |
| } |
| |
| // Create kernel |
| _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("gemm_interleave4x4", build_opts.options())); |
| |
| // Configure kernel window |
| auto win_config = validate_and_configure_window(input->info(), output->info(), mult_interleave4x4_height, reinterpret_input_as_3d); |
| ARM_COMPUTE_ERROR_THROW_ON(win_config.first); |
| ICLKernel::configure_internal(win_config.second); |
| |
| // Set config_id for enabling LWS tuning |
| _config_id = "interleave4x4_"; |
| _config_id += (_reinterpret_input_as_3d ? "3d_" : ""); |
| _config_id += lower_string(string_from_data_type(input->info()->data_type())); |
| _config_id += "_"; |
| _config_id += support::cpp11::to_string(output->info()->dimension(0)); |
| _config_id += "_"; |
| _config_id += support::cpp11::to_string(output->info()->dimension(1)); |
| _config_id += "_"; |
| _config_id += support::cpp11::to_string(output->info()->dimension(2)); |
| _config_id += "_"; |
| _config_id += support::cpp11::to_string(output->info()->dimension(3)); |
| } |
| |
| Status CLGEMMInterleave4x4Kernel::validate(const ITensorInfo *input, const ITensorInfo *output, int mult_interleave4x4_height, bool reinterpret_input_as_3d) |
| { |
| ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, mult_interleave4x4_height, reinterpret_input_as_3d)); |
| ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), output->clone().get(), mult_interleave4x4_height, reinterpret_input_as_3d).first); |
| |
| return Status{}; |
| } |
| |
| void CLGEMMInterleave4x4Kernel::run(const Window &window, cl::CommandQueue &queue) |
| { |
| ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); |
| ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window); |
| |
| /* |
| * This kernel puts the values in a 4x4 block of Matrix A on the same row (Interleaved values) |
| * |a00 a01 a02 a03| |
| * |a10 a11 a12 a13| |
| * |a20 a21 a22 a23| = | a00 a10 a20 a30 || a01 a11 a21 a31 || a02 a12 a22 a32 || a03 a13 a23 a33 | |
| * |a30 a31 a32 a33| |
| * |
| * After this operation, the output matrix will have the following shape: [ height * 4, width / 4 ] |
| */ |
| Window slice = window.first_slice_window_3D(); |
| |
| if(_reinterpret_input_as_3d) |
| { |
| // Pass bottom paddings to the kernel if the input has to be reinterpreted as 3D tensor |
| const unsigned int idx0 = 2 * num_arguments_per_3D_tensor(); |
| const unsigned int total_cross_plane_pad = _input->info()->padding().top + _input->info()->padding().bottom; |
| _kernel.setArg<cl_uint>(idx0, static_cast<unsigned int>(total_cross_plane_pad)); |
| } |
| |
| 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.slide_window_slice_3D(slice)); |
| } |
