| /* |
| * Copyright (c) 2016-2020 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 "src/core/NEON/kernels/NEGEMMInterleave4x4Kernel.h" |
| |
| #include "arm_compute/core/Error.h" |
| #include "arm_compute/core/Helpers.h" |
| #include "arm_compute/core/ITensor.h" |
| #include "arm_compute/core/Types.h" |
| #include "arm_compute/core/Validate.h" |
| #include "arm_compute/core/Window.h" |
| #include "arm_compute/core/utils/misc/ShapeCalculator.h" |
| #include "src/core/NEON/INEKernel.h" |
| #include "src/core/helpers/AutoConfiguration.h" |
| #include "src/core/helpers/WindowHelpers.h" |
| |
| #include <arm_neon.h> |
| #include <cstddef> |
| #include <cstdint> |
| #include <tuple> |
| |
| using namespace arm_compute; |
| using namespace arm_compute::misc::shape_calculator; |
| |
| namespace |
| { |
| Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input); |
| //Note: ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(input) is not needed here as this kernel doesn't use NEON FP16 instructions. |
| ARM_COMPUTE_RETURN_ERROR_ON(input->data_type() == DataType::UNKNOWN); |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); |
| |
| if(output->total_size() != 0) |
| { |
| TensorShape output_shape = input->tensor_shape(); |
| output_shape.set(0, input->dimension(0) * 4); |
| output_shape.set(1, std::ceil(input->dimension(1) / 4.0f)); |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(), output_shape); |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_QUANTIZATION_INFO(input, output); |
| } |
| |
| return Status{}; |
| } |
| } // namespace |
| |
| NEGEMMInterleave4x4Kernel::NEGEMMInterleave4x4Kernel() |
| : _func(nullptr) |
| { |
| } |
| |
| void NEGEMMInterleave4x4Kernel::configure(const ITensor *input, ITensor *output) |
| { |
| 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()))); |
| |
| // Perform validate step |
| ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info())); |
| |
| _input = input; |
| _output = output; |
| |
| switch(input->info()->element_size()) |
| { |
| case 1: |
| _func = &NEGEMMInterleave4x4Kernel::gemm_interleave4x4<uint8_t>; |
| break; |
| case 2: |
| _func = &NEGEMMInterleave4x4Kernel::gemm_interleave4x4<uint16_t>; |
| break; |
| case 4: |
| _func = &NEGEMMInterleave4x4Kernel::gemm_interleave4x4<uint32_t>; |
| break; |
| default: |
| ARM_COMPUTE_ERROR_ON("Element size not supported"); |
| break; |
| } |
| |
| Window win = calculate_max_window(*input->info(), Steps(1, 4)); |
| |
| Coordinates coord; |
| coord.set_num_dimensions(output->info()->num_dimensions()); |
| output->info()->set_valid_region(ValidRegion(coord, output->info()->tensor_shape())); |
| |
| INEKernel::configure(win); |
| } |
| |
| Status NEGEMMInterleave4x4Kernel::validate(const ITensorInfo *input, const ITensorInfo *output) |
| { |
| ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output)); |
| |
| return Status{}; |
| } |
| |
| template <typename ScalarType> |
| void NEGEMMInterleave4x4Kernel::gemm_interleave4x4(const ITensor *input, ITensor *output, const Window &window) |
| { |
| const size_t window_start_x = window.x().start(); |
| const size_t window_end_x = window.x().end(); |
| |
| const size_t in_height = input->info()->dimension(1); |
| const size_t in_stride = input->info()->strides_in_bytes()[1]; |
| |
| const size_t partial_y = in_height % 4; |
| |
| // Set window for the input tensor |
| Window win = window; |
| win.set(Window::DimX, Window::Dimension(0, 1, 1)); |
| |
| // Set window for the output tensor |
| Window win_out(window); |
| win_out.set(Window::DimX, Window::Dimension(0, 1, 1)); |
| win_out.scale(Window::DimY, 0.25f); |
| |
| Iterator in(input, win); |
| Iterator out(output, win_out); |
| |
| execute_window_loop(win, [&](const Coordinates & id) |
| { |
| if(id.y() + 4 <= static_cast<int>(in_height)) |
| { |
| for(size_t x = window_start_x; x < window_end_x; ++x) |
| { |
| const ScalarType data[4] = |
| { |
| *(reinterpret_cast<const ScalarType *>(in.ptr() + 0 * in_stride) + x), |
| *(reinterpret_cast<const ScalarType *>(in.ptr() + 1 * in_stride) + x), |
| *(reinterpret_cast<const ScalarType *>(in.ptr() + 2 * in_stride) + x), |
| *(reinterpret_cast<const ScalarType *>(in.ptr() + 3 * in_stride) + x), |
| }; |
| std::memcpy(out.ptr() + x * 4 * sizeof(ScalarType), data, 4 * sizeof(ScalarType)); |
| } |
| } |
| else |
| { |
| for(size_t x = window_start_x; x < window_end_x; ++x) |
| { |
| ScalarType data[4] = { 0, 0, 0, 0 }; |
| |
| for(size_t y = 0; y < partial_y; ++y) |
| { |
| data[y] = *(reinterpret_cast<const ScalarType *>(in.ptr() + y * in_stride) + x); |
| } |
| |
| std::memcpy(out.ptr() + x * 4 * sizeof(ScalarType), data, 4 * sizeof(ScalarType)); |
| } |
| } |
| }, |
| in, out); |
| } |
| |
| void NEGEMMInterleave4x4Kernel::run(const Window &window, const ThreadInfo &info) |
| { |
| ARM_COMPUTE_UNUSED(info); |
| ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); |
| ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window); |
| ARM_COMPUTE_ERROR_ON(_func == nullptr); |
| /* |
| * 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, ceil(width / 4.0f) ] |
| */ |
| (this->*_func)(_input, _output, window); |
| } |