| /* |
| * 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/NEON/kernels/NEGEMMMatrixAccumulateBiasesKernel.h" |
| |
| #include "arm_compute/core/AccessWindowStatic.h" |
| #include "arm_compute/core/Error.h" |
| #include "arm_compute/core/Helpers.h" |
| #include "arm_compute/core/ITensor.h" |
| #include "arm_compute/core/NEON/NEFixedPoint.h" |
| #include "arm_compute/core/Types.h" |
| #include "arm_compute/core/Validate.h" |
| #include "arm_compute/core/Window.h" |
| |
| #include <arm_neon.h> |
| #include <cstddef> |
| #include <cstdint> |
| |
| using namespace arm_compute; |
| |
| NEGEMMMatrixAccumulateBiasesKernel::NEGEMMMatrixAccumulateBiasesKernel() |
| : _accum(nullptr), _biases(nullptr) |
| { |
| } |
| |
| void NEGEMMMatrixAccumulateBiasesKernel::configure(ITensor *accum, const ITensor *biases) |
| { |
| ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(accum, 1, DataType::QS8, DataType::QS16, DataType::F16, DataType::F32); |
| ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(biases, accum); |
| ARM_COMPUTE_ERROR_ON_MISMATCHING_FIXED_POINT_POSITION(biases, accum); |
| ARM_COMPUTE_ERROR_ON(biases->info()->num_dimensions() > 1); |
| |
| _biases = biases; |
| _accum = accum; |
| |
| constexpr unsigned int num_elems_processed_per_iteration = 16; |
| |
| // Configure kernel window |
| Window win = calculate_max_window(*accum->info(), Steps(num_elems_processed_per_iteration)); |
| |
| update_window_and_padding(win, |
| AccessWindowHorizontal(accum->info(), 0, num_elems_processed_per_iteration), |
| AccessWindowStatic(biases->info(), 0, 0, win.x().end(), biases->info()->tensor_shape().y())); |
| |
| AccessWindowHorizontal output_access(accum->info(), 0, num_elems_processed_per_iteration); |
| |
| // Set the valid region for the accum tensor |
| Coordinates coord; |
| coord.set_num_dimensions(accum->info()->num_dimensions()); |
| output_access.set_valid_region(win, ValidRegion(coord, accum->info()->tensor_shape())); |
| |
| INEKernel::configure(win); |
| } |
| |
| void NEGEMMMatrixAccumulateBiasesKernel::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); |
| |
| Window win_biases; |
| win_biases.set(Window::DimX, Window::Dimension(window.x().start(), window.x().end(), window.x().step())); |
| win_biases.set(Window::DimY, Window::Dimension(0, 1, 1)); |
| |
| Iterator in0_out(_accum, window); |
| Iterator in1(_biases, win_biases); |
| |
| switch(_accum->info()->data_type()) |
| { |
| case DataType::F32: |
| { |
| execute_window_loop(window, [&](const Coordinates & id) |
| { |
| const float32x4x4_t accum = vld4q_f32(reinterpret_cast<const float *>(in0_out.ptr())); |
| const float32x4x4_t biases = vld4q_f32(reinterpret_cast<const float *>(in1.ptr())); |
| const float32x4x4_t res = |
| { |
| { |
| vaddq_f32(accum.val[0], biases.val[0]), |
| vaddq_f32(accum.val[1], biases.val[1]), |
| vaddq_f32(accum.val[2], biases.val[2]), |
| vaddq_f32(accum.val[3], biases.val[3]) |
| } |
| }; |
| |
| vst4q_f32(reinterpret_cast<float *>(in0_out.ptr()), res); |
| }, |
| in0_out, in1); |
| break; |
| } |
| #ifdef ARM_COMPUTE_AARCH64_V8_2 |
| case DataType::F16: |
| { |
| execute_window_loop(window, [&](const Coordinates & id) |
| { |
| const float16x8x2_t accum = vld2q_f16(reinterpret_cast<const float16_t *>(in0_out.ptr())); |
| const float16x8x2_t biases = vld2q_f16(reinterpret_cast<const float16_t *>(in1.ptr())); |
| const float16x8x2_t res = |
| { |
| { |
| vaddq_f16(accum.val[0], biases.val[0]), |
| vaddq_f16(accum.val[1], biases.val[1]) |
| } |
| }; |
| |
| vst2q_f16(reinterpret_cast<float16_t *>(in0_out.ptr()), res); |
| }, |
| in0_out, in1); |
| break; |
| } |
| #endif /* ARM_COMPUTE_AARCH64_V8_2 */ |
| case DataType::QS8: |
| { |
| execute_window_loop(window, [&](const Coordinates & id) |
| { |
| const qint8x16_t accum = vld1q_qs8(reinterpret_cast<const qint8_t *>(in0_out.ptr())); |
| const qint8x16_t biases = vld1q_qs8(reinterpret_cast<const qint8_t *>(in1.ptr())); |
| |
| vst1q_qs8(reinterpret_cast<qint8_t *>(in0_out.ptr()), vqaddq_qs8(accum, biases)); |
| }, |
| in0_out, in1); |
| break; |
| } |
| case DataType::QS16: |
| { |
| execute_window_loop(window, [&](const Coordinates & id) |
| { |
| qint16x8x2_t accum = vld2q_s16(reinterpret_cast<const qint16_t *>(in0_out.ptr())); |
| const qint16x8x2_t biases = vld2q_s16(reinterpret_cast<const qint16_t *>(in1.ptr())); |
| |
| accum.val[0] = vqaddq_qs16(accum.val[0], biases.val[0]); |
| accum.val[1] = vqaddq_qs16(accum.val[1], biases.val[1]); |
| |
| vst2q_s16(reinterpret_cast<qint16_t *>(in0_out.ptr()), accum); |
| }, |
| in0_out, in1); |
| break; |
| } |
| default: |
| ARM_COMPUTE_ERROR("Data type not supported"); |
| break; |
| } |
| } |