/* * Copyright (c) 2017-2018 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/arm64/NEGEMMLowpAArch64V8P4Kernel.h" #include "arm_compute/core/AccessWindowStatic.h" #include "arm_compute/core/Error.h" #include "arm_compute/core/Helpers.h" #include "arm_compute/core/IAccessWindow.h" #include "arm_compute/core/ITensor.h" #include "arm_compute/core/TensorInfo.h" #include "arm_compute/core/Types.h" #include "arm_compute/core/Utils.h" #include "arm_compute/core/Validate.h" #include "arm_compute/core/Window.h" #include "support/ToolchainSupport.h" namespace arm_compute { #include "arm_compute/core/NEON/kernels/assembly/gemm_interleaved.hpp" #include "arm_compute/core/NEON/kernels/assembly/kernels/a64_gemm_s8_12x8.hpp" #include "arm_compute/core/NEON/kernels/assembly/kernels/a64_gemm_u8_12x8.hpp" } // namespace arm_compute #include #include #include // Enable only if compiled for AArch64-V8.2-A targets #ifdef ARM_COMPUTE_AARCH64_V8_2 namespace { using namespace arm_compute; Status validate_arguments(const ITensorInfo *input0, const ITensorInfo *input1, const ITensorInfo *output) { ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input0, 1, DataType::QASYMM8, DataType::U8, DataType::S8); ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::S32); ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input1); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input0, input1); return Status{}; } std::pair validate_and_configure_window(ITensorInfo *input0, ITensorInfo *input1, ITensorInfo *output) { // Configure kernel window Window win = calculate_max_window(*output); AccessWindowRectangle output_access(output, 0, 0, 12, 8); const int input0_access_end = ceil_to_multiple(input0->tensor_shape().x(), 8); const int input1_access_end = ceil_to_multiple(input1->tensor_shape().x(), 12); bool window_changed = update_window_and_padding(win, AccessWindowStatic(input0, 0, 0, input0_access_end, input0->tensor_shape().y()), AccessWindowStatic(input1, 0, 0, input1_access_end, input1->tensor_shape().y()), output_access); Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{}; return std::make_pair(err, win); } template void *align_workspace(GemmInterleaved &gemm, const ThreadInfo &info, ITensor *ws) { constexpr size_t alignment = 4096; const size_t offset = (gemm.get_working_size() + alignment - 1) * info.thread_id; void *workspace = ws->buffer() + offset; size_t workspace_size = ws->info()->total_size(); if(support::cpp11::align(alignment, gemm.get_working_size(), workspace, workspace_size) == nullptr) { ARM_COMPUTE_ERROR("Not enough space to align buffer!"); } return workspace; } template void execute_gemm(const Window &win, Iterator &in0, Iterator &in1, Iterator &out, const ThreadInfo &info, ITensor *ws, int M, int N, int K, bool is_transposed_0, bool is_transposed_1, int lda, int ldb, int ldc, float alpha, float beta) { ARM_COMPUTE_UNUSED(M); ARM_COMPUTE_UNUSED(N); ARM_COMPUTE_UNUSED(K); ARM_COMPUTE_UNUSED(is_transposed_0); ARM_COMPUTE_UNUSED(is_transposed_1); GemmInterleaved gemm(&info.cpu_info, M, N, K, is_transposed_0, is_transposed_1); void *workspace = align_workspace(gemm, info, ws); execute_window_loop(win, [&](const Coordinates & id) { gemm.execute(reinterpret_cast(in0.ptr()), lda, reinterpret_cast(in1.ptr()), ldb, reinterpret_cast(out.ptr()), ldc, alpha, beta, workspace); }, in0, out); } } // namespace namespace arm_compute { void NEGEMMLowpAArch64V8P4Kernel::internal_configure(const ITensor *input0, const ITensor *input1, ITensor *output, ITensor *workspace, float alpha, float beta, bool is_transposed_0, bool is_transposed_1) { // Perform validate step ARM_COMPUTE_ERROR_ON_NULLPTR(input0, input1, output); ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input0->info(), input1->info(), output->info())); _input0 = input0; _input1 = input1; _output = output; _workspace = workspace; _alpha = alpha; _beta = beta; _is_transposed_0 = is_transposed_0; _is_transposed_1 = is_transposed_1; // Configure kernel window auto win_config = validate_and_configure_window(input0->info(), input1->info(), output->info()); ARM_COMPUTE_ERROR_THROW_ON(win_config.first); INEKernel::configure(win_config.second); } Status NEGEMMLowpAArch64V8P4Kernel::validate(const ITensorInfo *input0, const ITensorInfo *input1, const ITensorInfo *output) { ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input0, input1, output)); ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input0->clone().get(), input1->clone().get(), output->clone().get()).first); return Status{}; } void NEGEMMLowpAArch64V8P4Kernel::run(const Window &window, const ThreadInfo &info) { ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window); const int lda = _input0->info()->strides_in_bytes().y(); const int ldb = _input1->info()->strides_in_bytes().y(); const int ldc = _output->info()->strides_in_bytes().y() / sizeof(uint32_t); const int M = std::min(_output->info()->tensor_shape().y(), static_cast(window.y().end())) - window.y().start(); const int N = _output->info()->tensor_shape().x(); const int K = _input0->info()->tensor_shape().x(); // Only iterate over batches Window win(window); win.set(0, Window::Dimension(0, 1, 1)); win.set(1, Window::Dimension(0, 1, 1)); Iterator in0(_input0, window); Iterator in1(_input1, window); Iterator out(_output, window); switch(_input0->info()->data_type()) { case DataType::QASYMM8: case DataType::U8: { execute_gemm(win, in0, in1, out, info, _workspace, M, N, K, _is_transposed_0, _is_transposed_1, lda, ldb, ldc, _alpha, _beta); break; } case DataType::S8: { execute_gemm(win, in0, in1, out, info, _workspace, M, N, K, _is_transposed_0, _is_transposed_1, lda, ldb, ldc, _alpha, _beta); break; } default: { ARM_COMPUTE_ERROR("Not supported."); break; } } } } // namespace arm_compute #endif /* ARM_COMPUTE_AARCH64_V8_2 */