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Diffstat (limited to 'arm_compute/runtime/NEON/AssemblyHelper.h')
| -rw-r--r-- | arm_compute/runtime/NEON/AssemblyHelper.h | 252 |
1 files changed, 0 insertions, 252 deletions
diff --git a/arm_compute/runtime/NEON/AssemblyHelper.h b/arm_compute/runtime/NEON/AssemblyHelper.h deleted file mode 100644 index a62078e842..0000000000 --- a/arm_compute/runtime/NEON/AssemblyHelper.h +++ /dev/null @@ -1,252 +0,0 @@ -/* - * Copyright (c) 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. - */ -#ifndef __ARM_ASSEMBLY_HELPER_H__ -#define __ARM_ASSEMBLY_HELPER_H__ - -#include "arm_compute/core/ITensor.h" -#include "support/ToolchainSupport.h" - -#include "arm_compute/core/Helpers.h" -#include "arm_compute/core/IAccessWindow.h" -#include "arm_compute/core/Log.h" -#include "arm_compute/core/NEON/kernels/assembly/NEGEMMAssemblyWrapper.h" -#include "arm_compute/core/NEON/kernels/assembly/arm_gemm.hpp" -#include "arm_compute/core/TensorInfo.h" -#include "arm_compute/core/Types.h" -#include "arm_compute/core/Validate.h" -#include "arm_compute/core/Window.h" -#include "arm_compute/runtime/NEON/NEScheduler.h" - -namespace arm_compute -{ -/** Assembly kernel glue */ -template <typename TypeInput, typename TypeOutput> -class AssemblyKernelGlue final -{ -public: - /** Operator type */ - using TypeOperator = TypeInput; - /** Result type */ - using TypeResult = TypeOutput; - /** Default constructor. */ - AssemblyKernelGlue() - : _gemm_kernel_asm(nullptr), _optimised_kernel(nullptr), _a(nullptr), _b(nullptr), _d(nullptr), _workspace(nullptr), _pretranspose(nullptr), _is_prepared(false) - { - } - /** Assembly Gemm */ - using AssemblyGemm = arm_gemm::GemmCommon<TypeInput, TypeOutput>; - - /** Prevent instances of this class from being copy constructed */ - const AssemblyKernelGlue<TypeInput, TypeOutput> &operator=(const AssemblyKernelGlue<TypeInput, TypeOutput> &) = delete; - /** Prevent instances of this class from being copied */ - AssemblyKernelGlue(const AssemblyKernelGlue<TypeInput, TypeOutput> &) = delete; - - /** Assembly Gemm kernel */ - std::unique_ptr<AssemblyGemm> _gemm_kernel_asm; - /** Optimised NEON kernel */ - std::unique_ptr<INEKernel> _optimised_kernel; - /** Input A */ - const ITensor *_a; - /** Input B */ - const ITensor *_b; - /** Output */ - ITensor *_d; - /** GEMM workspace */ - ITensor *_workspace; - /** Pre-transpose tensor */ - ITensor *_pretranspose; - /** Prepared flag */ - bool _is_prepared; - - /** Runs a preparation step, usually for pre-transposing matrix b */ - void prepare() - { - // Pretranspose B if required - if(_gemm_kernel_asm->B_pretranspose_required()) - { - const int ldb = _b->info()->strides_in_bytes().y() / sizeof(TypeInput); - const auto in1_ptr = reinterpret_cast<const TypeInput *>(_b->buffer()); - const int multi_stride_b = _b->info()->strides_in_bytes().z() / sizeof(TypeInput); - - ARM_COMPUTE_ERROR_ON(_pretranspose == nullptr || _pretranspose->buffer() == nullptr); - _gemm_kernel_asm->pretranspose_B_array(_pretranspose->buffer(), in1_ptr, ldb, multi_stride_b); - _b->mark_as_unused(); - } - - _is_prepared = true; - } - - /** Configures the arrays pointers and strides in the assembly kernel and executes the assembly kernel. - * The call to set_arrays is needed to deal with the input sizes containing batches (dims > 2) - */ - inline void run() - { - const int lda = _a->info()->strides_in_bytes().y() / sizeof(TypeInput); - const int ldb = _b->info()->strides_in_bytes().y() / sizeof(TypeInput); - const int ldd = _d->info()->strides_in_bytes().y() / sizeof(TypeOutput); - - // In the case of NHWC we want to interpret the output shape as 3D. Thus, the batch stride for A is - // the relevant multiple of the row stride. - const bool is_nhwc = _a->info()->data_layout() == DataLayout::NHWC; - const int stride_in_bytes_a = is_nhwc ? _a->info()->strides_in_bytes().y() * _d->info()->dimension(1) : _a->info()->strides_in_bytes().z(); - - const int batch_stride_a = stride_in_bytes_a / sizeof(TypeInput); - const int batch_stride_d = _d->info()->strides_in_bytes().z() / sizeof(TypeOutput); - - const int multi_stride_a = _a->info()->strides_in_bytes()[3] / sizeof(TypeInput); - const int multi_stride_b = _b->info()->strides_in_bytes().z() / sizeof(TypeInput); - const int multi_stride_d = _d->info()->strides_in_bytes()[3] / sizeof(TypeOutput); - - const auto in0_ptr = reinterpret_cast<const TypeInput *>(_a->buffer()); - const auto in1_ptr = reinterpret_cast<const TypeInput *>(_b->buffer()); - auto out_ptr = reinterpret_cast<TypeOutput *>(_d->buffer()); - - // Set workspace if needed and reset number of threads as buffer manager gets re-created with max_threads - if(_workspace != nullptr) - { - _gemm_kernel_asm->set_working_space(reinterpret_cast<void *>(_workspace->buffer())); - const unsigned int window_size = _gemm_kernel_asm->get_window_size(); - unsigned int num_threads = NEScheduler::get().num_threads(); - if(window_size < num_threads) - { - num_threads = window_size; - _gemm_kernel_asm->set_nthreads(num_threads); - } - } - - // Prepare assembly kernel - prepare(); - - // Set gemm parameters - _gemm_kernel_asm->set_arrays(in0_ptr, lda, batch_stride_a, multi_stride_a, in1_ptr, ldb, multi_stride_b, out_ptr, ldd, batch_stride_d, multi_stride_d); - - // Schedule assembly kernel - NEScheduler::get().schedule(_optimised_kernel.get(), Window::DimX); - } -}; - -/** Float 32 assembly kernel glue */ -using AssemblyKernelGlueF32 = AssemblyKernelGlue<float, float>; -/** Uint 8 to Uint 32 kernel glue */ -using AssemblyKernelGlueU8U32 = AssemblyKernelGlue<uint8_t, uint32_t>; -/** Int 8 to Int 32 kernel glue */ -using AssemblyKernelGlueS8S32 = AssemblyKernelGlue<int8_t, int32_t>; - -/** Allocate a workspace tensor. - * - * @param[in] workspace_size Size to allocate. - * @param[out] workspace Tensor to allocate. - * @param[in] memory_group Tensor memory group. - * @param[in] alignment Workspace memory alignment. - */ -inline void allocate_workspace(size_t workspace_size, Tensor &workspace, MemoryGroup *memory_group, size_t alignment) -{ - ARM_COMPUTE_ERROR_ON_MSG(workspace_size == 0, "size cannot be 0"); - workspace.allocator()->init(TensorInfo(TensorShape{ (workspace_size + alignment /* FIXME: remove alignment after COMPMID-1088 */) }, 1, DataType::S8), alignment); - if(memory_group != nullptr) - { - memory_group->manage(&workspace); - } - workspace.allocator()->allocate(); -} - -/** Create a wrapper kernel. - * - * @param[in] a Input tensor A. - * @param[in] b Input tensor B. - * @param[out] d Output tensor. - * @param[in] alpha Alpha value. - * @param[in] beta Beta value. - * @param[in] pretranspose_hint Pre-transpose hint in case matrix b should be pre-transposed - * @param[out] workspace Workspace tensor - * @param[out] B_pretranspose Tensor to hold the pre-transposed B - * @param[in] memory_group Tensor memory group. - * @param[out] asm_glue Assembly glue kernel. - * - * @return the wrapper kernel. - */ -template <typename T> -inline bool setup_assembly_kernel(const ITensor *a, const ITensor *b, ITensor *d, float alpha, float beta, bool pretranspose_hint, - Tensor &workspace, Tensor &B_pretranspose, MemoryGroup &memory_group, T &asm_glue) -{ - const CPUInfo &ci = NEScheduler::get().cpu_info(); - const int M = d->info()->tensor_shape().y(); - const int N = d->info()->tensor_shape().x(); - const int K = a->info()->tensor_shape().x(); - const int batches = d->info()->tensor_shape().total_size_upper(2); - const int multis = b->info()->tensor_shape().z(); - unsigned int num_threads = NEScheduler::get().num_threads(); - - // unique_ptr to a Gemm object - std::unique_ptr<typename T::AssemblyGemm> - asm_gemm(arm_gemm::gemm<typename T::TypeOperator, typename T::TypeResult>(ci, M, N, K, batches, multis, false, false, alpha, beta, num_threads, pretranspose_hint)); - // arm_compute wrapper for the Gemm object (see above) - std::unique_ptr<NEGEMMAssemblyWrapper<typename T::AssemblyGemm>> - acl_gemm_wrapper = support::cpp14::make_unique<NEGEMMAssemblyWrapper<typename T::AssemblyGemm>>(); - if(acl_gemm_wrapper != nullptr && asm_gemm != nullptr) - { - acl_gemm_wrapper->configure(asm_gemm.get()); - const size_t workspace_size = asm_gemm->get_working_size(); - if(workspace_size) - { - // Allocate workspace - const unsigned int alignment = 4096; - allocate_workspace(workspace_size, workspace, &memory_group, alignment); - asm_glue._workspace = &workspace; - } - - //if we disable this code below in brackets then ConvLayer deadlocks when threads > 1 and - //the shapes are In=1x1x1024 Weights=1x1x1024x1001 Biases=1001 Out=1x1x1001 - { - const unsigned int window_size = asm_gemm->get_window_size(); - if(window_size < num_threads) - { - num_threads = window_size; - asm_gemm->set_nthreads(num_threads); - } - } - - // Check for pre-transposed support - if(asm_gemm->B_pretranspose_required()) - { - // Forcing 128-byte alignment (required by 32-bit kernels) - const unsigned int alignment = 128; - const size_t B_pretranspose_size = asm_gemm->get_B_pretransposed_array_size(); - allocate_workspace(B_pretranspose_size, B_pretranspose, nullptr, alignment); - ARM_COMPUTE_ERROR_ON_NULLPTR(B_pretranspose.buffer()); - asm_glue._pretranspose = &B_pretranspose; - } - - asm_glue._gemm_kernel_asm = std::move(asm_gemm); - asm_glue._optimised_kernel = std::move(acl_gemm_wrapper); - // We need to setup the ptrs in the run() method - asm_glue._a = a; - asm_glue._b = b; - asm_glue._d = d; - return true; - } - return false; -} -} -#endif /* __ARM_ASSEMBLY_HELPER_H__ */ |