| /* | |
| * Copyright (c) 2017-2022 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/runtime/CL/functions/CLGEMM.h" | |
| #include "arm_compute/core/CL/CLHelpers.h" | |
| #include "arm_compute/core/CL/CLKernelLibrary.h" | |
| #include "arm_compute/core/Helpers.h" | |
| #include "arm_compute/core/KernelDescriptors.h" | |
| #include "arm_compute/core/TensorInfo.h" | |
| #include "arm_compute/core/Types.h" | |
| #include "arm_compute/core/Utils.h" | |
| #include "src/core/helpers/MemoryHelpers.h" | |
| #include "src/gpu/cl/operators/ClGemm.h" | |
| namespace arm_compute | |
| { | |
| using namespace arm_compute::experimental; | |
| using OperatorType = opencl::ClGemm; | |
| struct CLGEMM::Impl | |
| { | |
| const ICLTensor *b{ nullptr }; | |
| std::unique_ptr<OperatorType> op{ nullptr }; | |
| MemoryGroup memory_group{}; | |
| IWeightsManager *weights_manager{ nullptr }; | |
| ITensorPack run_pack{}; | |
| ITensorPack prep_pack{}; | |
| MemoryRequirements aux_mem_req{}; | |
| WorkspaceData<CLTensor> workspace_tensors{}; | |
| bool is_prepared{ false }; | |
| }; | |
| CLGEMM::CLGEMM(std::shared_ptr<IMemoryManager> memory_manager, IWeightsManager *weights_manager) | |
| : _impl(std::make_unique<Impl>()) | |
| { | |
| _impl->memory_group = MemoryGroup(memory_manager); | |
| _impl->weights_manager = weights_manager; | |
| } | |
| CLGEMM::~CLGEMM() = default; | |
| void CLGEMM::configure(const ICLTensor *a, const ICLTensor *b, const ICLTensor *c, ICLTensor *output, float alpha, float beta, const GEMMInfo &gemm_info) | |
| { | |
| configure(CLKernelLibrary::get().get_compile_context(), a, b, c, output, alpha, beta, gemm_info); | |
| } | |
| void CLGEMM::configure(const CLCompileContext &compile_context, const ICLTensor *a, const ICLTensor *b, const ICLTensor *c, ICLTensor *output, float alpha, float beta, const GEMMInfo &gemm_info) | |
| { | |
| ARM_COMPUTE_ERROR_ON_NULLPTR(a, b, output); | |
| _impl->b = b; | |
| _impl->op = std::make_unique<OperatorType>(); | |
| _impl->is_prepared = gemm_info.retain_internal_weights(); | |
| _impl->op->configure(compile_context, a->info(), b->info(), c != nullptr ? c->info() : nullptr, output->info(), alpha, beta, gemm_info); | |
| _impl->aux_mem_req = _impl->op->workspace(); | |
| // Manage/allocate auxilairy tensors | |
| if(_impl->is_prepared) | |
| { | |
| _impl->run_pack.add_const_tensor(ACL_SRC_0, a); | |
| _impl->run_pack.add_tensor(ACL_DST, output); | |
| } | |
| else | |
| { | |
| _impl->run_pack = { { ACL_SRC_0, a }, { ACL_SRC_2, c }, { ACL_DST, output } }; | |
| _impl->prep_pack = { { ACL_SRC_1, _impl->b } }; | |
| _impl->workspace_tensors = manage_workspace<CLTensor>(_impl->op->workspace(), _impl->memory_group, _impl->run_pack, _impl->prep_pack); | |
| } | |
| } | |
| Status CLGEMM::validate(const ITensorInfo *a, const ITensorInfo *b, const ITensorInfo *c, const ITensorInfo *output, float alpha, float beta, const GEMMInfo &gemm_info) | |
| { | |
| return OperatorType::validate(a, b, c, output, alpha, beta, gemm_info); | |
| } | |
| void CLGEMM::run() | |
| { | |
| prepare(); | |
| MemoryGroupResourceScope scope_mg(_impl->memory_group); | |
| _impl->op->run(_impl->run_pack); | |
| } | |
| void CLGEMM::prepare() | |
| { | |
| if(!_impl->is_prepared) | |
| { | |
| _impl->op->prepare(_impl->prep_pack); | |
| auto has_reshape = std::find_if(_impl->aux_mem_req.begin(), | |
| _impl->aux_mem_req.end(), | |
| [](const MemoryInfo & m) -> bool { return m.lifetime == MemoryLifetime::Persistent; }); | |
| if(has_reshape != std::end(_impl->aux_mem_req)) | |
| { | |
| _impl->b->mark_as_unused(); | |
| } | |
| else | |
| { | |
| // Pack the B matrix to be used as the underlying GEMM performs no reshapes | |
| _impl->run_pack.add_const_tensor(ACL_SRC_1, _impl->b); | |
| } | |
| _impl->is_prepared = true; | |
| } | |
| } | |
| } // namespace arm_compute |