/* * Copyright (c) 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 "GpuKernelComponentGraph.h" #include "arm_compute/dynamic_fusion/sketch/MemoryDescriptor.h" namespace arm_compute { namespace experimental { namespace dynamic_fusion { namespace { /** Automatically create memory descriptors for all tensors in the graph * * @param[in] tensors @ref ITensorInfo map * @param[in] graph @ref DependencyGraph of which the @p tensors are a part * * @return MemoryDescriptorMap An assignment map of @ref MemoryDescriptors for each ITensorInfo in the graph */ MemoryDescriptorMap assign_memory_descriptors(const std::map tensors, const DependencyGraph &graph) { const auto all_tensors = graph.all_tensors(); const auto src_tensors = graph.global_src_tensors(); const auto dst_tensors = graph.global_dst_tensors(); const auto interm_tensors = graph.intermediate_tensors(); MemoryDescriptorMap mem_map{}; for(auto t_id : all_tensors) { const auto &tensor = tensors.at(t_id); // Only global src and dst tensors to the entire component graph are "User" tensors, which are user-specified memories if(is_in(t_id, src_tensors) || is_in(t_id, dst_tensors)) { mem_map[t_id] = MemoryDescriptor{ MemoryType::User }; } else if(is_in(t_id, interm_tensors)) { mem_map[t_id] = MemoryDescriptor { MemoryType::NoAlloc }; } else { AuxMemoryInfo aux_mem_info{ tensor->total_size() }; mem_map[t_id] = MemoryDescriptor{ MemoryType::Auxiliary, aux_mem_info }; } } return mem_map; } } // namespace std::vector GpuKernelComponentGraph::get_tensor_ids(const std::vector tensors) { std::vector tensor_ids{}; std::transform( std::begin(tensors), std::end(tensors), std::back_inserter(tensor_ids), [](const auto & t) { return t->id(); }); return tensor_ids; } GpuKernelComponentGraph::GpuKernelComponentGraph(GpuComponentServices *services) : _services{ services }, _components{}, _tensors{}, _dependency_graph{} { } GpuKernelComponentStream GpuKernelComponentGraph::fuse() const { // Obtain memory descriptor map const auto mem_map = assign_memory_descriptors(_tensors, _dependency_graph); GpuKernelComponentStream stream{ _services, mem_map }; const auto op_seq = _dependency_graph.build_operators_sequence(); stream.new_component_group(); for(auto op : op_seq) { const auto component = _components.at(op.op).get(); const auto success = stream.add_component(component); ARM_COMPUTE_ERROR_ON(!success); ARM_COMPUTE_UNUSED(success); } return stream; } } // namespace dynamic_fusion } // namespace experimental } // namespace arm_compute