| /* |
| * Copyright (c) 2022-2023 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/dynamic_fusion/sketch/gpu/GpuWorkloadContext.h" |
| #include "arm_compute/core/CL/CLCompileContext.h" |
| #include "src/dynamic_fusion/sketch/gpu/GpuWorkloadContextImpl.h" |
| |
| namespace arm_compute |
| { |
| namespace experimental |
| { |
| namespace dynamic_fusion |
| { |
| GpuWorkloadContext::GpuWorkloadContext(CLCompileContext *cl_compile_ctx) |
| : _impl{ std::make_unique<Impl>(GpuLanguage::OpenCL, cl_compile_ctx) } |
| { |
| } |
| |
| GpuWorkloadContext::~GpuWorkloadContext() = default; |
| |
| GpuWorkloadContext::GpuWorkloadContext(GpuWorkloadContext &&other) = default; |
| |
| GpuWorkloadContext &GpuWorkloadContext::operator=(GpuWorkloadContext &&other) = default; |
| |
| GpuTarget GpuWorkloadContext::gpu_target() const |
| { |
| return _impl->cl_compile_context()->get_gpu_target(); |
| } |
| |
| GpuLanguage GpuWorkloadContext::gpu_language() const |
| { |
| return _impl->gpu_language(); |
| } |
| |
| const CLCompileContext *GpuWorkloadContext::cl_compile_context() const |
| { |
| return _impl->cl_compile_context(); |
| } |
| |
| void GpuWorkloadContext::register_user_tensor(ITensorInfo &tensor_info) |
| { |
| _impl->register_user_tensor(tensor_info); |
| } |
| |
| GpuWorkloadContext::Impl &GpuWorkloadContext::implementation() |
| { |
| return *_impl; |
| } |
| |
| const GpuWorkloadContext::Impl &GpuWorkloadContext::implementation() const |
| { |
| return *_impl; |
| } |
| |
| GpuWorkloadContext::Impl::Impl(GpuLanguage gpu_language, CLCompileContext *cl_compile_ctx) |
| : _gpu_language(gpu_language), _cl_compile_ctx(cl_compile_ctx), _next_tensor_id(1), _mem_map(), _managed_tensor_info() |
| { |
| } |
| |
| GpuLanguage GpuWorkloadContext::Impl::gpu_language() const |
| { |
| return _gpu_language; |
| } |
| |
| const CLCompileContext *GpuWorkloadContext::Impl::cl_compile_context() const |
| { |
| return _cl_compile_ctx; |
| } |
| |
| const MemoryDescriptorMap &GpuWorkloadContext::Impl::mem_map() const |
| { |
| return _mem_map; |
| } |
| |
| void GpuWorkloadContext::Impl::register_user_tensor(ITensorInfo &tensor_info) |
| { |
| ARM_COMPUTE_ERROR_ON(tensor_info.has_valid_id()); |
| |
| const auto tensor_id = next_tensor_id(); |
| |
| tensor_info.set_id(tensor_id); |
| _mem_map[tensor_id] = MemoryDescriptor{ MemoryType::User }; |
| // Save a *copy* of the user tensor info in workload context for future reference |
| // Note that this means if the user modifies the @p tensor_info, the change will not be reflected in the context |
| _managed_tensor_info.emplace(tensor_info.id(), std::make_unique<TensorInfo>(tensor_info)); |
| } |
| |
| ITensorInfo *GpuWorkloadContext::Impl::create_virtual_tensor() |
| { |
| auto tensor_info = std::make_unique<TensorInfo>(); |
| const auto tensor_id = -next_tensor_id(); |
| tensor_info->set_id(tensor_id); |
| _mem_map[tensor_id] = MemoryDescriptor{ MemoryType::Virtual }; |
| auto inserted = _managed_tensor_info.emplace(tensor_info->id(), std::move(tensor_info)); |
| return inserted.first->second.get(); |
| } |
| |
| ITensorInfo *GpuWorkloadContext::Impl::create_auxiliary_tensor(const ITensorInfo &itensor_info) |
| { |
| auto tensor_info = std::make_unique<TensorInfo>(itensor_info); |
| const auto tensor_id = next_tensor_id(); |
| tensor_info->set_id(tensor_id); |
| _mem_map[tensor_id] = MemoryDescriptor{ MemoryType::Auxiliary, AuxMemoryInfo{ tensor_info->total_size() } }; |
| auto inserted = _managed_tensor_info.emplace(tensor_info->id(), std::move(tensor_info)); |
| return inserted.first->second.get(); |
| } |
| |
| ITensorInfo *GpuWorkloadContext::Impl::get_tensor_info(ITensorInfo::Id id) |
| { |
| return _managed_tensor_info.at(id).get(); |
| } |
| |
| const ITensorInfo *GpuWorkloadContext::Impl::get_tensor_info(ITensorInfo::Id id) const |
| { |
| return _managed_tensor_info.at(id).get(); |
| } |
| |
| ITensorInfo::Id GpuWorkloadContext::Impl::next_tensor_id() |
| { |
| return _next_tensor_id++; |
| } |
| |
| } // namespace dynamic_fusion |
| } // namespace experimental |
| } // namespace arm_compute |