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/*
* 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.
*/
#ifdef ENABLE_EXPERIMENTAL_DYNAMIC_FUSION
#include "arm_compute/runtime/experimental/ClCompositeOperator.h"
#include "arm_compute/core/experimental/ClWorkload.h"
#include "arm_compute/core/experimental/Types.h"
#include "src/gpu/cl/kernels/experimental/dynamic_fusion/ClCompositeKernel.h"
#include "support/Cast.h"
namespace arm_compute
{
namespace experimental
{
namespace dynamic_fusion
{
namespace
{
Status add_tensor_to_tensor_pack(int wk_tensor_id, ICLTensor *tensor, const ClWorkload &workload, TensorPackMap &prepare_pack_map, TensorPackMap &run_pack_map)
{
if(tensor == nullptr)
{
return ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Trying to add a nullptr into the tensor packs");
}
const auto bp_tensor_id = workload.tensors.at(wk_tensor_id).kernel_arg.arg_id; // blueprint tensor id
std::vector<ClWorkload::UnitWorkId> uwk_ids{};
const auto src_uwk_ids = workload.graph.src_ops_from_tensor(wk_tensor_id);
const auto dst_uwk_ids = workload.graph.dst_ops_from_tensor(wk_tensor_id);
uwk_ids.insert(uwk_ids.end(), src_uwk_ids.begin(), src_uwk_ids.end());
uwk_ids.insert(uwk_ids.end(), dst_uwk_ids.begin(), dst_uwk_ids.end());
for(auto uwk_id : uwk_ids)
{
TensorPackMap *pack_map = nullptr;
const auto uwk_stage = workload.unit_workloads.at(uwk_id).stage.stage;
switch(uwk_stage)
{
case UnitWorkloadStage::Stage::Run:
pack_map = &run_pack_map;
break;
case UnitWorkloadStage::Stage::Prepare:
pack_map = &prepare_pack_map;
break;
default:
return ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Unsupported workload stage");
}
ITensorPack *tensor_pack = pack_map->find_tensor_pack(uwk_id);
if(tensor_pack == nullptr)
{
pack_map->add_tensor_pack(uwk_id, ITensorPack{ { bp_tensor_id, tensor } });
}
else
{
tensor_pack->add_tensor(bp_tensor_id, tensor);
}
}
return Status{};
}
} // namespace
ITensorPack *TensorPackMap::find_tensor_pack(UnitWorkload::Id uwk_id)
{
auto tensor_pack = _tensor_packs.find(uwk_id);
if(tensor_pack != _tensor_packs.end())
{
return &(tensor_pack->second);
}
return nullptr;
}
ITensorPack &TensorPackMap::get_tensor_pack(UnitWorkload::Id uwk_id)
{
return _tensor_packs.at(uwk_id);
}
void TensorPackMap::add_tensor_pack(UnitWorkload::Id uwk_id, const ITensorPack &tensor_pack)
{
_tensor_packs[uwk_id] = tensor_pack;
}
Status bind_tensors(ClAuxTensorData &aux_tensor_data, TensorPackMap &prepare_pack_map, TensorPackMap &run_pack_map, const ClWorkload &workload, const OpTensorBinding &op_tensors)
{
for(auto tensor : workload.tensors)
{
const auto wk_tensor_id = tensor.first; // workload tensor id
ICLTensor *tensor_object = nullptr;
if(tensor.second.memory_type == MemoryType::Core)
{
const auto op_tensor_id = workload.op_tensor_id_lut.at(wk_tensor_id);
auto op_tensor_find = op_tensors.find(op_tensor_id);
if(op_tensor_find == op_tensors.end())
{
return ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Cannot find binding for some operator tensor");
}
tensor_object = utils::cast::polymorphic_downcast<ICLTensor *>(op_tensor_find->second);
}
else if(tensor.second.memory_type == MemoryType::Auxiliary)
{
// Create aux tensor CLTensor object
const TensorInfo tensor_info = *tensor.second.info;
const auto memory_info = tensor.second.memory_info;
tensor_object = aux_tensor_data.add_aux_tensor(wk_tensor_id, tensor_info, memory_info);
}
else
{
return ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Unsupported tensor memory type");
}
const auto st = add_tensor_to_tensor_pack(wk_tensor_id, tensor_object, workload, prepare_pack_map, run_pack_map);
ARM_COMPUTE_RETURN_ON_ERROR(st);
}
return Status{};
}
CLTensor *ClAuxTensorData::add_aux_tensor(int tensor_id, const ITensorInfo &tensor_info, const AuxMemoryInfo &memory_info)
{
auto find_tensor_pair = _owned_tensors.find(tensor_id);
if(find_tensor_pair == _owned_tensors.end())
{
return find_tensor_pair->second.get();
}
else
{
auto tensor = std::make_unique<CLTensor>();
auto inserted_pair = _owned_tensors.emplace(tensor_id, std::move(tensor)).first;
auto new_tensor = inserted_pair->second.get();
_tensors.emplace_back(new_tensor, tensor_info, memory_info);
return new_tensor;
}
}
std::vector<ClAuxTensorData::DataView> &ClAuxTensorData::get_tensors()
{
return _tensors;
}
struct ClCompositeOperator::Implementation
{
std::map<UnitWorkload::Id, std::unique_ptr<ClCompositeKernel>> _kernels{};
std::map<UnitWorkload::Id, std::unique_ptr<ClCompositeKernel>> _kernels_prep{};
ClWorkload _workload{};
bool _is_prepared{ false };
};
ClCompositeOperator::ClCompositeOperator()
: _impl{ std::make_unique<Implementation>() }
{
}
ClCompositeOperator::~ClCompositeOperator() = default;
void ClCompositeOperator::configure(const CLCompileContext &ctx, const ClWorkload &workload)
{
ARM_COMPUTE_ERROR_THROW_ON(ClCompositeOperator::validate(workload));
_impl->_workload = workload;
// Traverse workloads in topological order
const auto sorted = workload.graph.topological_sort().second;
for(const auto &node : sorted)
{
auto work = workload.unit_workloads.at(node.op);
auto stage = work.stage.stage;
auto k = std::make_unique<ClCompositeKernel>();
k->configure(ctx, work.code);
switch(stage)
{
case UnitWorkloadStage::Stage::Run:
_impl->_kernels.emplace(work.id, std::move(k));
break;
case UnitWorkloadStage::Stage::Prepare:
_impl->_kernels_prep.emplace(work.id, std::move(k));
break;
default:
ARM_COMPUTE_ERROR("Invalid stage");
}
break;
}
}
Status ClCompositeOperator::validate(const ClWorkload &workload)
{
return workload.status;
}
void ClCompositeOperator::prepare(TensorPackMap &tensor_pack_map)
{
if(!_impl->_is_prepared)
{
for(auto &id_kernel_pair : _impl->_kernels_prep)
{
const bool flush_queue = false;
const auto uwk_id = id_kernel_pair.first;
auto kernel = id_kernel_pair.second.get();
CLScheduler::get().enqueue_op(*kernel, tensor_pack_map.get_tensor_pack(uwk_id), ClExecutionDescriptor{}, flush_queue);
}
_impl->_is_prepared = true;
}
}
void ClCompositeOperator::run(TensorPackMap &tensor_pack_map)
{
ARM_COMPUTE_ERROR_ON_MSG(!_impl->_is_prepared, "Operator is not prepared");
for(auto &id_kernel_pair : _impl->_kernels)
{
// Flush the command queue on the last kernel
const bool flush_queue = false;
const auto uwk_id = id_kernel_pair.first;
auto kernel = id_kernel_pair.second.get();
CLScheduler::get().enqueue_op(*kernel, tensor_pack_map.get_tensor_pack(uwk_id), ClExecutionDescriptor{}, flush_queue);
}
}
} // namespace dynamic_fusion
} // namespace experimental
} // namespace arm_compute
#endif /* ENABLE_EXPERIMENTAL_DYNAMIC_FUSION */
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