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Diffstat (limited to 'runtimes/neurun/backend/acl_common/TemplTensorBuilder.h')
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diff --git a/runtimes/neurun/backend/acl_common/TemplTensorBuilder.h b/runtimes/neurun/backend/acl_common/TemplTensorBuilder.h new file mode 100644 index 000000000..df9fa8c2a --- /dev/null +++ b/runtimes/neurun/backend/acl_common/TemplTensorBuilder.h @@ -0,0 +1,617 @@ +/* + * Copyright (c) 2019 Samsung Electronics Co., Ltd. All Rights Reserved + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +#ifndef __NEURUN_BACKEND_ACL_COMMON_TEMPL_TENSOR_BUILDER_H__ +#define __NEURUN_BACKEND_ACL_COMMON_TEMPL_TENSOR_BUILDER_H__ + +#include <memory> +#include <queue> + +#include <arm_compute/core/Types.h> +#include <backend/ITensorBuilder.h> +#include "model/OperandIndexMap.h" +#include "AclTensorManager.h" +#include "cpp14/memory.h" +#include <util/Utils.h> + +namespace neurun +{ +namespace backend +{ +namespace acl_common +{ + +enum class UsesType +{ + FIRST, + LAST +}; + +template <typename T_ITensor, typename T_Tensor, typename T_SubTensor, typename T_Object> +class TemplTensorBuilder : public ITensorBuilder +{ +public: + using T_AclTensorManager = AclTensorManager<T_ITensor, T_Tensor, T_SubTensor, T_Object>; + + TemplTensorBuilder(T_AclTensorManager *tensor_mgr); + + /** + * @brief Register tensor information to allocate on ACL-CL backend + * @param[in] ind Operand index + * @param[in] info Tensor information + * @param[in] layout Tensor data layout + */ + void registerTensorInfo(const model::OperandIndex &ind, const model::OperandInfo &info, + model::Layout frontend_layout, model::Layout backend_layout, + bool as_const) override; + /** + * @brief Register subtensor information to allocate on ACL-CL backend + * @param[in] ind Operand index + * @param[in] info Tensor information + */ + void registerSubTensorInfo(const model::OperandIndex &ind, + const compiler::SubTensorInfo &info) override; + + void notifyFirstUse(const model::OperandIndex &) override; + void notifyLastUse(const model::OperandIndex &) override; + + void prepare(void) override; + void allocate(void) override; // TODO Remove this + void allocateConsts() override; + void allocateNonconsts() override; + void postFunctionPrepare() override; + void finalize() override; + + std::shared_ptr<::neurun::backend::operand::ITensor> + tensorAt(const model::OperandIndex &ind) override; + std::shared_ptr<backend::operand::IObject> wrapTensor(const model::OperandIndex &ind) override; + void iterate(const IterateFunction &fn) override; + + void preVisit(const model::Operation &node) override; + void postVisit(const model::Operation &node) override; + + std::unique_ptr<ITensorManager> releaseTensorManager(void) override; + + std::shared_ptr<T_ITensor> at(const ::neurun::model::OperandIndex &ind); + /** + * @brief Check child tensor is allocated as subtensor of parent tensor + * @param[in] parent Index of parent + * @param[in] child Index of child + * @return @c true if child is allocated as subtensor of parent, otherwise @c false + */ + bool isSubTensorOf(const model::OperandIndex &parent, const model::OperandIndex &child); + + void dimCorrection(const model::OperandIndex &index, bool apply_dim_correction); + + T_AclTensorManager *acl_tensor_manager(void) { return _tensor_mgr.get(); } + +private: + void buildTensors(void); + void buildSubtensors(void); + void validate(void); + model::OperandIndex findRootParent(model::OperandIndex index); + +private: + model::OperandIndexMap<model::OperandInfo> _tensor_info_map; + model::OperandIndexMap<compiler::SubTensorInfo> _subtensor_info_map; + model::OperandIndexMap<bool> _apply_dim_correction_map; + model::OperandIndexMap<std::pair<model::Layout, model::Layout>> _tensor_layouts_map; + + std::unique_ptr<T_AclTensorManager> _tensor_mgr; + model::OperandIndexSequence _constants; + + // TODO Consider dividing TensorBuilder into Linear and others + const std::string _executor_str; + + // for linear executor + std::queue<std::pair<UsesType, model::OperandIndex>> _uses_queue; + uint32_t _first_uses_num; + model::OperandIndexMap<bool> _first_uses_visit; + + // for subtensors + model::OperandIndexMap<uint32_t> _parent_def; + model::OperandIndexMap<uint32_t> _parent_uses; +}; + +} // namespace acl_common +} // namespace backend +} // namespace neurun + +#include <cassert> +#include <stack> + +#include "Convert.h" + +#include "util/logging.h" + +namespace neurun +{ +namespace backend +{ +namespace acl_common +{ + +template <typename T_ITensor, typename T_Tensor, typename T_SubTensor, typename T_Object> +TemplTensorBuilder<T_ITensor, T_Tensor, T_SubTensor, T_Object>::TemplTensorBuilder( + T_AclTensorManager *tensor_mgr) + : _tensor_mgr{tensor_mgr}, _executor_str(util::getConfigString(util::config::EXECUTOR)), + _first_uses_num(0) +{ + assert(_tensor_mgr); +} + +template <typename T_ITensor, typename T_Tensor, typename T_SubTensor, typename T_Object> +void TemplTensorBuilder<T_ITensor, T_Tensor, T_SubTensor, T_Object>::registerTensorInfo( + const model::OperandIndex &ind, const model::OperandInfo &info, model::Layout frontend_layout, + model::Layout backend_layout, bool as_const) +{ + assert(_tensor_mgr->constTensors().size() == 0); + assert(_tensor_mgr->nonconstTensors().size() == 0); + + _tensor_info_map.emplace(ind, info); + _apply_dim_correction_map.emplace(ind, true); + _tensor_layouts_map.insert({ind, std::make_pair(frontend_layout, backend_layout)}); + if (as_const) + _constants.append(ind); + + assert(_first_uses_visit.find(ind) == _first_uses_visit.end()); + _first_uses_visit[ind] = false; +} + +template <typename T_ITensor, typename T_Tensor, typename T_SubTensor, typename T_Object> +void TemplTensorBuilder<T_ITensor, T_Tensor, T_SubTensor, T_Object>::registerSubTensorInfo( + const model::OperandIndex &ind, const compiler::SubTensorInfo &info) +{ + assert(_tensor_mgr->constTensors().size() == 0); + assert(_tensor_mgr->nonconstTensors().size() == 0); + + _subtensor_info_map.emplace(ind, info); + _apply_dim_correction_map.emplace(ind, true); + + assert(_first_uses_visit.find(ind) == _first_uses_visit.end()); + _first_uses_visit[ind] = false; + + const auto &parent_ind = info.parent(); + + // parent_def + _parent_def[parent_ind] = 1; + + // parent_use + if (_parent_uses.find(parent_ind) == _parent_uses.end()) + _parent_uses[parent_ind] = 1; // 1 means including parent it-self + _parent_uses[parent_ind]++; +} + +template <typename T_ITensor, typename T_Tensor, typename T_SubTensor, typename T_Object> +void TemplTensorBuilder<T_ITensor, T_Tensor, T_SubTensor, T_Object>::notifyFirstUse( + const model::OperandIndex &ind) +{ + _first_uses_num++; + _uses_queue.emplace(UsesType::FIRST, ind); +} + +template <typename T_ITensor, typename T_Tensor, typename T_SubTensor, typename T_Object> +void TemplTensorBuilder<T_ITensor, T_Tensor, T_SubTensor, T_Object>::notifyLastUse( + const model::OperandIndex &ind) +{ + _uses_queue.emplace(UsesType::LAST, ind); +} + +template <typename T_ITensor, typename T_Tensor, typename T_SubTensor, typename T_Object> +void TemplTensorBuilder<T_ITensor, T_Tensor, T_SubTensor, T_Object>::prepare(void) +{ + buildTensors(); + buildSubtensors(); +} + +template <typename T_ITensor, typename T_Tensor, typename T_SubTensor, typename T_Object> +void TemplTensorBuilder<T_ITensor, T_Tensor, T_SubTensor, T_Object>::allocate(void) +{ + allocateConsts(); + allocateNonconsts(); +} + +template <typename T_ITensor, typename T_Tensor, typename T_SubTensor, typename T_Object> +void TemplTensorBuilder<T_ITensor, T_Tensor, T_SubTensor, T_Object>::allocateConsts(void) +{ + assert(_constants.size() == _tensor_mgr->constTensors().size()); + _tensor_mgr->allocateConsts(); +} + +template <typename T_ITensor, typename T_Tensor, typename T_SubTensor, typename T_Object> +void TemplTensorBuilder<T_ITensor, T_Tensor, T_SubTensor, T_Object>::allocateNonconsts(void) +{ + assert(_tensor_info_map.size() == _tensor_mgr->nonconstTensors().size() + _constants.size()); + _tensor_mgr->allocateNonconsts(); +} + +template <typename T_ITensor, typename T_Tensor, typename T_SubTensor, typename T_Object> +void TemplTensorBuilder<T_ITensor, T_Tensor, T_SubTensor, T_Object>::postFunctionPrepare(void) +{ + _tensor_mgr->tryDeallocConstants(); +} + +template <typename T_ITensor, typename T_Tensor, typename T_SubTensor, typename T_Object> +void TemplTensorBuilder<T_ITensor, T_Tensor, T_SubTensor, T_Object>::finalize(void) +{ + validate(); + _tensor_mgr->allocateInternalBufferManager(); +} + +template <typename T_ITensor, typename T_Tensor, typename T_SubTensor, typename T_Object> +std::shared_ptr<::neurun::backend::operand::ITensor> +TemplTensorBuilder<T_ITensor, T_Tensor, T_SubTensor, T_Object>::tensorAt( + const model::OperandIndex &ind) +{ + return _tensor_mgr->at(ind); +} + +template <typename T_ITensor, typename T_Tensor, typename T_SubTensor, typename T_Object> +std::shared_ptr<backend::operand::IObject> +TemplTensorBuilder<T_ITensor, T_Tensor, T_SubTensor, T_Object>::wrapTensor( + const model::OperandIndex &ind) +{ + return _tensor_mgr->wrapTensor(ind); +} + +template <typename T_ITensor, typename T_Tensor, typename T_SubTensor, typename T_Object> +void TemplTensorBuilder<T_ITensor, T_Tensor, T_SubTensor, T_Object>::iterate( + const IterateFunction &fn) +{ + _tensor_mgr->iterate(fn); +} + +template <typename T_ITensor, typename T_Tensor, typename T_SubTensor, typename T_Object> +std::shared_ptr<T_ITensor> TemplTensorBuilder<T_ITensor, T_Tensor, T_SubTensor, T_Object>::at( + const ::neurun::model::OperandIndex &ind) +{ + return _tensor_mgr->at(ind); +} + +template <typename T_ITensor, typename T_Tensor, typename T_SubTensor, typename T_Object> +bool TemplTensorBuilder<T_ITensor, T_Tensor, T_SubTensor, T_Object>::isSubTensorOf( + const model::OperandIndex &parent, const model::OperandIndex &child) +{ + if (_subtensor_info_map.find(child) == _subtensor_info_map.end()) + { + return false; + } + + auto &subtensors = _tensor_mgr->nonconstSubtensors(); + if (subtensors.find(child) == subtensors.end()) + { + return false; + } + + if (_subtensor_info_map.at(child).parent() != parent) + { + return false; + } + + return true; +} + +template <typename T_ITensor, typename T_Tensor, typename T_SubTensor, typename T_Object> +void TemplTensorBuilder<T_ITensor, T_Tensor, T_SubTensor, T_Object>::dimCorrection( + const model::OperandIndex &index, bool apply_dim_correction) +{ + _apply_dim_correction_map[index] = apply_dim_correction; +} + +template <typename T_ITensor, typename T_Tensor, typename T_SubTensor, typename T_Object> +std::unique_ptr<ITensorManager> +TemplTensorBuilder<T_ITensor, T_Tensor, T_SubTensor, T_Object>::releaseTensorManager(void) +{ + return std::move(_tensor_mgr); +} + +template <typename T_ITensor, typename T_Tensor, typename T_SubTensor, typename T_Object> +void TemplTensorBuilder<T_ITensor, T_Tensor, T_SubTensor, T_Object>::buildTensors(void) +{ + assert(_tensor_mgr->constTensors().size() == 0); + assert(_tensor_mgr->nonconstTensors().size() == 0); + + for (auto &entry : _tensor_info_map) + { + auto ind = entry.first; + const auto &info = entry.second; + // NOTE SubTensor's layout must be the same with layout of parent tensor + const auto &root_parent = findRootParent(ind); + const auto &frontend_layout = _tensor_layouts_map[root_parent].first; + const auto &backend_layout = _tensor_layouts_map[root_parent].second; + auto tensor_info = asTensorInfo(info.shape(), info.typeInfo(), frontend_layout, backend_layout, + _apply_dim_correction_map[ind]); + _tensor_mgr->buildTensor(ind, tensor_info, info.shape().rank(), _constants.contains(ind)); + } +} + +template <typename T_ITensor, typename T_Tensor, typename T_SubTensor, typename T_Object> +void TemplTensorBuilder<T_ITensor, T_Tensor, T_SubTensor, T_Object>::buildSubtensors(void) +{ + // TODO Handle SubTensor(subsumption) + // Currently this TemplTensorBuilder does not have subsumption info yet + // Allocated subtensor will be mapped to _subtensors instead of _tensors + assert(_tensor_mgr->nonconstSubtensors().size() == 0); + + // To make subtensor, parent tensor must be made first + // For this condition, use stack + // 1) Push one subtensor index to stack (iterate subtensors) + // 2) If tensor at stack top is already made, pop and go to 4) + // 3) If tensor pushed at 1) is not made, check parent tensor + // 3-1) If parent tensor is already made, we can make child tensor + // Make child tensor and pop, go to 4) + // 3-2) If parent tensor is not made, we can't make child tensor yet + // Push parent tensor index to stack and return to 4) + // 4) If stack is empty, return to 1), else return to 2) + auto &subtensors = _tensor_mgr->nonconstSubtensors(); + for (auto &entry : _subtensor_info_map) + { + model::OperandIndex ind = entry.first; + + std::stack<model::OperandIndex> stack; + stack.push(ind); + + while (!stack.empty()) + { + const auto current = stack.top(); + const auto &info = _subtensor_info_map.at(current); + + // Already generated SubTensor + if (subtensors.find(current) != subtensors.end()) + { + stack.pop(); + continue; + } + + auto parent = info.parent(); + std::shared_ptr<T_ITensor> parent_tensor = _tensor_mgr->findTensorAsParent(parent); + if (!parent_tensor) + { + // Cannot find allocated parent tensor: allocate parent first + assert(_subtensor_info_map.find(parent) != _subtensor_info_map.end()); + stack.push(parent); + continue; + } + assert(parent_tensor != nullptr); + + // Child's type should be same with parent + assert(info.type().offset() == parent_tensor->info()->quantization_info().offset); + assert(info.type().scale() == parent_tensor->info()->quantization_info().scale); + assert(asDataType(info.type().type()) == parent_tensor->info()->data_type()); + + // NOTE SubTensor's layout must be the same with layout of parent tensor + const auto &root_parent = findRootParent(parent); + const auto &frontend_layout = _tensor_layouts_map[root_parent].first; + const auto &backend_layout = _tensor_layouts_map[root_parent].second; + + auto shape = asTensorShape(info.shape(), frontend_layout, backend_layout, + _apply_dim_correction_map[current]); + ::arm_compute::Coordinates coordinates = + asTensorCoordinate(info.offset(), frontend_layout, backend_layout); + _tensor_mgr->buildSubtensor(parent, current, shape, coordinates, info.shape().rank(), true); + stack.pop(); + } + } +} + +template <typename T_ITensor, typename T_Tensor, typename T_SubTensor, typename T_Object> +void TemplTensorBuilder<T_ITensor, T_Tensor, T_SubTensor, T_Object>::preVisit( + const model::Operation &node) +{ + // For now others executor doesn't need this step + if (_executor_str != "Linear") + { + return; + } + + std::function<void(const model::OperandIndex &ind)> def_handler = + [this, &def_handler](const model::OperandIndex &ind) { + bool is_subtensor = _subtensor_info_map.find(ind) != _subtensor_info_map.end(); + bool is_parent = _parent_def.find(ind) != _parent_def.end(); + if (!is_subtensor && !is_parent) + { + _tensor_mgr->startLifetime(ind); + return; + } + + if (is_parent) + { + if (_parent_def[ind] == 0) + return; + + _parent_def[ind] = 0; + + if (is_subtensor) + { + const auto &it = _parent_def.find(ind); + _parent_def.erase(it); + def_handler(ind); + } + else + { + _tensor_mgr->startLifetime(ind); + } + } + else if (is_subtensor) + { + const model::OperandIndex &parent_ind = _subtensor_info_map.at(ind).parent(); + if (_parent_def[parent_ind] == 0) + return; + def_handler(parent_ind); + } + }; + + // See #5642 + model::OperandIndexMap<bool> outputs_map; + for (const auto &ind : node.getOutputs()) + { + assert(_first_uses_visit.find(ind) != _first_uses_visit.end()); + outputs_map[ind] = _first_uses_visit[ind]; + } + + // outputs_map's all elements are true? + auto outputs_map_all_check = [&outputs_map]() { + return std::all_of(outputs_map.begin(), outputs_map.end(), + [](std::pair<const model::OperandIndex, bool> it) { return it.second; }); + }; + + std::pair<UsesType, model::OperandIndex> peak; + while (!outputs_map_all_check() && (peak = _uses_queue.front()).first == UsesType::FIRST) + { + _uses_queue.pop(); + _first_uses_num--; + + const auto &popped_idx = peak.second; + def_handler(popped_idx); + + outputs_map[popped_idx] = true; + _first_uses_visit[popped_idx] = true; + } +} + +template <typename T_ITensor, typename T_Tensor, typename T_SubTensor, typename T_Object> +void TemplTensorBuilder<T_ITensor, T_Tensor, T_SubTensor, T_Object>::postVisit( + const model::Operation &node) +{ + // For now others executor doesn't need this step + if (_executor_str != "Linear") + { + return; + } + + std::function<void(const model::OperandIndex &ind)> use_handler = + [this, &use_handler](const model::OperandIndex &ind) { + bool is_subtensor = _subtensor_info_map.find(ind) != _subtensor_info_map.end(); + bool is_parent = _parent_uses.find(ind) != _parent_uses.end(); + if (!is_subtensor && !is_parent) + { + _tensor_mgr->finishLifetime(ind); + return; + } + + // This handler shall be executed by the linear executor so that + // The parent operand will always be done after the subtensor + if (is_parent) + { + --_parent_uses[ind]; + assert(_parent_uses[ind] == 0); + + if (is_subtensor) + { + const auto &it = _parent_uses.find(ind); + _parent_uses.erase(it); + use_handler(ind); + } + else + { + _tensor_mgr->finishLifetime(ind); + } + } + else if (is_subtensor) + { + const model::OperandIndex &parent_ind = _subtensor_info_map.at(ind).parent(); + --_parent_uses[parent_ind]; + assert(_parent_uses[parent_ind] > 0); + } + }; + + // See #5642 + const auto &inputs = node.getInputs(); + std::pair<UsesType, model::OperandIndex> peak; + while ((peak = _uses_queue.front()).first == UsesType::LAST) + { + const auto &popped_idx = peak.second; + if (inputs.contains(popped_idx)) + { + _uses_queue.pop(); + use_handler(popped_idx); + } + else + { + break; + } + } + + if (_first_uses_num == 0) + { + while (!_uses_queue.empty()) + { + peak = _uses_queue.front(); + assert(peak.first == UsesType::LAST); + + _uses_queue.pop(); + + use_handler(peak.second); + } + } +} + +template <typename T_ITensor, typename T_Tensor, typename T_SubTensor, typename T_Object> +void TemplTensorBuilder<T_ITensor, T_Tensor, T_SubTensor, T_Object>::validate(void) +{ + // For now others executor doesn't need this step + if (_executor_str != "Linear") + { + return; + } + + for (auto it : _tensor_info_map) + { + assert(_first_uses_visit.find(it.first) != _first_uses_visit.end()); + assert(_first_uses_visit[it.first]); + } + + for (auto it : _subtensor_info_map) + { + assert(_first_uses_visit.find(it.first) != _first_uses_visit.end()); + assert(_first_uses_visit[it.first]); + } + + for (auto it : _tensor_layouts_map) + { + assert(_first_uses_visit.find(it.first) != _first_uses_visit.end()); + assert(_first_uses_visit[it.first]); + UNUSED_RELEASE(it); + } + + assert(_uses_queue.size() == 0); + assert(_first_uses_num == 0); + + assert(std::all_of( + _parent_def.begin(), _parent_def.end(), + [](std::pair<const model::OperandIndex, uint32_t> it) { return it.second == 0; })); + + assert(std::all_of( + _parent_uses.begin(), _parent_uses.end(), + [](std::pair<const model::OperandIndex, uint32_t> it) { return it.second == 0; })); +} + +template <typename T_ITensor, typename T_Tensor, typename T_SubTensor, typename T_Object> +model::OperandIndex TemplTensorBuilder<T_ITensor, T_Tensor, T_SubTensor, T_Object>::findRootParent( + model::OperandIndex ind) +{ + if (_subtensor_info_map.find(ind) == _subtensor_info_map.end()) + return ind; + + const auto &parent_ind = _subtensor_info_map.at(ind).parent(); + return findRootParent(parent_ind); +} + +} // namespace acl_common +} // namespace backend +} // namespace neurun + +#endif // __NEURUN_BACKEND_ACL_COMMON_TEMPL_TENSOR_BUILDER_H__ |