forked from huawei/mindspore2022
223 lines
9.0 KiB
C++
223 lines
9.0 KiB
C++
/**
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* Copyright 2019-2021 Huawei Technologies Co., Ltd
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#ifndef MINDSPORE_CCSRC_MINDDATA_DATASET_ENGINE_EXECUTION_TREE_H_
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#define MINDSPORE_CCSRC_MINDDATA_DATASET_ENGINE_EXECUTION_TREE_H_
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#include <functional>
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#include <memory>
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#include <stack>
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#include <string>
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#include <vector>
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#ifndef ENABLE_ANDROID
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#if !defined(_WIN32) && !defined(_WIN64) && !defined(__APPLE__)
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#include <sys/sysinfo.h>
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#include <opencv2/imgproc/imgproc.hpp>
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#endif
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#endif
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#include "minddata/dataset/engine/datasetops/dataset_op.h"
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#include "minddata/dataset/util/status.h"
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#include "mindspore/ccsrc/minddata/dataset/engine/perf/profiling.h"
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namespace mindspore {
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namespace dataset {
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// Forward declares
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class TaskGroup;
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class DatasetOp;
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class Pass;
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using OptPass = std::vector<std::unique_ptr<Pass>>;
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class ExecutionTree {
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public:
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// State flags for the lifecycle of the tree
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enum TreeState {
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kDeTStateInit = 0, // The freshly initialized state after construction
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kDeTStateBuilding, // The tree is being built, nodes are being added
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kDeTStatePrepared, // The tree has been prepared and is ready to be launched
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kDeTStateExecuting, // The tree has been launched and is executing
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kDeTStateEpochEnd, // The tree has been received end of epoch signal, just for profiling
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kDeTStateFinished // The tree has been drained, dataset iterator received EOF
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};
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class Iterator {
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public:
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// Constructor
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// @param root The root node to start iterating from
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explicit Iterator(const std::shared_ptr<DatasetOp> &root = nullptr);
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// Destructor
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~Iterator() {}
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Iterator &operator++() {
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++ind_;
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return *this;
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} // prefix ++ overload
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Iterator operator++(int) {
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Iterator it = *this;
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it.ind_ = ind_;
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ind_++;
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return it;
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} // post-fix ++ overload
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Iterator &operator--() {
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--ind_;
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return *this;
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} // prefix -- overload
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Iterator operator--(int) {
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Iterator it = *this;
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it.ind_ = ind_;
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ind_--;
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return it;
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} // post-fix -- overload
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DatasetOp &operator*() { return *nodes_[ind_]; } // dereference operator
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std::shared_ptr<DatasetOp> operator->() { return nodes_[ind_]; }
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// getter function
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// @return Shared pointer to the current operator
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std::shared_ptr<DatasetOp> get() { return nodes_[ind_]; }
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bool operator==(const Iterator &rhs) { return nodes_[ind_] == rhs.nodes_[rhs.ind_]; }
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bool operator!=(const Iterator &rhs) { return nodes_[ind_] != rhs.nodes_[rhs.ind_]; }
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int32_t NumNodes() { return nodes_.size(); }
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private:
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int32_t ind_; // the cur node our Iterator points to
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std::vector<std::shared_ptr<DatasetOp>> nodes_; // store the nodes in post order
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void PostOrderTraverse(const std::shared_ptr<DatasetOp> &);
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};
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// Constructor
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ExecutionTree();
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// Destructor
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~ExecutionTree();
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/// \brief Associates a DatasetOp with this tree. This assigns a valid node id to the operator and
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/// provides it with a link to the tree. A node cannot form any relationships (parent/child) with
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/// other nodes unless they are associated with the same tree.
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/// \param op - The operator to associate
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/// \return Status The status code returned
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Status AssociateNode(const std::shared_ptr<DatasetOp> &op);
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/// \brief Set the root node of the tree
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/// \param op - The operator to assign as root
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/// \return Status The status code returned
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Status AssignRoot(const std::shared_ptr<DatasetOp> &op);
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/// \brief Start the execution of the tree
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/// \return Status The status code returned
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Status Launch();
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/// /brief A print method typically used for debugging
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/// \param out - The output stream to write output to
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void Print(std::ostream &out, const std::shared_ptr<DatasetOp> &op = nullptr) const;
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/// \brief Return an iterator positioned at the start
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/// \return Iterator - The iterator
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ExecutionTree::Iterator begin(const std::shared_ptr<DatasetOp> &root = nullptr) const {
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return Iterator(root == nullptr ? root_ : root);
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}
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/// \brief Return an iterator positioned at the end
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/// \return Iterator - The iterator
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ExecutionTree::Iterator end() const { return Iterator(nullptr); }
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/// \brief << Stream output operator overload
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/// \notes This allows you to write the debug print info using stream operators
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/// \param out - reference to the output stream being overloaded
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/// \param exe_tree - reference to the execution tree to display
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/// \return - the output stream must be returned
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friend std::ostream &operator<<(std::ostream &out, ExecutionTree &exe_tree) {
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exe_tree.Print(out);
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return out;
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}
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/// \brief Given the number of workers, launches the worker entry function for each. Essentially a
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/// wrapper for the TaskGroup handling that is stored inside the execution tree.
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/// \param num_workers - The number of workers to launch
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/// \param func - The function entry point that workers will execute
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/// \param name - The description of worker to launch
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/// \param op_id - The id of corresponding operator, if not inherit from dataset op then it is -1.
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/// \return Status The status code returned
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Status LaunchWorkers(int32_t num_workers, std::function<Status(uint32_t)> func, std::string name = "",
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int32_t operator_id = -1);
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/// \brief Getter method
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/// \return shared_ptr to the root operator
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std::shared_ptr<DatasetOp> root() const { return root_; }
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/// \brief The prepare phase walks the tree in post-order to perform modifications to get it ready for execution.
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/// \return Status The status code returned
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Status Prepare();
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/// \brief Return the pointer to the TaskGroup
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/// \return raw pointer to the TaskGroup
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TaskGroup *const AllTasks() const { return tg_.get(); }
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/// \brief Return if the ExecutionTree is at end of epoch status
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/// \return bool - true is ExecutionTree is end of epoch status
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bool IsEpochEnd() const { return tree_state_ == TreeState::kDeTStateEpochEnd; }
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/// \brief Set the ExecutionTree to EOE state
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void SetEpochEnd() { tree_state_ = TreeState::kDeTStateEpochEnd; }
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/// \brief Set the ExecutionTree to executing state
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void SetExecuting() { tree_state_ = TreeState::kDeTStateExecuting; }
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/// \brief Set the ExecutionTree to Finished state.
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void SetFinished() { tree_state_ = TreeState::kDeTStateFinished; }
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/// \brief Return if the ExecutionTree is finished (iterator receives EOF).
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/// \return Bool - true is ExecutionTree is finished
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bool isFinished() const { return tree_state_ == TreeState::kDeTStateFinished; }
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/// \brief Return if the ExecutionTree is ready.
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/// \return Bool - true is ExecutionTree is ready
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bool isPrepared() const {
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return tree_state_ == TreeState::kDeTStatePrepared || tree_state_ == TreeState::kDeTStateExecuting ||
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tree_state_ == TreeState::kDeTStateFinished;
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}
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/// \brief Getter for profiling manager, no ownership
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ProfilingManager *GetProfilingManager() { return profiling_manager_.get(); }
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private:
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/// \brief A helper functions for doing the recursive printing
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/// \param dataset_op - The dataset op to print
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/// \param indent - an indent string for aligning child levels in output
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/// \param last - an indicator if it's the last child or not
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/// \param detailed - should it display the detailed node output or the summary line
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void PrintNode(std::ostream &out, const std::shared_ptr<DatasetOp> &dataset_op, std::string indent, bool last,
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bool detailed) const;
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std::unique_ptr<TaskGroup> tg_; // Class for worker management
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std::shared_ptr<DatasetOp> root_; // The root node of the tree
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int32_t id_count_; // Counter for generating operator id's
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uint32_t prepare_flags_; // Flags used during tree prepare
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TreeState tree_state_; // Tracking the current tree state
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std::unique_ptr<ProfilingManager> profiling_manager_; // Profiling manager
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#if defined(ENABLE_GPUQUE) || defined(ENABLE_TDTQUE)
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// This rank_id is for numa and device_queue, one process work with only one rank_id,
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// for standalone scenario, this rank_id may come from env 'CUDA_VISIBLE_DEVICES',
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// but for distribute scenario, this rank_id come from _get_global_rank() in python
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int32_t rank_id_;
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bool numa_enable_;
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void *handle_;
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#endif
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};
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} // namespace dataset
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} // namespace mindspore
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#endif // MINDSPORE_CCSRC_MINDDATA_DATASET_ENGINE_EXECUTION_TREE_H_
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