!40 Synchronize with latest Ascend software suite 17 Jun 2020
Merge pull request !40 from yanghaoran/masterpull/40/MERGE
mindspore-ci-bot
5 years ago
committed by
Gitee
commit
1c2672868f
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/**
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* Copyright 2019-2020 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 INC_FRAMEWORK_GE_RUNTIME_DAVINCI_MODEL_H_
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#define INC_FRAMEWORK_GE_RUNTIME_DAVINCI_MODEL_H_
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#include <memory>
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#include <vector>
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#include "ge_runtime/op_info.h"
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#include "ge_runtime/task_info.h"
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namespace ge {
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namespace model_runner {
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class DavinciModel {
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public:
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DavinciModel(const std::vector<std::shared_ptr<TaskInfo>> &task_info_list,
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const std::vector<std::shared_ptr<OpInfo>> &data_info_list,
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const std::vector<std::shared_ptr<OpInfo>> &output_info_list,
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const std::vector<std::shared_ptr<OpInfo>> &constant_info_list,
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const std::vector<model_runner::OpInfoPtr> &variable_info_list,
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const std::vector<uint32_t> &wait_active_stream_list,
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const std::vector<uint32_t> &force_copy_stream_list, uint64_t mem_size = 0, uint64_t weight_size = 0,
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uint64_t var_size = 0, uintptr_t logic_mem_base = 0, uintptr_t logic_weight_base = 0,
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uintptr_t logic_var_base = 0, uint32_t stream_num = 0, uint32_t batch_num = 0, uint32_t event_num = 0,
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int32_t priority = 0)
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: task_info_list_(task_info_list),
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data_info_list_(data_info_list),
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output_info_list_(output_info_list),
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constant_info_list_(constant_info_list),
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variable_info_list_(variable_info_list),
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wait_active_stream_list_(wait_active_stream_list),
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force_copy_stream_list_(force_copy_stream_list),
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mem_size_(mem_size),
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weight_size_(weight_size),
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var_size_(var_size),
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logic_mem_base_(logic_mem_base),
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logic_weight_base_(logic_weight_base),
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logic_var_base_(logic_var_base),
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stream_num_(stream_num),
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batch_num_(batch_num),
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event_num_(event_num),
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priority_(priority) {}
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~DavinciModel() {}
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uint64_t GetMemSize() const { return mem_size_; }
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uint64_t GetWeightSize() const { return weight_size_; }
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uint64_t GetVarSize() const { return var_size_; }
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uintptr_t GetLogicMemBase() const { return logic_mem_base_; }
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uintptr_t GetLogicWeightBase() const { return logic_weight_base_; }
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uintptr_t GetLogicVarBase() const { return logic_var_base_; }
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uint32_t GetStreamNum() const { return stream_num_; }
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uint32_t GetBatchNum() const { return batch_num_; }
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uint32_t GetEventNum() const { return event_num_; }
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const std::vector<uint32_t> &GetWaitActiveStreams() const { return wait_active_stream_list_; }
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const std::vector<uint32_t> &GetForceCopyStreams() const { return force_copy_stream_list_; }
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int32_t GetPriority() const { return priority_; }
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const std::vector<std::shared_ptr<TaskInfo>> &GetTaskInfoList() const { return task_info_list_; }
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const std::vector<std::shared_ptr<OpInfo>> &GetDataInfoList() const { return data_info_list_; }
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const std::vector<std::shared_ptr<OpInfo>> &GetOutputInfoList() const { return output_info_list_; }
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const std::vector<std::shared_ptr<OpInfo>> &GetConstantInfoList() const { return output_info_list_; }
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const std::vector<model_runner::OpInfoPtr> &GetVariableInfoList() const { return variable_info_list_; }
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private:
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std::vector<std::shared_ptr<TaskInfo>> task_info_list_;
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std::vector<std::shared_ptr<OpInfo>> data_info_list_;
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std::vector<std::shared_ptr<OpInfo>> output_info_list_;
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std::vector<std::shared_ptr<OpInfo>> constant_info_list_;
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std::vector<model_runner::OpInfoPtr> variable_info_list_;
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std::vector<uint32_t> wait_active_stream_list_;
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std::vector<uint32_t> force_copy_stream_list_;
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uint64_t mem_size_;
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uint64_t weight_size_;
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uint64_t var_size_;
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uintptr_t logic_mem_base_;
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uintptr_t logic_weight_base_;
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uintptr_t logic_var_base_;
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uint32_t stream_num_;
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uint32_t batch_num_;
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uint32_t event_num_;
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int32_t priority_;
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// Disable to copy constructor and assignment operator
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DavinciModel &operator=(const DavinciModel &) = delete;
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DavinciModel(const DavinciModel &) = delete;
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};
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} // namespace model_runner
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} // namespace ge
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#endif // INC_FRAMEWORK_GE_RUNTIME_DAVINCI_MODEL_H_
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@ -1,58 +0,0 @@
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/**
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* Copyright 2019-2020 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 INC_FRAMEWORK_GE_RUNTIME_MODEL_RUNNER_H_
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#define INC_FRAMEWORK_GE_RUNTIME_MODEL_RUNNER_H_
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#include <memory>
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#include <unordered_map>
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#include <vector>
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#include "common/ge_inner_error_codes.h"
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#include "common/ge_types.h"
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#include "ge_runtime/davinci_model.h"
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namespace ge {
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namespace model_runner {
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class RuntimeModel;
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class ModelRunner {
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public:
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static ModelRunner &Instance();
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bool LoadDavinciModel(uint32_t device_id, uint64_t session_id, uint32_t model_id,
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std::shared_ptr<DavinciModel> davinci_model, std::shared_ptr<ModelListener> listener);
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const std::vector<uint32_t> &GetTaskIdList(uint32_t model_id) const;
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bool UnloadModel(uint32_t model_id);
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bool RunModel(uint32_t model_id, const InputData &input_data, OutputData *output_data);
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bool GetInputOutputDescInfo(uint32_t model_id, bool zero_copy, std::vector<InputOutputDescInfo> *input_desc,
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std::vector<InputOutputDescInfo> *output_desc, std::vector<uint32_t> *input_format,
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std::vector<uint32_t> *output_format);
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private:
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ModelRunner() = default;
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~ModelRunner() = default;
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std::unordered_map<uint32_t, std::shared_ptr<RuntimeModel>> runtime_models_;
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};
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} // namespace model_runner
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} // namespace ge
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#endif // INC_FRAMEWORK_GE_RUNTIME_MODEL_RUNNER_H_
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@ -1,72 +0,0 @@
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/**
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* Copyright 2019-2020 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 INC_FRAMEWORK_GE_RUNTIME_OP_INFO_H_
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#define INC_FRAMEWORK_GE_RUNTIME_OP_INFO_H_
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#include <memory>
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#include <string>
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#include <vector>
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namespace ge {
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namespace model_runner {
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struct TensorInfo {
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int64_t GetShapeSize() const {
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int64_t res = 1;
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if (dims.empty()) {
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return 0;
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}
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for (auto dim : dims) {
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res *= dim;
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}
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return res;
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}
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int64_t GetDim(uint32_t index) {
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if (index >= dims.size()) {
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return 0;
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}
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return dims[index];
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}
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std::vector<int64_t> dims;
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uint32_t datatype;
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uint32_t format;
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uint32_t real_dim_cnt;
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uint32_t size;
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bool is_output;
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};
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struct OpInfo {
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uint32_t index;
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std::string name;
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std::string type;
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bool var_is_broadcast;
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std::vector<uintptr_t> input_addrs;
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std::vector<uintptr_t> output_addrs;
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std::vector<TensorInfo> input_tensors;
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std::vector<TensorInfo> output_tensors;
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std::vector<TensorInfo> weight_tensors;
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std::vector<std::string> src_name;
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std::vector<int64_t> src_index;
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std::string weight_data;
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};
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using TensorInfoPtr = std::shared_ptr<TensorInfo>;
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using OpInfoPtr = std::shared_ptr<OpInfo>;
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} // namespace model_runner
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} // namespace ge
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#endif // INC_FRAMEWORK_GE_RUNTIME_OP_INFO_H_
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