forked from huawei/mindspore2022
140 lines
4.4 KiB
C++
140 lines
4.4 KiB
C++
/**
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* Copyright 2020-2021 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_LITE_TOOLS_COMMON_TENSOR_UTIL_H
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#define MINDSPORE_LITE_TOOLS_COMMON_TENSOR_UTIL_H
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#include <cmath>
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#include <unordered_map>
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#include <memory>
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#include <algorithm>
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#include <utility>
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#include <string>
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#include <vector>
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#include "schema/inner/model_generated.h"
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#include "src/common/log_adapter.h"
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#include "ir/dtype/type_id.h"
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#include "ir/tensor.h"
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#include "src/common/utils.h"
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namespace mindspore {
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namespace lite {
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using schema::CNodeT;
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using schema::Format;
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using schema::FusedBatchNormT;
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using schema::MetaGraphT;
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using schema::QuantParamT;
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using schema::TensorT;
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std::unique_ptr<QuantParamT> GetTensorQuantParam(const std::unique_ptr<TensorT> &tensor);
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tensor::TensorPtr CreateTensorInfo(const void *data, size_t data_size, const std::vector<int64_t> &shape,
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TypeId data_type);
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AbstractBasePtr CreateTensorAbstract(const std::vector<int64_t> &shape, TypeId data_type);
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int SetParameterAbstractAndParam(const ParameterPtr ¶meter, const void *data, size_t data_size,
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const std::vector<int64_t> &shape, TypeId data_type);
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int SetTensorData(const tensor::TensorPtr &tensor_info, const void *data, size_t data_size);
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std::unique_ptr<schema::TensorT> CreateTensorTFromTensorInfo(const tensor::TensorPtr &tensor_info,
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const std::string &tensor_name = "");
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int UpdateTensorTFromTensorInfo(const tensor::TensorPtr &src_tensor, std::unique_ptr<schema::TensorT> *dst_tensor);
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int InitParameterFromTensorInfo(const ParameterPtr ¶m_node, const tensor::TensorPtr &tensor_info);
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size_t GetElementSize(const TensorT &tensor);
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size_t GetElementSize(const TypeId &dataType);
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size_t GetShapeSize(const TensorT &tensor);
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size_t GetShapeSize(const std::vector<int32_t> &shape);
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std::unique_ptr<TensorT> CopyTensorDefT(const std::unique_ptr<TensorT> &);
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size_t GetRefCount(schema::MetaGraphT *graphT, uint32_t tensorIdx);
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std::unique_ptr<schema::QuantParamT> CopyQuantParamT(const std::unique_ptr<schema::QuantParamT> &srcQuantParam);
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std::unique_ptr<schema::QuantParamT> CopyQuantParamArrayT(
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const std::unique_ptr<schema::QuantParamT> &srcQuantParamArray);
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enum Category { CONSTANT = 0, GRAPH_INPUT = 1, OP_OUTPUT = 2, TF_CONST = 3 };
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class TensorCache {
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public:
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TensorCache() = default;
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~TensorCache() { tensors.clear(); }
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int AddTensor(const std::string &name, TensorT *tensor, int Category) {
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index++;
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if (Category == CONSTANT || Category == TF_CONST || Category == GRAPH_INPUT) {
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tensor->refCount = 1;
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tensor->nodeType = NodeType_ValueNode;
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} else {
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tensor->nodeType = NodeType_Parameter;
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}
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tensor->name = name;
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tensors.push_back(tensor);
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if (Category == GRAPH_INPUT) {
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graphInputs.push_back(index);
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}
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if (Category == GRAPH_INPUT || Category == OP_OUTPUT || Category == TF_CONST) {
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UpdateTensorIndex(name, index);
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}
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return index;
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}
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// find the name index
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int FindTensor(const std::string &name) {
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auto iter = tensorIndex.find(name);
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if (iter != tensorIndex.end()) {
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return iter->second;
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}
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return -1;
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}
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void UpdateTensorIndex(const std::string &name, int idx) {
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auto iter = tensorIndex.find(name);
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if (iter != tensorIndex.end()) {
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tensorIndex[name] = idx;
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} else {
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tensorIndex.insert(make_pair(name, idx));
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}
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}
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// return allTensors
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const std::vector<TensorT *> &GetCachedTensor() const { return tensors; }
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const std::vector<int> &GetGraphInputs() const { return graphInputs; }
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private:
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std::vector<TensorT *> tensors;
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std::unordered_map<std::string, int> tensorIndex;
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std::vector<int> graphInputs;
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int index = -1;
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};
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} // namespace lite
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} // namespace mindspore
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#endif // MINDSPORE_LITE_TOOLS_COMMON_TENSOR_UTIL_H
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