MindSpore Lite API
Summary of MindSpore Lite API support
Class |
Description |
C++ API |
Python API |
|---|---|---|---|
Context |
Set the number of threads at runtime |
void SetThreadNum(int32_t thread_num) |
|
Context |
Get the current thread number setting |
int32_t GetThreadNum() const |
|
Context |
Set the parallel number of operators at runtime |
void SetInterOpParallelNum(int32_t parallel_num) |
|
Context |
Get the current operators parallel number setting |
int32_t GetInterOpParallelNum() const |
|
Context |
Set the thread affinity to CPU cores |
void SetThreadAffinity(int mode) |
|
Context |
Get the thread affinity of CPU cores |
int GetThreadAffinityMode() const |
|
Context |
Set the thread lists to CPU cores |
void SetThreadAffinity(const std::vector<int> &core_list) |
|
Context |
Get the thread lists of CPU cores |
std::vector<int32_t> GetThreadAffinityCoreList() const |
|
Context |
Set the status whether to perform model inference or training in parallel |
void SetEnableParallel(bool is_parallel) |
|
Context |
Get the status whether to perform model inference or training in parallel |
bool GetEnableParallel() const |
|
Context |
Set built-in delegate mode to access third-party AI framework |
void SetBuiltInDelegate(DelegateMode mode) |
|
Context |
Get the built-in delegate mode of the third-party AI framework |
DelegateMode GetBuiltInDelegate() const |
|
Context |
Set Delegate to access third-party AI framework |
set_delegate(const std::shared_ptr<AbstractDelegate> &delegate) |
|
Context |
Get the delegate of the third-party AI framework |
std::shared_ptr<AbstractDelegate> get_delegate() const |
|
Context |
Set quant model to run as float model in multi device |
void SetMultiModalHW(bool float_mode) |
|
Context |
Get the mode of the model run |
bool GetMultiModalHW() const |
|
Context |
Get a mutable reference of DeviceInfoContext vector in this context |
std::vector<std::shared_ptr<DeviceInfoContext>> &MutableDeviceInfo() |
Wrapped in Context.target |
DeviceInfoContext |
Get the type of this DeviceInfoContext |
enum DeviceType GetDeviceType() const |
|
DeviceInfoContext |
converts DeviceInfoContext to a shared pointer of type T |
std::shared_ptr<T> Cast() |
|
DeviceInfoContext |
set provider’s name |
void SetProvider(const std::string &provider) |
|
DeviceInfoContext |
obtain provider’s name |
std::string GetProvider() const |
|
DeviceInfoContext |
set provider’s device type |
void SetProviderDevice(const std::string &device) |
|
DeviceInfoContext |
obtain provider’s device type |
std::string GetProviderDevice() const |
|
DeviceInfoContext |
set memory allocator |
void SetAllocator(const std::shared_ptr<Allocator> &allocator) |
|
DeviceInfoContext |
obtain memory allocator |
std::shared_ptr<Allocator> GetAllocator() const |
|
CPUDeviceInfo |
Get the type of this DeviceInfoContext |
enum DeviceType GetDeviceType() const |
|
CPUDeviceInfo |
Set enables to perform the float16 inference |
void SetEnableFP16(bool is_fp16) |
|
CPUDeviceInfo |
Get enables to perform the float16 inference |
bool GetEnableFP16() const |
|
GPUDeviceInfo |
Get the type of this DeviceInfoContext |
enum DeviceType GetDeviceType() const |
|
GPUDeviceInfo |
Set device id |
void SetDeviceID(uint32_t device_id) |
|
GPUDeviceInfo |
Get the device id |
uint32_t GetDeviceID() const |
|
GPUDeviceInfo |
Get the distribution rank id |
int GetRankID() const |
|
GPUDeviceInfo |
Get the distribution group size |
int GetGroupSize() const |
|
GPUDeviceInfo |
Set the precision mode |
void SetPrecisionMode(const std::string &precision_mode) |
|
GPUDeviceInfo |
Get the precision mode |
std::string GetPrecisionMode() const |
|
GPUDeviceInfo |
Set enables to perform the float16 inference |
void SetEnableFP16(bool is_fp16) |
|
GPUDeviceInfo |
Get enables to perform the float16 inference |
bool GetEnableFP16() const |
|
GPUDeviceInfo |
Set enables to sharing mem with OpenGL |
void SetEnableGLTexture(bool is_enable_gl_texture) |
|
GPUDeviceInfo |
Get enables to sharing mem with OpenGL |
bool GetEnableGLTexture() const |
|
GPUDeviceInfo |
Set current OpenGL context |
void SetGLContext(void *gl_context) |
|
GPUDeviceInfo |
Get current OpenGL context |
void *GetGLContext() const |
|
GPUDeviceInfo |
Set current OpenGL display |
void SetGLDisplay(void *gl_display) |
|
GPUDeviceInfo |
Get current OpenGL display |
void *GetGLDisplay() const |
|
AscendDeviceInfo |
Get the type of this DeviceInfoContext |
enum DeviceType GetDeviceType() const |
|
AscendDeviceInfo |
Set device id |
void SetDeviceID(uint32_t device_id) |
|
AscendDeviceInfo |
Get the device id |
uint32_t GetDeviceID() const |
|
AscendDeviceInfo |
Set AIPP configuration file path |
void SetInsertOpConfigPath(const std::string &cfg_path) |
|
AscendDeviceInfo |
Get AIPP configuration file path |
std::string GetInsertOpConfigPath() const |
|
AscendDeviceInfo |
Set format of model inputs |
void SetInputFormat(const std::string &format) |
|
AscendDeviceInfo |
Get format of model inputs |
std::string GetInputFormat() const |
|
AscendDeviceInfo |
Set shape of model inputs |
void SetInputShape(const std::string &shape) |
|
AscendDeviceInfo |
Get shape of model inputs |
std::string GetInputShape() const |
|
AscendDeviceInfo |
Set shape of model inputs |
void SetInputShapeMap(const std::map<int, std::vector <int>> &shape) |
|
AscendDeviceInfo |
Get shape of model inputs |
std::map<int, std::vector <int>> GetInputShapeMap() const |
|
AscendDeviceInfo |
Set dynamic batch sizes of model inputs. Ranges from 2 to 100 |
void SetDynamicBatchSize(const std::vector<size_t> &dynamic_batch_size) |
|
AscendDeviceInfo |
Get dynamic batch sizes of model inputs |
std::string GetDynamicBatchSize() const |
|
AscendDeviceInfo |
Set the dynamic image size of model inputs |
void SetDynamicImageSize(const std::string &dynamic_image_size) |
|
AscendDeviceInfo |
Get dynamic image size of model inputs |
std::string GetDynamicImageSize() const |
|
AscendDeviceInfo |
Set type of model outputs |
void SetOutputType(enum DataType output_type) |
|
AscendDeviceInfo |
Get type of model outputs |
enum DataType GetOutputType() const |
|
AscendDeviceInfo |
Set precision mode of model |
void SetPrecisionMode(const std::string &precision_mode) |
|
AscendDeviceInfo |
Get precision mode of model |
std::string GetPrecisionMode() const |
|
AscendDeviceInfo |
Set op select implementation mode |
void SetOpSelectImplMode(const std::string &op_select_impl_mode) |
|
AscendDeviceInfo |
Get op select implementation mode |
std::string GetOpSelectImplMode() const |
|
AscendDeviceInfo |
Set fusion switch config file path. Controls which fusion passes to be turned off |
void SetFusionSwitchConfigPath(const std::string &cfg_path) |
|
AscendDeviceInfo |
Get fusion switch config file path |
std::string GetFusionSwitchConfigPath() const |
|
AscendDeviceInfo |
Set buffer optimize mode |
void SetBufferOptimizeMode(const std::string &buffer_optimize_mode) |
|
AscendDeviceInfo |
Get buffer optimize mode |
std::string GetBufferOptimizeMode() const |
|
KirinNPUDeviceInfo |
Get the type of this DeviceInfoContext |
enum DeviceType GetDeviceType() const |
|
KirinNPUDeviceInfo |
Set enables to perform the float16 inference |
void SetEnableFP16(bool is_fp16) |
|
KirinNPUDeviceInfo |
Get enables to perform the float16 inference |
bool GetEnableFP16() const |
|
KirinNPUDeviceInfo |
Set the NPU frequency |
void SetFrequency(int frequency) |
|
KirinNPUDeviceInfo |
Get the NPU frequency |
int GetFrequency() const |
|
Model |
Build a model from model buffer so that it can run on a device |
Status Build(const void *model_data, size_t data_size, ModelType model_type, const std::shared_ptr <Context> &model_context = nullptr) |
|
Model |
Load and build a model from model buffer so that it can run on a device |
Status Build(const std::string &model_path, ModelType model_type, const std::shared_ptr <Context> &model_context = nullptr) |
|
Model |
Build a model from model buffer so that it can run on a device |
Status Build(const void *model_data, size_t data_size, ModelType model_type, const std::shared_ptr <Context> &model_context, const Key &dec_key, const std::string &dec_mode, const std::string &cropto_lib_path) |
|
Model |
Load and build a model from model buffer so that it can run on a device |
Status Build(const std::string &model_path, ModelType model_type, const std::shared_ptr <Context> &model_context, const Key &dec_key, const std::string &dec_mode, const std::string &cropto_lib_path) |
|
Model |
Build a train model from GraphCell so that it can run on a device |
Status Build(GraphCell graph, const std::shared_ptr <Context> &model_context = nullptr, const std::shared_ptr <TrainCfg> &train_cfg = nullptr) |
|
Model |
Build a train model from GraphCell so that it can run on a device |
Status Build(GraphCell graph, Node *optimizer, std::vector<Expr *> inputs, const std::shared_ptr <Context> &model_context, const std::shared_ptr <TrainCfg> &train_cfg) |
|
Model |
Build a Transfer Learning model where the backbone weights are fixed and the head weights are trainable |
Status BuildTransferLearning(GraphCell backbone, GraphCell head, const std::shared_ptr <Context> &context, const std::shared_ptr <TrainCfg> &train_cfg = nullptr) |
|
Model |
Resize the shapes of inputs |
Status Resize(const std::vector <MSTensor> &inputs, const std::vector <std::vector<int64_t>> &dims) |
|
Model |
Change the size and or content of weight tensors |
Status UpdateWeights(const std::vector <MSTensor> &new_weights) |
|
Model |
Inference model API |
Status Predict(const std::vector <MSTensor> &inputs, std::vector <MSTensor> *outputs, const MSKernelCallBack &before = nullptr, const MSKernelCallBack &after = nullptr) |
|
Model |
Inference model API only with callback |
Status Predict(const MSKernelCallBack &before = nullptr, const MSKernelCallBack &after = nullptr) |
|
Model |
Training API, Run model by step |
Status RunStep(const MSKernelCallBack &before = nullptr, const MSKernelCallBack &after = nullptr) |
|
Model |
Inference model with preprocess in model |
Status PredictWithPreprocess(const std::vector <std::vector<MSTensor>> &inputs, std::vector <MSTensor> *outputs, const MSKernelCallBack &before = nullptr, const MSKernelCallBack &after = nullptr) |
|
Model |
Apply data preprocess if it exits in model |
Status Preprocess(const std::vector <std::vector<MSTensor>> &inputs, std::vector <MSTensor> *outputs) |
|
Model |
Check if data preprocess exists in model |
bool HasPreprocess() |
|
Model |
Load config file |
Status LoadConfig(const std::string &config_path) |
Wrapped in the parameter config_path of Model.build_from_file |
Model |
Update config |
Status UpdateConfig(const std::string §ion, const std::pair<std::string, std::string> &config) |
|
Model |
Obtains all input tensors of the model |
std::vector <MSTensor> GetInputs() |
|
Model |
Obtains the input tensor of the model by name |
MSTensor GetInputByTensorName(const std::string &tensor_name) |
|
Model |
Obtain all gradient tensors of the model |
std::vector <MSTensor> GetGradients() const |
|
Model |
Update gradient tensors of the model |
Status ApplyGradients(const std::vector <MSTensor> &gradients) |
|
Model |
Obtain all weights tensors of the model |
std::vector <MSTensor> GetFeatureMaps() const |
|
Model |
Obtain all trainable parameters of the model optimizers |
std::vector <MSTensor> GetTrainableParams() const |
|
Model |
Update weights tensors of the model |
Status UpdateFeatureMaps(const std::vector <MSTensor> &new_weights) |
|
Model |
Obtain optimizer params tensors of the model |
std::vector <MSTensor> GetOptimizerParams() const |
|
Model |
Update the optimizer parameters |
Status SetOptimizerParams(const std::vector <MSTensor> ¶ms) |
|
Model |
Setup training with virtual batches |
Status SetupVirtualBatch(int virtual_batch_multiplier, float lr = -1.0f, float momentum = -1.0f) |
|
Model |
Set the Learning Rate of the training |
Status SetLearningRate(float learning_rate) |
|
Model |
Get the Learning Rate of the optimizer |
float GetLearningRate() |
|
Model |
Initialize object with metrics |
Status InitMetrics(std::vector<Metrics *> metrics) |
|
Model |
Accessor to TrainLoop metric objects |
std::vector<Metrics *> GetMetrics() |
|
Model |
Obtains all output tensors of the model |
std::vector <MSTensor> GetOutputs() |
Wrapped in the return value of Model.predict |
Model |
Obtains names of all output tensors of the model |
std::vector <std::string> GetOutputTensorNames() |
|
Model |
Obtains the output tensor of the model by name |
MSTensor GetOutputByTensorName(const std::string &tensor_name) |
|
Model |
Get output MSTensors of model by node name |
std::vector <MSTensor> GetOutputsByNodeName(const std::string &node_name) |
|
Model |
Bind GLTexture2D object to cl Memory |
Status BindGLTexture2DMemory(const std::map<std::string, unsigned int> &inputGLTexture, std::map<std::string, unsigned int> *outputGLTexture) |
|
Model |
Set the model running mode |
Status SetTrainMode(bool train) |
|
Model |
Get the model running mode |
bool GetTrainMode() const |
|
Model |
Performs the training Loop in Train Mode |
Status Train(int epochs, std::shared_ptr <dataset::Dataset>ds, std::vector<TrainCallBack *> cbs) |
|
Model |
Performs the training loop over all data in Eval Mode |
Status Evaluate(std::shared_ptr <dataset::Dataset> ds, std::vector<TrainCallBack *> cbs) |
|
Model |
Check if the device supports the model |
static bool CheckModelSupport(enum DeviceType device_type, ModelType model_type) |
|
RunnerConfig |
Set the number of workers at runtime |
void SetWorkersNum(int32_t workers_num) |
|
RunnerConfig |
Get the current operators parallel workers number setting |
int32_t GetWorkersNum() const |
|
RunnerConfig |
Set the context at runtime |
void SetContext(const std::shared_ptr <Context> &context) |
Wrapped in Context.parallel |
RunnerConfig |
Get the current context setting |
std::shared_ptr <Context> GetContext() const |
Wrapped in Context.parallel |
RunnerConfig |
Set the config before runtime |
void SetConfigInfo(const std::string §ion, const std::map<std::string, std::string> &config) |
|
RunnerConfig |
Get the current config setting |
std::map<std::string, std::map<std::string, std::string>> GetConfigInfo() const |
|
RunnerConfig |
Set the config path before runtime |
void SetConfigPath(const std::string &config_path) |
|
RunnerConfig |
Get the current config path |
std::string GetConfigPath() const |
|
ModelParallelRunner |
build a model parallel runner from model path so that it can run on a device |
Status Init(const std::string &model_path, const std::shared_ptr <RunnerConfig> &runner_config = nullptr) |
|
ModelParallelRunner |
build a model parallel runner from model buffer so that it can run on a device |
Status Init(const void *model_data, const size_t data_size, const std::shared_ptr <RunnerConfig> &runner_config = nullptr) |
|
ModelParallelRunner |
Obtains all input tensors information of the model |
std::vector <MSTensor> GetInputs() |
|
ModelParallelRunner |
Obtains all output tensors information of the model |
std::vector <MSTensor> GetOutputs() |
Wrapped in the return value of Model.parallel_runner.predict |
ModelParallelRunner |
Inference ModelParallelRunner |
Status Predict(const std::vector <MSTensor> &inputs, std::vector <MSTensor> *outputs,const MSKernelCallBack &before = nullptr, const MSKernelCallBack &after = nullptr) |
|
MSTensor |
Creates a MSTensor object, whose data need to be copied before accessed by Model |
static inline MSTensor *CreateTensor(const std::string &name, DataType type, const std::vector<int64_t> &shape, const void *data, size_t data_len) noexcept |
|
MSTensor |
Creates a MSTensor object, whose data can be directly accessed by Model |
static inline MSTensor *CreateRefTensor(const std::string &name, DataType type, const std::vector<int64_t> &shape, const void *data, size_t data_len, bool own_data = true) noexcept |
|
MSTensor |
Creates a MSTensor object, whose device data can be directly accessed by Model |
static inline MSTensor CreateDeviceTensor(const std::string &name, DataType type, const std::vector<int64_t> &shape, void *data, size_t data_len) noexcept |
|
MSTensor |
Creates a MSTensor object from local file |
static inline MSTensor *CreateTensorFromFile(const std::string &file, DataType type = DataType::kNumberTypeUInt8, const std::vector<int64_t> &shape = {}) noexcept |
|
MSTensor |
Create a string type MSTensor object whose data can be accessed by Model only after being copied |
static inline MSTensor *StringsToTensor(const std::string &name, const std::vectorstd::string &str) |
|
MSTensor |
Parse the string type MSTensor object into strings |
static inline std::vectorstd::string TensorToStrings(const MSTensor &tensor) |
|
MSTensor |
Destroy an object created by Clone , StringsToTensor , CreateRefTensor or CreateTensor |
static void DestroyTensorPtr(MSTensor *tensor) noexcept |
|
MSTensor |
Obtains the name of the MSTensor |
std::string Name() const |
|
MSTensor |
Obtains the data type of the MSTensor |
enum DataType DataType() const |
|
MSTensor |
Obtains the shape of the MSTensor |
const std::vector<int64_t> &Shape() const |
|
MSTensor |
Obtains the number of elements of the MSTensor |
int64_t ElementNum() const |
|
MSTensor |
Obtains a shared pointer to the copy of data of the MSTensor |
std::shared_ptr <const void> Data() const |
|
MSTensor |
Obtains the pointer to the data of the MSTensor |
void *MutableData() |
Wrapped in Tensor.get_data_to_numpy and Tensor.set_data_from_numpy |
MSTensor |
Obtains the length of the data of the MSTensor, in bytes |
size_t DataSize() const |
|
MSTensor |
Get whether the MSTensor data is const data |
bool IsConst() const |
|
MSTensor |
Gets the boolean value that indicates whether the memory of MSTensor is on device |
bool IsDevice() const |
|
MSTensor |
Gets a deep copy of the MSTensor |
MSTensor *Clone() const |
|
MSTensor |
Gets the boolean value that indicates whether the MSTensor is valid |
bool operator==(std::nullptr_t) const |
|
MSTensor |
Gets the boolean value that indicates whether the MSTensor is valid |
bool operator!=(std::nullptr_t) const |
|
MSTensor |
Get the boolean value that indicates whether the MSTensor equals tensor |
bool operator==(const MSTensor &tensor) const |
|
MSTensor |
Get the boolean value that indicates whether the MSTensor not equals tensor |
bool operator!=(const MSTensor &tensor) const |
|
MSTensor |
Set the shape of for the MSTensor |
void SetShape(const std::vector<int64_t> &shape) |
|
MSTensor |
Set the data type for the MSTensor |
void SetDataType(enum DataType data_type) |
|
MSTensor |
Set the name for the MSTensor |
void SetTensorName(const std::string &name) |
|
MSTensor |
Set the Allocator for the MSTensor |
void SetAllocator(std::shared_ptr <Allocator> allocator) |
|
MSTensor |
Obtain the Allocator of the MSTensor |
std::shared_ptr <Allocator> allocator() const |
|
MSTensor |
Set the format for the MSTensor |
void SetFormat(mindspore::Format format) |
|
MSTensor |
Obtain the format of the MSTensor |
mindspore::Format format() const |
|
MSTensor |
Set the data for the MSTensor |
void SetData(void *data, bool own_data = true) |
|
MSTensor |
Set the device data address for the MSTensor |
void SetDeviceData(void *data) |
|
MSTensor |
Get the device data address of the MSTensor set by SetDeviceData |
void *GetDeviceData() |
|
MSTensor |
Get the quantization parameters of the MSTensor |
std::vector <QuantParam> QuantParams() const |
|
MSTensor |
Set the quantization parameters for the MSTensor |
void SetQuantParams(std::vector <QuantParam> quant_params) |
|
ModelGroup |
Construct a ModelGroup object and indicate shared workspace memory or shared weight memory, with default shared workspace memory |
ModelGroup(ModelGroupFlag flags = ModelGroupFlag::kShareWorkspace) |
|
ModelGroup |
When sharing weight memory, add model objects that require shared weight memory |
Status AddModel(const std::vector<Model> &model_list) |
|
ModelGroup |
When sharing workspace memory, add the path of the model that requires shared workspace memory |
Status AddModel(const std::vector<std::string> &model_path_list) |
|
ModelGroup |
When sharing workspace memory, add a model buffer that requires shared workspace memory |
Status AddModel(const std::vector<std::pair<const void *, size_t>> &model_buff_list) |
|
ModelGroup |
When sharing workspace memory, calculate the maximum workspace memory size |
Status CalMaxSizeOfWorkspace(ModelType model_type, const std::shared_ptr<Context> &ms_context) |
MindSpore Lite API
C++ API
Python API