LiteSession
import com.mindspore.lite.LiteSession;
LiteSession defines session in MindSpore Lite for compiling Model and forwarding model.
Public Member Functions
function |
|---|
static LiteSession createSession(final MappedByteBuffer buffer, final MSConfig config) |
boolean export(String modelFilename, int model_type, int quantization_type) |
boolean isTrain() |
boolean isEval() |
boolean setLearningRate(float learning_rate) |
boolean setupVirtualBatch(int virtualBatchMultiplier, float learningRate, float momentum) |
List |
boolean updateFeatures(List |
init
public boolean init(MSConfig config)
Initialize LiteSession.
Parameters
config: MSConfig class.
Returns
Whether the initialization is successful.
createSession
public static LiteSession createSession(final MSConfig config)
Use MSConfig to create Litessesion.
Parameters
config: MSConfig class.
Returns
Return LiteSession object.
public static LiteSession createSession(final MappedByteBuffer buffer, final MSConfig config)
Use Model buffer and MSConfig to create Litessesion.
Parameters
buffer: MappedByteBuffer class.config: MSConfig class.
Returns
Return LiteSession object.
getSessionPtr
public long getSessionPtr()
Returns
Return session pointer.
setSessionPtr
public void setSessionPtr(long sessionPtr)
Parameters
sessionPtr: session pointer.
bindThread
public void bindThread(boolean isBind)
Attempt to bind or unbind threads in the thread pool to or from the specified cpu core.
Parameters
isBind: Define whether to bind or unbind threads.
compileGraph
public boolean compileGraph(Model model)
Compile MindSpore Lite model.
Parameters
Model: Define the model to be compiled.
Returns
Whether the compilation is successful.
runGraph
public boolean runGraph()
Run the session for inference.
Returns
Whether the inference is successful.
getInputs
public List<MSTensor> getInputs()
Get the MSTensors input of MindSpore Lite model.
Returns
The vector of MindSpore Lite MSTensor.
getInputsByTensorName
public MSTensor getInputsByTensorName(String tensorName)
Get the MSTensors input of MindSpore Lite model by the node name.
Parameters
tensorName: Define the tensor name.
Returns
MindSpore Lite MSTensor.
getOutputsByNodeName
public List<MSTensor> getOutputsByNodeName(String nodeName)
Get the MSTensors output of MindSpore Lite model by the node name.
Parameters
nodeName: Define the node name.
Returns
The vector of MindSpore Lite MSTensor.
getOutputMapByTensor
public Map<String, MSTensor> getOutputMapByTensor()
Get the MSTensors output of the MindSpore Lite model associated with the tensor name.
Returns
The map of output tensor name and MindSpore Lite MSTensor.
getOutputTensorNames
public List<String> getOutputTensorNames()
Get the name of output tensors of the model compiled by this session.
Returns
The vector of string as output tensor names in order.
getOutputByTensorName
public MSTensor getOutputByTensorName(String tensorName)
Get the MSTensors output of MindSpore Lite model by the tensor name.
Parameters
tensorName: Define the tensor name.
Returns
Pointer of MindSpore Lite MSTensor.
resize
public boolean resize(List<MSTensor> inputs, int[][] dims)
Resize inputs shape.
Parameters
inputs: Model inputs.dims: Define the new inputs shape.
Returns
Whether the resize is successful.
free
public void free()
Free LiteSession.
export
public boolean export(String modelFilename, int model_type, int quantization_type)
Export the model.
Parameters
modelFilename: Model file name.model_type: Train or Inference type.quantization_type: The quant type.
Returns
Whether the export is successful.
train
public void train()
Switch to the train mode
eval
public void eval()
Switch to the eval mode.
istrain
public void isTrain()
It is Train mode.
iseval
public void isEval()
It is Eval mode.
setLearningRate
public boolean setLearningRate(float learning_rate)
set learning rate.
Parameters
learning_rate: learning rate.
Returns
Whether the set learning rate is successful.
setupVirtualBatch
public boolean setupVirtualBatch(int virtualBatchMultiplier, float learningRate, float momentum)
Set the virtual batch.
Parameters
virtualBatchMultiplier: virtual batch multuplier.learningRate: learning rate.momentum: monentum.
Returns
Whether the virtual batch is successfully set.
getFeaturesMap
public List<MSTensor> getFeaturesMap()
Get the FeatureMap.
Returns
FeaturesMap Tensor list.
updateFeatures
public boolean updateFeatures(List<MSTensor> features)
Update model Features.
Parameters
features: new FeatureMap Tensor List.
Returns
Whether the model features is successfully update.