Python* API Reference for Intel® Data Analytics Acceleration Library 2020 Update 1

Public Member Functions | List of all members
Model Class Reference

Class Model object for the prediction stage of neural network algorithm. More...

Public Member Functions

def serializationTag
 
def getSerializationTag
 
def __init__
 
def create
 
def setLayers
 
def getLayers
 
def getLayer
 
def allocate_{Float64|Float32}
 
- Public Member Functions inherited from ModelImpl
def getNextLayers
 
def setWeightsAndBiases
 
def getWeightsAndBiases
 
- Public Member Functions inherited from Model
def __init__
 
def getSerializationTag
 
- Public Member Functions inherited from SerializationIface
def serialize
 
def deserialize
 
def getSerializationTag
 
- Public Member Functions inherited from Base
def __init__
 

Detailed Description

Deprecated:
This item will be removed in a future release.

Constructor & Destructor Documentation

def __init__ (   self,
  args 
)

Variant 1

Constructs model object for the prediction stage of neural network from the list of forward stages of the layers and the list of connections between the layers

Parameters
forwardLayersForModelList of forward stages of the layers
nextLayersForModelList of next layers for each layer with corresponding index
Deprecated:
This item will be removed in a future release.

Variant 2

Constructs model object for the prediction stage of neural network from a collection of layer descriptors

Parameters
topologyCollection of layer descriptors of every inserted layer
Deprecated:
This item will be removed in a future release.

Member Function Documentation

def allocate_{Float64|Float32} (   self,
  sampleSize,
  parameter = None 
)

Variant 1

Allocates the buffers needed for the prediction using neural network

Parameters
sampleSizeDimensionality of the batch for the input to the first layer
parameterPrediction model parameter
Returns
Status of computations
Deprecated:
This item will be removed in a future release.

Variant 2

Allocates the buffers needed for the prediction using neural network

Parameters
sampleSizeDimensionality of the batch for the input to the first layer
parameterPrediction model parameter
Returns
Status of computations
Deprecated:
This item will be removed in a future release.
Full Names
  • allocate_Float64 is for float64
  • allocate_Float32 is for float32
def create (   args)

Variant 1

Constructs empty model for the prediction stage of neural network

Parameters
statStatus of the model construction
Returns
Empty model for the prediction stage of neural network
Deprecated:
This item will be removed in a future release.

Variant 2

Constructs model object for the prediction stage of neural network from the list of forward stages of the layers and the list of connections between the layers

Parameters
forwardLayersForModelList of forward stages of the layers
nextLayersForModelList of next layers for each layer with corresponding index
statStatus of the model construction
Returns
Model object for the prediction stage of neural network
Deprecated:
This item will be removed in a future release.

Variant 3

Constructs model object for the prediction stage of neural network from the list of forward stages of the layers and the list of connections between the layers

Parameters
forwardLayersForModelList of forward stages of the layers
nextLayersForModelList of next layers for each layer with corresponding index
statStatus of the model construction
Returns
Model object for the prediction stage of neural network
Deprecated:
This item will be removed in a future release.

Variant 4

Constructs model object for the prediction stage of neural network from a collection of layer descriptors

Parameters
topologyCollection of layer descriptors of every inserted layer
statStatus of the model construction
Returns
Model object for the prediction stage of neural network
Deprecated:
This item will be removed in a future release.

Variant 5

Constructs model object for the prediction stage of neural network from a collection of layer descriptors

Parameters
topologyCollection of layer descriptors of every inserted layer
statStatus of the model construction
Returns
Model object for the prediction stage of neural network
Deprecated:
This item will be removed in a future release.
def getLayer (   self,
  index 
)

Returns the forward stage of a layer with certain index in the network

Parameters
indexIndex of the layer in the network
Returns
Forward stage of a layer with certain index in the network
Deprecated:
This item will be removed in a future release.
def getLayers (   self)

Returns the list of forward stages of the layers

Returns
List of forward stages of the layers
Deprecated:
This item will be removed in a future release.
def getSerializationTag (   self)

getSerializationTag(Model self) -> int

def serializationTag ( )
def setLayers (   self,
  forwardLayers,
  nextLayers 
)

Sets list of forward stages of the layers and the list of connections between the layers

Parameters
forwardLayersList of forward stages of the layers
nextLayersList of next layers for each layer with corresponding index
Returns
Status of computations
Deprecated:
This item will be removed in a future release.

The documentation for this class was generated from the following file:

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