MyCaffe  1.12.2.41
Deep learning software for Windows C# programmers.
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MyCaffe.fillers.XavierFiller< T > Class Template Reference

Fills a Blob with values $ x\sim U(-a, a) $ where $ a $ is set inversely proportional to number of incoming nodes, outgoing nodes, or their average. More...

Inheritance diagram for MyCaffe.fillers.XavierFiller< T >:
MyCaffe.fillers.Filler< T >

Public Member Functions

 XavierFiller (CudaDnn< T > cuda, Log log, FillerParameter p)
 Constructor. More...
 
override void Fill (int nCount, long hMem, int nNumAxes=1, int nNumOutputs=1, int nNumChannels=1, int nHeight=1, int nWidth=1)
 Fill the memory with random numbers from a xavier distribution. More...
 
- Public Member Functions inherited from MyCaffe.fillers.Filler< T >
 Filler (CudaDnn< T > cuda, Log log, FillerParameter p)
 Constructor. More...
 
void Fill (Blob< T > b)
 Fill the blob with values based on the actual filler used. More...
 

Additional Inherited Members

- Static Public Member Functions inherited from MyCaffe.fillers.Filler< T >
static Filler< T > Create (CudaDnn< T > cuda, Log log, FillerParameter p)
 Create a new Filler instance. More...
 
- Protected Attributes inherited from MyCaffe.fillers.Filler< T >
CudaDnn< T > m_cuda
 Specifies the CudaDnn instance used to communicate to the low-level Cuda Dnn DLL. More...
 
Log m_log
 Specifies the output log. More...
 
FillerParameter m_param
 Specifies the filler parameters. More...
 

Detailed Description

Fills a Blob with values $ x\sim U(-a, a) $ where $ a $ is set inversely proportional to number of incoming nodes, outgoing nodes, or their average.

A filler based on paper Understanding the difficulty of training deep feedfrward neural networks by Bengio and Glorot, 2010.

It fills the incoming matrix by randomly sampling uniform data from $ [-scale, scale] $ where $ scale = sqrt(3 / n) $ where $ n $ is the fan_in, fan_out, or their average, depending on the variance_norm option. You shold make sure the input blob has shape (num, a, b, c) where $ a * b * c = fan_in $ and $ num * b * c = fan_out$. Note that this is currently not the case for inner product layers.

Template Parameters
TThe base type float or double.

Definition at line 26 of file XavierFiller.cs.

Constructor & Destructor Documentation

◆ XavierFiller()

MyCaffe.fillers.XavierFiller< T >.XavierFiller ( CudaDnn< T >  cuda,
Log  log,
FillerParameter  p 
)

Constructor.

Parameters
cudaInstance of CudaDnn - connection to cuda.
logLog used for output.
pFiller parameter that defines the filler settings.

Definition at line 34 of file XavierFiller.cs.

Member Function Documentation

◆ Fill()

override void MyCaffe.fillers.XavierFiller< T >.Fill ( int  nCount,
long  hMem,
int  nNumAxes = 1,
int  nNumOutputs = 1,
int  nNumChannels = 1,
int  nHeight = 1,
int  nWidth = 1 
)
virtual

Fill the memory with random numbers from a xavier distribution.

Parameters
nCountSpecifies the number of items to fill.
hMemSpecifies the handle to GPU memory to fill.
nNumAxesOptionally, specifies the number of axes (default = 1).
nNumOutputsOptionally, specifies the number of outputs (default = 1).
nNumChannelsOptionally, specifies the number of channels (default = 1).
nHeightOptionally, specifies the height (default = 1).
nWidthOptionally, specifies the width (default = 1).

Implements MyCaffe.fillers.Filler< T >.

Definition at line 49 of file XavierFiller.cs.

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