ConvNet
1.0
A GPU-based C++ implementation of Convolutional Neural Nets
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- a -
AddIncoming() :
Layer
AddOutgoing() :
Layer
AllocateEdgeMemory() :
ConvNet
AllocateLayerMemory() :
ConvNet
AllocateMemory() :
ConvEdge
,
ConvNet
,
ConvOneToOneEdge
,
Edge
,
FCEdge
,
Layer
,
LinearLayer
,
LocalEdge
,
LogisticLayer
,
MaxPoolEdge
,
ResponseNormEdge
,
SoftmaxDistLayer
,
SoftmaxLayer
ApplyActivation() :
Layer
,
LinearLayer
,
LogisticLayer
,
ReLULayer
,
SoftmaxLayer
ApplyDerivativeOfActivation() :
Layer
,
LinearLayer
,
LogisticLayer
,
ReLULayer
,
SoftmaxLayer
ApplyDerivativeofDropout() :
Layer
ApplyDropout() :
Layer
- b -
Bprop() :
ConvNet
,
MultiGPUConvNet
BuildNet() :
ConvNet
- c -
CheckReduceLearningRate() :
ConvNet
ChooseEdgeClass() :
Edge
ComputeDeriv() :
ConvNet
,
Layer
,
LinearLayer
,
LogisticLayer
,
SoftmaxDistLayer
,
SoftmaxLayer
ComputeDown() :
ConvEdge
,
ConvOneToOneEdge
,
DownSampleEdge
,
Edge
,
FCEdge
,
LocalEdge
,
MaxPoolEdge
,
ResponseNormEdge
,
RGBToYUVEdge
,
UpSampleEdge
ComputeOuter() :
ConvEdge
,
ConvOneToOneEdge
,
Edge
,
FCEdge
,
LocalEdge
ComputeUp() :
ConvEdge
,
ConvOneToOneEdge
,
DownSampleEdge
,
Edge
,
FCEdge
,
LocalEdge
,
MaxPoolEdge
,
ResponseNormEdge
,
RGBToYUVEdge
,
UpSampleEdge
ConvNet() :
ConvNet
- d -
DestroyNet() :
ConvNet
Display() :
ConvNet
DisplayWeights() :
ConvEdge
,
Edge
,
EdgeWithWeight
,
LocalEdge
DisplayWeightStats() :
Edge
,
EdgeWithWeight
DumpOutputs() :
ConvNet
- e -
Edge() :
Edge
- f -
Fprop() :
ConvNet
,
MultiGPUConvNet
- g -
GetData() :
Layer
GetDeriv() :
Layer
GetIncomingEdge() :
Layer
GetLoss() :
ConvNet
,
GradChecker
,
Layer
,
LinearLayer
,
LogisticLayer
,
SoftmaxDistLayer
,
SoftmaxLayer
GetLoss2() :
Layer
,
SoftmaxLayer
GetNumModules() :
ConvEdge
,
ConvOneToOneEdge
,
Edge
,
EdgeWithWeight
,
LocalEdge
,
MaxPoolEdge
,
RGBToYUVEdge
GetRMSWeight() :
Edge
,
EdgeWithWeight
GetState() :
Layer
- h -
HasNoParameters() :
Edge
,
EdgeWithWeight
- i -
Initialize() :
Edge
,
EdgeWithWeight
IsBackPropBlocked() :
Edge
- l -
Layer() :
Layer
Load() :
ConvNet
LoadParameters() :
Edge
,
EdgeWithWeight
- r -
ReduceLearningRate() :
ConvNet
,
Edge
,
EdgeWithWeight
- s -
Save() :
ConvNet
SaveParameters() :
Edge
,
EdgeWithWeight
SetImageSize() :
ConvEdge
,
ConvOneToOneEdge
,
DownSampleEdge
,
Edge
,
LocalEdge
,
MaxPoolEdge
,
ResponseNormEdge
,
UpSampleEdge
SetInputChannels() :
Edge
SetOutputChannels() :
Edge
SetTiedTo() :
ConvEdge
,
Edge
,
EdgeWithWeight
,
LocalEdge
,
MaxPoolEdge
,
ResponseNormEdge
Sort() :
ConvNet
- t -
Train() :
ConvNet
TrainOneBatch() :
ConvNet
- u -
UpdateWeights() :
Edge
,
EdgeWithWeight
- v -
Validate() :
ConvNet
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