DeepCL  SNAPSHOT
Deep convolutional neural networks using OpenCL
Class List
Here are the classes, structs, unions and interfaces with brief descriptions:
 CBatcherRuns an epoch for a single set of already-loaded data
 CConvolutionalMakerUse to create a convolutional layer
 CDropoutMakerUse to create a dropout layer
 CFullyConnectedMakerUse to create a fully-connected layer
 CGenericLoaderUse to load data from file, given the path to the images file
 CInputLayerMakerUse to create an InputLayer, which can be added to a NeuralNet
 CLayerA single layer within the neural net
 CNetdefToNetAdd layers to a NeuralNet object, based on a netdef-string
 CNetLearnerRuns multiple learning epochs using Batcher objects
 CNetLearnerOnDemandLearns multiple epochs, for data that wont fit in memory
 CNetLearnerOnDemandv2Learns multiple epochs, for data that wont fit in memory
 CNeuralNetNeuralNet: main container class for network layers
 CNormalizationLayerMakerUse to add a NormalizationLayer to a NeuralNet
 COnDemandBatcherLearns an entire epoch of training, for data that wont fit in memory
 COnDemandBatcherv2Learns an entire epoch of training, for data that wont fit in memory
 CPoolingMakerUse to create a Max-Pooling layer
 CRandomPatchesMakerUse to create a RandomPatches Layer
 CRandomTranslationsMakerUse to create a RandomTranslations Layer
 CWeightsPersisterUse to read/write weights from a NeuralNet