Package org.deeplearning4j.nn.conf

Interface Summary

Interface	Description
InputPreProcessor	Input pre processor used for pre processing input before passing it to the neural network.

Class Summary

Class	Description
ComputationGraphConfiguration	ComputationGraphConfiguration is a configuration object for neural networks with arbitrary connection structure.
ComputationGraphConfiguration.GraphBuilder
MultiLayerConfiguration	Configuration for a multi layer network
MultiLayerConfiguration.Builder
NeuralNetConfiguration	A Serializable configuration for neural nets that covers per layer parameters
NeuralNetConfiguration.Builder	NeuralNetConfiguration builder, used as a starting point for creating a MultiLayerConfiguration or ComputationGraphConfiguration. Note that values set here on the layer will be applied to all relevant layers - unless the value is overridden on a layer's configuration
NeuralNetConfiguration.ListBuilder	Fluent interface for building a list of configurations

Enum Summary

Enum	Description
BackpropType	Defines the type of backpropagation.
CacheMode
ConvolutionMode	ConvolutionMode defines how convolution operations should be executed for Convolutional and Subsampling layers, for a given input size and network configuration (specifically stride/padding/kernel sizes). Currently, 3 modes are provided: Strict: Output size for Convolutional and Subsampling layers are calculated as follows, in each dimension: outputSize = (inputSize - kernelSize + 2*padding) / stride + 1.
GradientNormalization	Gradient normalization strategies.
Updater	All the possible different updaters
WorkspaceMode	Workspace mode to use.