Uses of Class
org.deeplearning4j.nn.layers.BaseLayer

Packages that use BaseLayer

Package	Description
org.deeplearning4j.nn.layers
org.deeplearning4j.nn.layers.convolution
org.deeplearning4j.nn.layers.feedforward.autoencoder
org.deeplearning4j.nn.layers.feedforward.dense
org.deeplearning4j.nn.layers.feedforward.embedding
org.deeplearning4j.nn.layers.feedforward.rbm
org.deeplearning4j.nn.layers.normalization
org.deeplearning4j.nn.layers.recurrent
org.deeplearning4j.nn.layers.training

Uses of BaseLayer in org.deeplearning4j.nn.layers

Subclasses of BaseLayer in org.deeplearning4j.nn.layers

Modifier and Type	Class and Description
class	BaseOutputLayer<LayerConfT extends BaseOutputLayer> Output layer with different objective in co-occurrences for different objectives.
class	BasePretrainNetwork<LayerConfT extends BasePretrainNetwork> Baseline class for any Neural Network used as a layer in a deep network *
class	DropoutLayer Created by davekale on 12/7/16.
class	LossLayer LossLayer is a flexible output "layer" that performs a loss function on an input without MLP logic.
class	OutputLayer Output layer with different objective incooccurrences for different objectives.

Uses of BaseLayer in org.deeplearning4j.nn.layers.convolution

Subclasses of BaseLayer in org.deeplearning4j.nn.layers.convolution

Modifier and Type	Class and Description
class	Convolution1DLayer 1D (temporal) convolutional layer.
class	ConvolutionLayer Convolution layer

Uses of BaseLayer in org.deeplearning4j.nn.layers.feedforward.autoencoder

Subclasses of BaseLayer in org.deeplearning4j.nn.layers.feedforward.autoencoder

Modifier and Type	Class and Description
class	AutoEncoder Autoencoder.

Uses of BaseLayer in org.deeplearning4j.nn.layers.feedforward.dense

Subclasses of BaseLayer in org.deeplearning4j.nn.layers.feedforward.dense

Modifier and Type	Class and Description
class	DenseLayer

Uses of BaseLayer in org.deeplearning4j.nn.layers.feedforward.embedding

Subclasses of BaseLayer in org.deeplearning4j.nn.layers.feedforward.embedding

Modifier and Type	Class and Description
class	EmbeddingLayer Embedding layer: feed-forward layer that expects single integers per example as input (class numbers, in range 0 to numClass-1) as input.

Uses of BaseLayer in org.deeplearning4j.nn.layers.feedforward.rbm

Subclasses of BaseLayer in org.deeplearning4j.nn.layers.feedforward.rbm

Modifier and Type	Class and Description
class	RBM Restricted Boltzmann Machine.

Uses of BaseLayer in org.deeplearning4j.nn.layers.normalization

Subclasses of BaseLayer in org.deeplearning4j.nn.layers.normalization

Modifier and Type	Class and Description
class	BatchNormalization Batch normalization layer.

Uses of BaseLayer in org.deeplearning4j.nn.layers.recurrent

Subclasses of BaseLayer in org.deeplearning4j.nn.layers.recurrent

Modifier and Type	Class and Description
class	BaseRecurrentLayer<LayerConfT extends BaseLayer>
class	GravesBidirectionalLSTM RNN tutorial: http://deeplearning4j.org/usingrnns.html READ THIS FIRST Bdirectional LSTM layer implementation.
class	GravesLSTM LSTM layer implementation.
class	LSTM LSTM layer implementation.
class	RnnOutputLayer Recurrent Neural Network Output Layer. Handles calculation of gradients etc for various objective functions. Functionally the same as OutputLayer, but handles output and label reshaping automatically. Input and output activations are same as other RNN layers: 3 dimensions with shape [miniBatchSize,nIn,timeSeriesLength] and [miniBatchSize,nOut,timeSeriesLength] respectively.

Methods in org.deeplearning4j.nn.layers.recurrent with parameters of type BaseLayer

Modifier and Type

Method and Description

static FwdPassReturn

LSTMHelpers.activateHelper(BaseLayer layer, NeuralNetConfiguration conf, org.nd4j.linalg.activations.IActivation gateActivationFn, org.nd4j.linalg.api.ndarray.INDArray input, org.nd4j.linalg.api.ndarray.INDArray recurrentWeights, org.nd4j.linalg.api.ndarray.INDArray originalInputWeights, org.nd4j.linalg.api.ndarray.INDArray biases, boolean training, org.nd4j.linalg.api.ndarray.INDArray originalPrevOutputActivations, org.nd4j.linalg.api.ndarray.INDArray originalPrevMemCellState, boolean forBackprop, boolean forwards, String inputWeightKey, org.nd4j.linalg.api.ndarray.INDArray maskArray, boolean hasPeepholeConnections, LSTMHelper helper, CacheMode cacheMode) Returns FwdPassReturn object with activations/INDArrays.

Uses of BaseLayer in org.deeplearning4j.nn.layers.training

Subclasses of BaseLayer in org.deeplearning4j.nn.layers.training

Modifier and Type	Class and Description
class	CenterLossOutputLayer Center loss is similar to triplet loss except that it enforces intraclass consistency and doesn't require feed forward of multiple examples.