Uses of Class
deepnetts.tensor.TensorBase

Packages that use TensorBase

Package	Description
deepnetts.cudnn
deepnetts.data	Data structures to store example data used for building machine learning models.
deepnetts.data.norm	Data normalization methods, used to scale data to specific range, in order to make them suitable for use by a neural network.
deepnetts.net	Neural network architectures with their corresponding builders.
deepnetts.net.layers	Neural network layers, which are main building blocks of a neural network.
deepnetts.net.layers.activation	Activation functions for neural network layers.
deepnetts.net.loss	Commonly used loss functions, which are used to calculate error during the training as a difference between predicted and target output.
deepnetts.tensor
deepnetts.util	Various utility classes including Tensor, image operations, multithreading, exceptions etc.

Uses of TensorBase in deepnetts.cudnn

Methods in deepnetts.cudnn that return TensorBase

Modifier and Type	Method	Description
TensorBase	CudaTensor.getTensor()
TensorBase	CudaTensorBridge.getTensor()

Constructors in deepnetts.cudnn with parameters of type TensorBase

Modifier	Constructor	Description
	CudaTensor(TensorBase tensor)
	CudaTensorBridge(TensorBase tensor)	Alocate tensor on cuda device, copy from jvm memory to cuda and back
	FullyConnectedBackwardCuda(CudaHandles cudaHandles, TensorBase outputs, TensorBase weights, TensorBase biases, TensorBase inputs)
	FullyConnectedForwardCuda(CudaHandles cudaHandles, TensorBase outputs, TensorBase weights, TensorBase biases, TensorBase inputs)
	SoftMaxBackwardCuda(CudaHandles cudaHandles, TensorBase deltas, TensorBase weights, TensorBase biases, TensorBase inputs)
	SoftMaxForwardCuda(CudaHandles cudaHandles, TensorBase outputs, TensorBase weights, TensorBase biases, TensorBase inputs)

Uses of TensorBase in deepnetts.data

Methods in deepnetts.data that return TensorBase

Modifier and Type	Method	Description
TensorBase	MLDataItem.getInput()	Returns an input for machine learning model of this item.
TensorBase	TabularDataSet.Item.getInput()
TensorBase	ImageSet.getMean()
TensorBase	ExampleImage.getTargetOutput()
TensorBase	MLDataItem.getTargetOutput()	Returns target output for machine learning model of this item.
TensorBase	TabularDataSet.Item.getTargetOutput()
TensorBase	ImageSet.zeroMean()	Applies zero mean normalization to entire dataset, and returns mean tensor.
TensorBase	ImageSet.zeroMeanAndNormalize()
TensorBase	ImageSet.zeroMeanPerChannel()

Methods in deepnetts.data with parameters of type TensorBase

Modifier and Type	Method	Description
final void	ExampleImage.setTargetOutput(TensorBase targetOutput)

Constructors in deepnetts.data with parameters of type TensorBase

Modifier	Constructor	Description
	Item(TensorBase input, TensorBase targetOutput)

Uses of TensorBase in deepnetts.data.norm

Methods in deepnetts.data.norm that return TensorBase

Modifier and Type	Method	Description
TensorBase	MaxScaler.getMaxInputs()
TensorBase	MaxScaler.getMaxOutputs()

Methods in deepnetts.data.norm with parameters of type TensorBase

Modifier and Type	Method	Description
void	MaxScaler.deNormalizeInputs(TensorBase inputs)
void	MaxScaler.deNormalizeOutputs(TensorBase outputs)	De-normalize given output vector in-place.
void	MaxScaler.normalizeInput(TensorBase input)
abstract void	AbstractScaler.scaleInput(TensorBase input)	Normalize input of deployed model
void	DecimalScaler.scaleInput(TensorBase input)
void	MaxScaler.scaleInput(TensorBase input)
void	MinMaxScaler.scaleInput(TensorBase input)
void	RangeScaler.scaleInput(TensorBase input)
void	Standardizer.scaleInput(TensorBase input)
void	MaxScaler.setMaxInputs(TensorBase maxInputs)
void	MaxScaler.setMaxOutputs(TensorBase maxOutputs)

Uses of TensorBase in deepnetts.net

Methods in deepnetts.net that return TensorBase

Modifier and Type	Method	Description
TensorBase	NeuralNetwork.getOutput()	Returns network's output.
TensorBase	NeuralNetwork.predict(TensorBase input)	Returns the prediction of this neural network for the given input.

Methods in deepnetts.net that return types with arguments of type TensorBase

Modifier and Type	Method	Description
List<TensorBase>	ConvolutionalNetwork.getDeltaWeights()	Returns delta weights for all layers.
List<TensorBase>	ConvolutionalNetwork.getLayersOutputs()	Returns outputs of all layers.
Preprocessing<TensorBase>	NeuralNetwork.getPreprocessing()	Gets preprocessing that needs to be performed before input is fed to this network.
List<TensorBase>	ConvolutionalNetwork.getWeights()	Returns weights from all layers in this network as a list of tensors.

Methods in deepnetts.net with parameters of type TensorBase

Modifier and Type	Method	Description
TensorBase	NeuralNetwork.predict(TensorBase input)	Returns the prediction of this neural network for the given input.
void	ConvolutionalNetwork.setInput(TensorBase input)
void	NeuralNetwork.setInput(TensorBase inputs)	Sets network input and calculates entire network (triggers forward pass).
void	NeuralNetwork.setOutputError(TensorBase outputErrors)	Sets the network's output errors, which are a difference between actual(predicted) and target output.

Method parameters in deepnetts.net with type arguments of type TensorBase

Modifier and Type	Method	Description
void	NeuralNetwork.setPreprocessing(Preprocessing<TensorBase> preprocessing)	Sets preprocessing that needs to be performed before input is fed to this network.

Uses of TensorBase in deepnetts.net.layers

Classes in deepnetts.net.layers with type parameters of type TensorBase

Modifier and Type	Class	Description
class	AbstractLayer<I extends TensorBase,O extends TensorBase,W extends TensorBase>	Base class for different types of layers.
class	AbstractLayer<I extends TensorBase,O extends TensorBase,W extends TensorBase>	Base class for different types of layers.
class	AbstractLayer<I extends TensorBase,O extends TensorBase,W extends TensorBase>	Base class for different types of layers.
interface	Layer<O extends TensorBase>	Common base interface for all types of neural network layers.

Methods in deepnetts.net.layers that return TensorBase

Modifier and Type	Method	Description
TensorBase	AbstractLayer.getBiases()
TensorBase	ConvolutionalLayer.getFilterDeltaWeights()
TensorBase	ConvolutionalLayer.getFilters()
final TensorBase	AbstractLayer.getGradients()
final TensorBase	OutputLayer.getOutputErrors()

Methods in deepnetts.net.layers with parameters of type TensorBase

Modifier and Type	Method	Description
void	InputLayer.setInput(TensorBase in)	Sets network input
final void	OutputLayer.setOutputErrors(TensorBase outputErrors)

Uses of TensorBase in deepnetts.net.layers.activation

Methods in deepnetts.net.layers.activation with parameters of type TensorBase

Modifier and Type	Method	Description
default void	ActivationFunction.accept(TensorBase tensor)
void	ActivationFunction.apply(TensorBase tensor, int from, int to)
void	LeakyRelu.apply(TensorBase tensor, int from, int to)
void	Linear.apply(TensorBase tensor, int from, int to)
void	Relu.apply(TensorBase tensor, int from, int to)
void	Sigmoid.apply(TensorBase tensor, int from, int to)
void	SoftSign.apply(TensorBase tensor, int from, int to)
void	Tanh.apply(TensorBase tensor, int from, int to)

Uses of TensorBase in deepnetts.net.loss

Methods in deepnetts.net.loss that return TensorBase

Modifier and Type	Method	Description
TensorBase	BinaryCrossEntropyLoss.addPatternError(TensorBase predictedOutput, TensorBase targetOutput)
TensorBase	CrossEntropyLoss.addPatternError(TensorBase predictedOut, TensorBase targetOut)
TensorBase	LossFunction.addPatternError(TensorBase predictedOutput, TensorBase targetOutput)
TensorBase	MeanSquaredErrorLoss.addPatternError(TensorBase predictedOut, TensorBase targetOut)

Methods in deepnetts.net.loss with parameters of type TensorBase

Modifier and Type	Method	Description
TensorBase	BinaryCrossEntropyLoss.addPatternError(TensorBase predictedOutput, TensorBase targetOutput)
TensorBase	CrossEntropyLoss.addPatternError(TensorBase predictedOut, TensorBase targetOut)
TensorBase	LossFunction.addPatternError(TensorBase predictedOutput, TensorBase targetOutput)
TensorBase	MeanSquaredErrorLoss.addPatternError(TensorBase predictedOut, TensorBase targetOut)

Uses of TensorBase in deepnetts.tensor

Subclasses of TensorBase in deepnetts.tensor

Modifier and Type	Class	Description
class	Tensor1D	One dimensional tensor - a vector or an array.
final class	Tensor2D	A 2D tensor / matrix with specified number of rows and columns..
class	Tensor3D
class	Tensor4D

Methods in deepnetts.tensor that return TensorBase

Modifier and Type	Method	Description
static TensorBase	Tensors.absMax(TensorBase t, TensorBase max)	Returns tensors with max value for each component of input tensors.
static TensorBase	Tensors.absMin(TensorBase t, TensorBase min)
final TensorBase	TensorBase.add(TensorBase t)	Adds specified tensor t to this tensor.
final TensorBase	TensorBase.addInto(TensorBase t, TensorBase result)
TensorBase	TensorBase.apply(ActivationFunction af)
TensorBase	Tensor1D.copy()
TensorBase	Tensor2D.copy()
TensorBase	Tensor3D.copy()
TensorBase	Tensor4D.copy()
TensorBase	TensorBase.copy()
static TensorBase	Tensors.fromFile(String filePath)
TensorBase	TensorBase.multiply(float m)	Multiplies all the values in tensor with a specified input parameter.
TensorBase	TensorBase.sqr()
final TensorBase	TensorBase.subInto(TensorBase t, TensorBase result)

Methods in deepnetts.tensor with parameters of type TensorBase

Modifier and Type	Method	Description
static TensorBase	Tensors.absMax(TensorBase t, TensorBase max)	Returns tensors with max value for each component of input tensors.
static TensorBase	Tensors.absMin(TensorBase t, TensorBase min)
final TensorBase	TensorBase.add(TensorBase t)	Adds specified tensor t to this tensor.
final TensorBase	TensorBase.addInto(TensorBase t, TensorBase result)
static final void	Tensors.copy(TensorBase src, TensorBase dest)
final void	TensorBase.copyFrom(TensorBase src)
final void	TensorBase.div(TensorBase t)	Element-wise divison with specified tensor.
boolean	TensorBase.equals(TensorBase t2, float delta)
static void	Tensors.max(TensorBase t1, TensorBase t2, TensorBase result)
static void	Tensors.min(TensorBase t1, TensorBase t2, TensorBase result)
void	TensorBase.multiplyElementWise(TensorBase tensor2)
final void	TensorBase.sub(TensorBase t)	Subtracts specified tensor t from this tensor.
static final void	TensorBase.subInplace(TensorBase t1, TensorBase t2)	Subtracts tensor t2 from t1.
final TensorBase	TensorBase.subInto(TensorBase t, TensorBase result)
static String	TensorBase.valuesAsString(TensorBase[] tensors)

Constructors in deepnetts.tensor with parameters of type TensorBase

Modifier	Constructor	Description
	TensorBase(TensorBase t)	Public deep copy / clone constructor.

Uses of TensorBase in deepnetts.util

Methods in deepnetts.util that return TensorBase

Modifier and Type	Method	Description
TensorBase	ImagePreprocessing.getMean()

Methods in deepnetts.util with parameters of type TensorBase

Modifier and Type	Method	Description
void	ImagePreprocessing.apply(TensorBase input)
void	ImagePreprocessing.setMean(TensorBase mean)