Uses of Class
deepnetts.util.Tensor

Packages that use Tensor

Package	Description
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.util	Various utility classes including Tensor, image operations, multithreading, exceptions etc.

Uses of Tensor in deepnetts.data

Methods in deepnetts.data that return Tensor

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

Methods in deepnetts.data with parameters of type Tensor

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

Constructors in deepnetts.data with parameters of type Tensor

Constructor and Description
Item(Tensor input, Tensor targetOutput)

Uses of Tensor in deepnetts.data.norm

Methods in deepnetts.data.norm that return Tensor

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

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

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

Uses of Tensor in deepnetts.net

Methods in deepnetts.net that return Tensor

Modifier and Type	Method and Description
Tensor	NeuralNetwork.predict(Tensor input) Returns the prediction of this neural network for the given input.

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

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

Methods in deepnetts.net with parameters of type Tensor

Modifier and Type	Method and Description
Tensor	NeuralNetwork.predict(Tensor input) Returns the prediction of this neural network for the given input.
void	ConvolutionalNetwork.setInput(Tensor input)
void	NeuralNetwork.setInput(Tensor inputs) Sets network input and calculates entire network (triggers forward pass).

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

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

Uses of Tensor in deepnetts.net.layers

Methods in deepnetts.net.layers that return Tensor

Modifier and Type	Method and Description
Tensor	AbstractLayer.getDeltas()
Tensor	Layer.getDeltas() Returns layer deltas/errors (as a tensor).
Tensor	AbstractLayer.getDeltaWeights()
Tensor	ConvolutionalLayer.getFilterDeltaWeights()
Tensor	ConvolutionalLayer.getFilters()
Tensor	AbstractLayer.getGradients()
Tensor	AbstractLayer.getOutputs()
Tensor	Layer.getOutputs() Returns layer outputs (as a tensor).
Tensor	AbstractLayer.getPrevDeltaWeights()
Tensor	AbstractLayer.getWeights()

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

Modifier and Type	Method and Description
void	AbstractLayer.setDeltas(Tensor deltas)
void	ConvolutionalLayer.setFilters(Tensor filters)
void	InputLayer.setInput(Tensor in) Sets network input
void	AbstractLayer.setOutputs(Tensor outputs)
void	AbstractLayer.setPrevDeltaWeights(Tensor prevDeltaWeights)
void	AbstractLayer.setWeights(Tensor weights)

Uses of Tensor in deepnetts.net.layers.activation

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

Modifier and Type	Method and Description
void	ActivationFunction.apply(Tensor tensor, int channel)
void	LeakyRelu.apply(Tensor tensor, int channel)
void	Linear.apply(Tensor tensor, int channel)
void	Relu.apply(Tensor tensor, int channel)
void	Sigmoid.apply(Tensor tensor, int channel)
void	Tanh.apply(Tensor tensor, int channel)
void	ActivationFunction.apply(Tensor tensor, int from, int to)
void	LeakyRelu.apply(Tensor tensor, int from, int to)
void	Linear.apply(Tensor tensor, int from, int to)
void	Relu.apply(Tensor tensor, int from, int to)
void	Sigmoid.apply(Tensor tensor, int from, int to)
void	Tanh.apply(Tensor tensor, int from, int to)

Uses of Tensor in deepnetts.util

Methods in deepnetts.util that return Tensor

Modifier and Type	Method and Description
static Tensor	Tensors.absMax(Tensor t, Tensor max) Returns tensors with max value for each component of input tensors.
static Tensor	Tensors.absMin(Tensor t, Tensor min)
Tensor	Tensor.clone()
Tensor	Tensor.copy()
static Tensor	Tensor.create(int rows, int cols, float[] values) Factory method for creating tensor instance,
static Tensor	Tensor.create(int rows, int cols, int depth, float[] values)
static Tensor	Tensor.create(int rows, int cols, int depth, int fourthDim, float[] values)
Tensor	ImagePreprocessing.getMean()
static Tensor	Tensor.of(float[] values)
static Tensor	Tensors.ones(int cols)
static Tensor	Tensors.random(int size)
static Tensor	Tensors.random(int rows, int cols) Generate and return random tensor with specified number of rows and cols.
static Tensor	Tensors.random(int rows, int cols, int depth)
static Tensor	Tensors.random(int rows, int cols, int depth, int fourthDim)
static Tensor	Tensors.zeros(int cols)

Methods in deepnetts.util with parameters of type Tensor

Modifier and Type	Method and Description
static Tensor	Tensors.absMax(Tensor t, Tensor max) Returns tensors with max value for each component of input tensors.
static Tensor	Tensors.absMin(Tensor t, Tensor min)
void	Tensor.add(Tensor t) Adds specified tensor t to this tensor.
void	ImagePreprocessing.apply(Tensor input)
static void	Tensors.copy(Tensor src, Tensor dest)
void	Tensor.div(Tensor t)
boolean	Tensor.equals(Tensor t2, float delta)
static void	Tensors.fillFourthDim(Tensor deltaWeights, int fourthIdx, float val)
static void	Tensors.max(Tensor t1, Tensor t2, Tensor result)
static void	Tensors.min(Tensor t1, Tensor t2, Tensor result)
void	Tensor.multiplyElementWise(Tensor tensor2)
void	ImagePreprocessing.setMean(Tensor mean)
void	Tensor.sub(Tensor t) Subtracts specified tensor t from this tensor.
static void	Tensor.sub(Tensor t1, Tensor t2) Subtracts tensor t2 from t1.
static String	Tensor.valuesAsString(Tensor[] tensors)

Constructors in deepnetts.util with parameters of type Tensor

Constructor and Description
Tensor(Tensor t) Public deep copy / clone constructor.