Uses of Class
deepnetts.tensor.Tensor1D

Packages that use Tensor1D

Package	Description
deepnetts.accl.spi
deepnetts.net.layers	Neural network layers, which are main building blocks of a neural network.
deepnetts.net.train.opt	Optimization methods used by training algorithm.
deepnetts.tensor

Uses of Tensor1D in deepnetts.accl.spi

Methods in deepnetts.accl.spi that return Tensor1D

Modifier and Type	Method	Description
Tensor1D	TensorVectorizationProvider.addVectorized(Tensor1D addTo, Tensor1D toAdd)
Tensor1D	TensorVectorizationProvider.matMulFma(Tensor2D matrixA, Tensor1D vector, Tensor1D result)
Tensor1D	TensorVectorizationProvider.matMulFmaParallel(Tensor2D matrixA, Tensor1D vector, Tensor1D result)
Tensor1D	TensorVectorizationProvider.matMulWithAddVector(Tensor2D matrixA, Tensor1D vector, Tensor1D result)
Tensor1D	TensorVectorizationProvider.matMulWithAddVectorParallel(Tensor2D matrixA, Tensor1D vector, Tensor1D result)

Methods in deepnetts.accl.spi with parameters of type Tensor1D

Modifier and Type	Method	Description
Tensor1D	TensorVectorizationProvider.addVectorized(Tensor1D addTo, Tensor1D toAdd)
Tensor2D	TensorVectorizationProvider.addVectorized(Tensor2D addTo, Tensor1D toAdd)
void	ActivationVectorizationProvider.applySoftmaxVectorized(Tensor1D outputs1D, float maxWs)
Tensor1D	TensorVectorizationProvider.matMulFma(Tensor2D matrixA, Tensor1D vector, Tensor1D result)
Tensor1D	TensorVectorizationProvider.matMulFmaParallel(Tensor2D matrixA, Tensor1D vector, Tensor1D result)
Tensor1D	TensorVectorizationProvider.matMulWithAddVector(Tensor2D matrixA, Tensor1D vector, Tensor1D result)
Tensor1D	TensorVectorizationProvider.matMulWithAddVectorParallel(Tensor2D matrixA, Tensor1D vector, Tensor1D result)
void	TensorVectorizationProvider.outerProductVectorized(Tensor1D firstTensor, Tensor1D otherTensor, Tensor2D result)

Uses of Tensor1D in deepnetts.net.layers

Fields in deepnetts.net.layers declared as Tensor1D

Modifier and Type	Field	Description
protected Tensor1D	AbstractLayer.biases
protected Tensor1D	AbstractLayer.deltaBiases
protected Tensor1D	AbstractLayer.prevDeltaBiases

Methods in deepnetts.net.layers that return Tensor1D

Modifier and Type	Method	Description
Tensor1D	AbstractLayer.getBiases()
Tensor1D	AbstractLayer.getDeltaBiases()
Tensor1D	AbstractLayer.getPrevDeltaBiases()

Methods in deepnetts.net.layers with parameters of type Tensor1D

Modifier and Type	Method	Description
void	SoftmaxOutputLayer.applySoftmax(Tensor1D outputs1D, float maxWs)	/ prva implementacija single threaded ubaci da izvrti batch u for petlji, onda paralelizuj batch
void	AbstractLayer.setBiases(Tensor1D biases)

Uses of Tensor1D in deepnetts.net.train.opt

Methods in deepnetts.net.train.opt that return Tensor1D

Modifier and Type	Method	Description
Tensor1D	AdaDeltaOptimizer.calculateDeltaBias(Tensor1D grad)
Tensor1D	AdaGradOptimizer.calculateDeltaBias(Tensor1D grad)
Tensor1D	AdamOptimizer.calculateDeltaBias(Tensor1D grad)
Tensor1D	MomentumOptimizer.calculateDeltaBias(Tensor1D grad)
Tensor1D	Optimizer.calculateDeltaBias(Tensor1D grad)
Tensor1D	RmsPropOptimizer.calculateDeltaBias(Tensor1D grad)
Tensor1D	SgdOptimizer.calculateDeltaBias(Tensor1D grad)

Methods in deepnetts.net.train.opt with parameters of type Tensor1D

Modifier and Type	Method	Description
Tensor1D	AdaDeltaOptimizer.calculateDeltaBias(Tensor1D grad)
Tensor1D	AdaGradOptimizer.calculateDeltaBias(Tensor1D grad)
Tensor1D	AdamOptimizer.calculateDeltaBias(Tensor1D grad)
Tensor1D	MomentumOptimizer.calculateDeltaBias(Tensor1D grad)
Tensor1D	Optimizer.calculateDeltaBias(Tensor1D grad)
Tensor1D	RmsPropOptimizer.calculateDeltaBias(Tensor1D grad)
Tensor1D	SgdOptimizer.calculateDeltaBias(Tensor1D grad)

Uses of Tensor1D in deepnetts.tensor

Methods in deepnetts.tensor that return Tensor1D

Modifier and Type	Method	Description
final Tensor1D	Tensor1D.add(Tensor1D toAdd)
static Tensor1D	Tensors.dotProduct(Tensor2D matrixA, Tensor1D vectorB, Tensor1D resultC)	Dot product matrix vector multiplication C = A .
static Tensor1D	Tensor1D.fromFile(String filePath)
Tensor1D	Tensor2D.matMul(Tensor1D vectorB, Tensor1D result)	Performs matrix multiplication with this 2d tensor and vector , and stores results in result tensor.
Tensor1D	Tensor2D.matMulVectorized(Tensor1D vector, Tensor1D result)
static Tensor1D	Tensor1D.of(float[] values)	Create and return a 1D tensor of specified values.
static Tensor1D	Tensors.ones(int size)
static Tensor1D	Tensors.random(int size)	Generates a random 1D tensor with the specified dimensions.
Tensor1D	Tensor2D.sqrSumByCol(Tensor1D sumSqr)
Tensor1D	Tensor2D.sumByColInto(Tensor1D sumTensor)
static Tensor1D	Tensors.zeros(int size)

Methods in deepnetts.tensor with parameters of type Tensor1D

Modifier and Type	Method	Description
final Tensor1D	Tensor1D.add(Tensor1D toAdd)
final Tensor2D	Tensor2D.add(Tensor1D toAdd)
static void	Tensors.dotProduct(Tensor1D vectorA, Tensor1D vectorB, Tensor1D result)
static Tensor1D	Tensors.dotProduct(Tensor2D matrixA, Tensor1D vectorB, Tensor1D resultC)	Dot product matrix vector multiplication C = A .
static void	Tensors.dotProductBuffered(Tensor2D matrixA, Tensor1D vectorB, Tensor1D resultC)	Matrix vector dot product.
Tensor1D	Tensor2D.matMul(Tensor1D vectorB, Tensor1D result)	Performs matrix multiplication with this 2d tensor and vector , and stores results in result tensor.
Tensor1D	Tensor2D.matMulVectorized(Tensor1D vector, Tensor1D result)
void	Tensor1D.outerProduct(Tensor1D otherTensor, Tensor2D result)
Tensor1D	Tensor2D.sqrSumByCol(Tensor1D sumSqr)
Tensor1D	Tensor2D.sumByColInto(Tensor1D sumTensor)