Package deepnetts.tensor

Class Tensors

java.lang.Object

deepnetts.tensor.Tensors

public class Tensors
extends Object

Static utility methods for tensors.

Method Summary

Modifier and Type	Method	Description
static float[]	absMax(float[] arr, float[] max)	Returns array with max values for each position in the given input vectors.
static TensorBase	absMax(TensorBase t, TensorBase max)	Returns tensors with max value for each component of input tensors.
static float[]	absMin(float[] arr, float[] min)
static TensorBase	absMin(TensorBase t, TensorBase min)
static final void	add(float[] array1, float[] array2)	Adds given vector and store result in first.
static final void	copy(float[] src, float[] dest)
static final void	copy(TensorBase src, TensorBase dest)
static float[]	copyOf(float[] arr)
static Tensor2D	create(int rows, int cols, float[] values)	Factory method for creating tensor instance,
static Tensor3D	create(int depth, int rows, int cols, float[] values)
static Tensor4D	create(int fourthDim, int depth, int rows, int cols, float[] values)
static void	div(float[] array, float val)
static void	div(float[] array, float[] divisor)
static Tensor1D	dotProduct(Tensor2D matrixA, Tensor1D vectorB, Tensor1D resultC)	Dot product matrix vector multiplication C = A .
static void	dotProduct(Tensor2D matrixA, Tensor2D matrixB, Tensor2D result)
static void	dotProductBuffered(Tensor2D matrixA, Tensor1D vectorB, Tensor1D resultC)	Matrix vector dot product.
static void	dotProductBuffered(Tensor2D matrixA, Tensor2D matrixB, Tensor2D result)
static void	fillFourthDim(Tensor4D deltaWeights, int fourthIdx, float val)
static TensorBase	fromFile(String filePath)
static void	max(TensorBase t1, TensorBase t2, TensorBase result)
static void	min(TensorBase t1, TensorBase t2, TensorBase result)
static void	multiply(float[] arr1, float[] arr2)
static Tensor1D	ones(int size)
static float[]	parseFloats(String str)
static int[]	parseInts(String str)
static Tensor1D	random(int size)	Generates a random 1D tensor with the specified dimensions.
static Tensor2D	random(int rows, int cols)	Create and return a tensor with specified number of rows and cols filled with random values.
static Tensor3D	random(int depth, int rows, int cols)
static Tensor4D	random(int fourthDim, int depth, int rows, int cols)
static void	sub(float[] arr, float val)
static final void	sub(float[] array1, float[] array2)
static Tensor1D	zeros(int size)

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Method Details

copyOf

public static float[] copyOf(float[] arr)

copy

public static final void copy(TensorBase src,
 TensorBase dest)

copy

public static final void copy(float[] src,
 float[] dest)

sub

public static void sub(float[] arr,
 float val)

multiply

public static void multiply(float[] arr1,
 float[] arr2)

fillFourthDim

public static void fillFourthDim(Tensor4D deltaWeights,
 int fourthIdx,
 float val)

absMax

public static TensorBase absMax(TensorBase t,
 TensorBase max)

Returns tensors with max value for each component of input tensors.

Parameters:

t -

max - proposed max tensor

Returns:

tensor with max value for each component

absMax

public static float[] absMax(float[] arr,
 float[] max)

Returns array with max values for each position in the given input vectors. Stores max values in second parameter.

Parameters:

arr -

max -

Returns:

absMin

public static TensorBase absMin(TensorBase t,
 TensorBase min)

absMin

public static float[] absMin(float[] arr,
 float[] min)

div

public static void div(float[] array,
 float val)

div

public static void div(float[] array,
 float[] divisor)

dotProduct

public static Tensor1D dotProduct(Tensor2D matrixA,
 Tensor1D vectorB,
 Tensor1D resultC)

Dot product matrix vector multiplication C = A . B

Parameters:

matrixA -

vectorB -

resultC -

dotProductBuffered

public static void dotProductBuffered(Tensor2D matrixA,
 Tensor1D vectorB,
 Tensor1D resultC)

Matrix vector dot product. Using matrix row buffering to accelerate computation.

Parameters:

matrixA -

vectorB -

resultC -

dotProduct

public static void dotProduct(Tensor2D matrixA,
 Tensor2D matrixB,
 Tensor2D result)

dotProductBuffered

public static void dotProductBuffered(Tensor2D matrixA,
 Tensor2D matrixB,
 Tensor2D result)

sub

public static final void sub(float[] array1,
 float[] array2)

add

public static final void add(float[] array1,
 float[] array2)

Adds given vector and store result in first.

Parameters:

array1 -

array2 -

zeros

public static Tensor1D zeros(int size)

ones

public static Tensor1D ones(int size)

random

public static Tensor1D random(int size)

Generates a random 1D tensor with the specified dimensions. Random values are uniformly distributed in range [0, 1]

Parameters:

size - size of the 1 dim tensor

Returns:

1D tensor filled with random values from global random num generator.

random

public static Tensor2D random(int rows,
 int cols)

Create and return a tensor with specified number of rows and cols filled with random values.

Parameters:

rows - number of rows

cols - number of columns

Returns:

a random tensor of specificed dimensions

random

public static Tensor3D random(int depth,
 int rows,
 int cols)

random

public static Tensor4D random(int fourthDim,
 int depth,
 int rows,
 int cols)

min

public static void min(TensorBase t1,
 TensorBase t2,
 TensorBase result)

max

public static void max(TensorBase t1,
 TensorBase t2,
 TensorBase result)

create

public static Tensor2D create(int rows,
 int cols,
 float[] values)

Factory method for creating tensor instance,

Parameters:

rows -

cols -

values -

Returns:

create

public static Tensor3D create(int depth,
 int rows,
 int cols,
 float[] values)

create

public static Tensor4D create(int fourthDim,
 int depth,
 int rows,
 int cols,
 float[] values)

fromFile

public static TensorBase fromFile(String filePath)
                           throws IOException

Throws:

IOException

parseInts

public static int[] parseInts(String str)

parseFloats

public static float[] parseFloats(String str)