Package io.github.kirstenali.deepj.tensor

Interface TensorBackend

All Known Implementing Classes:

CpuBackend, MetalBackend

public interface TensorBackend

Method Summary

Modifier and Type	Method	Description
void	adamWUpdate(Tensor w, Tensor g, Tensor mt, Tensor vt, double lr, double beta1, double beta2, double eps, double weightDecay, double bc1, double bc2)	In-place AdamW update.
Tensor	add(Tensor a, Tensor b)
Tensor	addBroadcastCols(Tensor a, Tensor colVector)
Tensor	addBroadcastRows(Tensor a, Tensor rowVector)
default void	addInPlace(Tensor a, Tensor b)
Tensor	addRowVector(Tensor a, Tensor rowVector)
Tensor	addScalar(Tensor a, double scalar)
default void	addScalarInPlace(Tensor a, double s)
Tensor	causalMask(int size)
Tensor	clamp(Tensor a, double min, double max)
Tensor	crossEntropyGradient(Tensor logits, int[] targets)
double	crossEntropyLoss(Tensor logits, int[] targets)
Tensor	divide(Tensor a, Tensor b)
Tensor	divideBroadcastCols(Tensor a, Tensor colVector)
default void	divideInPlace(Tensor a, Tensor b)
Tensor	divideScalar(Tensor a, double scalar)
default void	divideScalarInPlace(Tensor a, double s)
Tensor	exp(Tensor a)
default void	expInPlace(Tensor a)
double[]	flattenTensor(Tensor t)
Tensor	gelu(Tensor a)
Tensor	geluBackward(Tensor input, Tensor gradOutput)
default void	geluInPlace(Tensor a)
double	get(Tensor t, int r, int c)
Tensor	getRow(Tensor t, int row)
Tensor	layerNormBackward(Tensor dXHat, Tensor xHat, Tensor std, int dim)	LayerNorm backward through normalization (given dXHat, xHat, std).
Tensor	log(Tensor a)
default void	logInPlace(Tensor a)
default void	materializeTensor(Tensor t)	Materialize a tensor: flush any pending GPU computation and download the result to the tensor's CPU data[][].
Tensor	matmul(Tensor a, Tensor b)
Tensor	maxAlongRows(Tensor a)
Tensor	meanAlongRows(Tensor a)
Tensor	multiply(Tensor a, Tensor b)
Tensor	multiplyBroadcastCols(Tensor a, Tensor colVector)
Tensor	multiplyBroadcastRows(Tensor a, Tensor rowVector)
default void	multiplyInPlace(Tensor a, Tensor b)
Tensor	multiplyScalar(Tensor a, double scalar)
default void	multiplyScalarInPlace(Tensor a, double s)
Tensor	neg(Tensor a)
default void	negInPlace(Tensor a)
Tensor	ones(int rows, int cols)
Tensor	pow(Tensor a, double exponent)
void	print(Tensor t, String label)
Tensor	random(int rows, int cols, Random rand)
default void	releaseResources()	Release backend-owned resources (GPU buffers, native handles, etc.).
Tensor	relu(Tensor a)
Tensor	reluBackward(Tensor input, Tensor gradOutput)
default void	reluInPlace(Tensor a)
Tensor	sampleRows(Tensor t, int n, Random rnd)	Sample random rows from t.
void	scatterAddRows(Tensor target, int[] indices, Tensor grad)	Scatter-add: target.data[indices[i]] += grad.data[i] (for embedding backward).
void	set(Tensor t, int r, int c, double value)
void	setRow(Tensor t, int row, Tensor source, int srcRow)
Tensor	sigmoid(Tensor a)
default void	sigmoidInPlace(Tensor a)
Tensor	sliceRows(Tensor t, int[] rowIndices, int cols)	Gather rows by index (for embedding lookup).
Tensor	softmaxBackward(Tensor gradOutput, Tensor softmaxOut)
Tensor	softmaxRows(Tensor logits)
Tensor	sqrt(Tensor a)
default void	sqrtInPlace(Tensor a)
Tensor	subtract(Tensor a, Tensor b)
Tensor	subtractBroadcastCols(Tensor a, Tensor colVector)
default void	subtractInPlace(Tensor a, Tensor b)
double	sum(Tensor a)
double	sumAbs(Tensor a)
Tensor	sumAlongCols(Tensor a)
Tensor	sumAlongRows(Tensor a)
Tensor	sumRows(Tensor a)
Tensor	tanh(Tensor a)
default void	tanhInPlace(Tensor a)
Tensor	transpose(Tensor a)
Tensor	unflattenToTensor(double[] flat, int rows, int cols)
Tensor	varianceAlongRows(Tensor a)
Tensor	zeros(int rows, int cols)

Method Details

zeros

Tensor zeros(int rows,
 int cols)

ones

Tensor ones(int rows,
 int cols)

random

Tensor random(int rows,
 int cols,
 Random rand)

causalMask

Tensor causalMask(int size)

unflattenToTensor

Tensor unflattenToTensor(double[] flat,
 int rows,
 int cols)

flattenTensor

double[] flattenTensor(Tensor t)

matmul

Tensor matmul(Tensor a,
 Tensor b)

add

Tensor add(Tensor a,
 Tensor b)

subtract

Tensor subtract(Tensor a,
 Tensor b)

multiply

Tensor multiply(Tensor a,
 Tensor b)

divide

Tensor divide(Tensor a,
 Tensor b)

addRowVector

Tensor addRowVector(Tensor a,
 Tensor rowVector)

addBroadcastCols

Tensor addBroadcastCols(Tensor a,
 Tensor colVector)

divideBroadcastCols

Tensor divideBroadcastCols(Tensor a,
 Tensor colVector)

subtractBroadcastCols

Tensor subtractBroadcastCols(Tensor a,
 Tensor colVector)

multiplyBroadcastCols

Tensor multiplyBroadcastCols(Tensor a,
 Tensor colVector)

addBroadcastRows

Tensor addBroadcastRows(Tensor a,
 Tensor rowVector)

multiplyBroadcastRows

Tensor multiplyBroadcastRows(Tensor a,
 Tensor rowVector)

multiplyScalar

Tensor multiplyScalar(Tensor a,
 double scalar)

addScalar

Tensor addScalar(Tensor a,
 double scalar)

divideScalar

Tensor divideScalar(Tensor a,
 double scalar)

sumRows

Tensor sumRows(Tensor a)

sumAlongRows

Tensor sumAlongRows(Tensor a)

sumAlongCols

Tensor sumAlongCols(Tensor a)

meanAlongRows

Tensor meanAlongRows(Tensor a)

varianceAlongRows

Tensor varianceAlongRows(Tensor a)

maxAlongRows

Tensor maxAlongRows(Tensor a)

sum

double sum(Tensor a)

sumAbs

double sumAbs(Tensor a)

clamp

Tensor clamp(Tensor a,
 double min,
 double max)

transpose

Tensor transpose(Tensor a)

sqrt

Tensor sqrt(Tensor a)

pow

Tensor pow(Tensor a,
 double exponent)

neg

Tensor neg(Tensor a)

exp

Tensor exp(Tensor a)

log

Tensor log(Tensor a)

tanh

Tensor tanh(Tensor a)

sigmoid

Tensor sigmoid(Tensor a)

relu

Tensor relu(Tensor a)

reluBackward

Tensor reluBackward(Tensor input,
 Tensor gradOutput)

gelu

Tensor gelu(Tensor a)

geluBackward

Tensor geluBackward(Tensor input,
 Tensor gradOutput)

softmaxRows

Tensor softmaxRows(Tensor logits)

softmaxBackward

Tensor softmaxBackward(Tensor gradOutput,
 Tensor softmaxOut)

crossEntropyLoss

double crossEntropyLoss(Tensor logits,
 int[] targets)

crossEntropyGradient

Tensor crossEntropyGradient(Tensor logits,
 int[] targets)

adamWUpdate

void adamWUpdate(Tensor w,
 Tensor g,
 Tensor mt,
 Tensor vt,
 double lr,
 double beta1,
 double beta2,
 double eps,
 double weightDecay,
 double bc1,
 double bc2)

In-place AdamW update. Mutates w, mt, vt.

layerNormBackward

Tensor layerNormBackward(Tensor dXHat,
 Tensor xHat,
 Tensor std,
 int dim)

LayerNorm backward through normalization (given dXHat, xHat, std).

get

double get(Tensor t,
 int r,
 int c)

set

void set(Tensor t,
 int r,
 int c,
 double value)

getRow

Tensor getRow(Tensor t,
 int row)

setRow

void setRow(Tensor t,
 int row,
 Tensor source,
 int srcRow)

sliceRows

Tensor sliceRows(Tensor t,
 int[] rowIndices,
 int cols)

Gather rows by index (for embedding lookup).

scatterAddRows

void scatterAddRows(Tensor target,
 int[] indices,
 Tensor grad)

Scatter-add: target.data[indices[i]] += grad.data[i] (for embedding backward).

sampleRows

Tensor sampleRows(Tensor t,
 int n,
 Random rnd)

Sample random rows from t.

print

void print(Tensor t,
 String label)

addInPlace

default void addInPlace(Tensor a,
 Tensor b)

subtractInPlace

default void subtractInPlace(Tensor a,
 Tensor b)

multiplyInPlace

default void multiplyInPlace(Tensor a,
 Tensor b)

divideInPlace

default void divideInPlace(Tensor a,
 Tensor b)

multiplyScalarInPlace

default void multiplyScalarInPlace(Tensor a,
 double s)

addScalarInPlace

default void addScalarInPlace(Tensor a,
 double s)

divideScalarInPlace

default void divideScalarInPlace(Tensor a,
 double s)

sqrtInPlace

default void sqrtInPlace(Tensor a)

negInPlace

default void negInPlace(Tensor a)

expInPlace

default void expInPlace(Tensor a)

logInPlace

default void logInPlace(Tensor a)

reluInPlace

default void reluInPlace(Tensor a)

geluInPlace

default void geluInPlace(Tensor a)

tanhInPlace

default void tanhInPlace(Tensor a)

sigmoidInPlace

default void sigmoidInPlace(Tensor a)

materializeTensor

default void materializeTensor(Tensor t)

Materialize a tensor: flush any pending GPU computation and download the result to the tensor's CPU data[][]. Default is a no-op (for CpuBackend).

releaseResources

default void releaseResources()

Release backend-owned resources (GPU buffers, native handles, etc.). Default is a no-op for backends without external resources.