Package io.github.kirstenali.deepj.tensor

Class Tensor

java.lang.Object
io.github.kirstenali.deepj.tensor.Tensor
public class Tensor extends Object

  • Field Details

    • data

      public final float[] data
      Flat row-major storage: element (r, c) lives at data[r * cols + c].

    • rows

      public final int rows

    • cols

      public final int cols

  • Constructor Details

    • Tensor

      public Tensor(int rows, int cols)

    • Tensor

      public Tensor(Tensor source)
      Copy constructor — creates an independent deep copy.

  • Method Details

    • getGpuTag

      public Object getGpuTag()
      Get the GPU handle (used by GPU backends).

    • setGpuTag

      public void setGpuTag(Object tag)
      Set the GPU handle (used by GPU backends).

    • setBackend

      public static void setBackend(TensorBackend backend)

    • backend

      public static TensorBackend backend()

    • rowData

      public float[] rowData(int r)
      Returns a fresh float[] copy of row r. Convenience for tests and debugging; not a view.

    • materialize

      public void materialize()
      Ensures this tensor's data[] is up to date with any pending GPU computation. No-op if this tensor has no GPU handle or is already materialized. Call this before reading data[] directly.

    • matmul

      public Tensor matmul(Tensor other)

    • add

      public Tensor add(Tensor other)

    • subtract

      public Tensor subtract(Tensor other)

    • multiply

      public Tensor multiply(Tensor other)

    • divide

      public Tensor divide(Tensor other)

    • addRowVector

      public Tensor addRowVector(Tensor rowVector)

    • addBroadcastCols

      public Tensor addBroadcastCols(Tensor colVector)

    • divideBroadcastCols

      public Tensor divideBroadcastCols(Tensor colVector)

    • subtractBroadcastCols

      public Tensor subtractBroadcastCols(Tensor colVector)

    • multiplyBroadcastCols

      public Tensor multiplyBroadcastCols(Tensor colVector)

    • addBroadcastRows

      public Tensor addBroadcastRows(Tensor rowVector)

    • multiplyBroadcastRows

      public Tensor multiplyBroadcastRows(Tensor rowVector)

    • multiplyScalar

      public Tensor multiplyScalar(float s)

    • addScalar

      public Tensor addScalar(float s)

    • divideScalar

      public Tensor divideScalar(float s)

    • sumRows

      public Tensor sumRows()

    • sumAlongRows

      public Tensor sumAlongRows()

    • sumAlongCols

      public Tensor sumAlongCols()

    • meanAlongRows

      public Tensor meanAlongRows()

    • varianceAlongRows

      public Tensor varianceAlongRows()

    • transpose

      public Tensor transpose()

    • sqrt

      public Tensor sqrt()

    • neg

      public Tensor neg()

    • exp

      public Tensor exp()

    • log

      public Tensor log()

    • tanhActivation

      public Tensor tanhActivation()

    • sigmoidActivation

      public Tensor sigmoidActivation()

    • reluActivation

      public Tensor reluActivation()

    • reluBackward

      public Tensor reluBackward(Tensor gradOutput)

    • geluActivation

      public Tensor geluActivation()

    • geluBackward

      public Tensor geluBackward(Tensor gradOutput)

    • addInPlace

      public Tensor addInPlace(Tensor b)

    • subtractInPlace

      public Tensor subtractInPlace(Tensor b)

    • multiplyInPlace

      public Tensor multiplyInPlace(Tensor b)

    • divideInPlace

      public Tensor divideInPlace(Tensor b)

    • multiplyScalarInPlace

      public Tensor multiplyScalarInPlace(float s)

    • addScalarInPlace

      public Tensor addScalarInPlace(float s)

    • divideScalarInPlace

      public Tensor divideScalarInPlace(float s)

    • sqrtInPlace

      public Tensor sqrtInPlace()

    • negInPlace

      public Tensor negInPlace()

    • expInPlace

      public Tensor expInPlace()

    • logInPlace

      public Tensor logInPlace()

    • reluInPlace

      public Tensor reluInPlace()

    • geluInPlace

      public Tensor geluInPlace()

    • tanhInPlace

      public Tensor tanhInPlace()

    • sigmoidInPlace

      public Tensor sigmoidInPlace()

    • softmaxRows

      public Tensor softmaxRows()

    • softmaxBackward

      public Tensor softmaxBackward(Tensor softmaxOut)

    • crossEntropyGradient

      public Tensor crossEntropyGradient(int[] targets)

    • adamWUpdate

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

    • layerNormBackward

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

    • maxAlongRows

      public Tensor maxAlongRows()

    • clamp

      public Tensor clamp(float min, float max)

    • pow

      public Tensor pow(float exponent)

    • scatterAddRows

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

    • from2D

      public static Tensor from2D(float[][] data)
      Build a tensor from 2-D row-major data. Preferred API for literal matrix construction.

    • sum

      public float sum()

    • sumAbs

      public float sumAbs()

    • crossEntropyLoss

      public float crossEntropyLoss(int[] targets)

    • get

      public float get(int r, int c)

    • set

      public void set(int r, int c, float value)

    • getRow

      public Tensor getRow(int row)

    • setRow

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

    • sliceRows

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

    • sampleRows

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

    • print

      public void print(String label)

    • zeros

      public static Tensor zeros(int rows, int cols)

    • ones

      public static Tensor ones(int rows, int cols)

    • random

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

    • causalMask

      public static Tensor causalMask(int size)

    • requireSameShape

      public static void requireSameShape(Tensor a, Tensor b, String op)

    • requireTargetsMatchRows

      public static void requireTargetsMatchRows(Tensor logits, int[] targets)