skainet-lang-core/sk.ainet.lang.tensor.data/DenseTensorDataFactory

DenseTensorDataFactory

class DenseTensorDataFactory : TensorDataFactory(source)

Low level DenseTensorDataFactory factories.

Constructors

constructor()

Functions

fromByteArray

fun <T : DType, V> fromByteArray(data: ByteArray, dtype: T): TensorData<T, V>

Creates a tensor from byte array data for various data types.

open override fun <T : DType, V> fromByteArray(shape: Shape, dtype: KClass<T>, data: ByteArray): TensorData<T, V>

fromFloatArray

fun <T : DType, V> fromFloatArray(data: FloatArray, dtype: T): TensorData<T, V>

Creates a tensor from float array with specified data type (overloaded version).

fun <T : DType> fromFloatArray(shape: Shape, data: FloatArray, dtype: T): TensorData<T, Float>

open override fun <T : DType, V> fromFloatArray(shape: Shape, dtype: KClass<T>, data: FloatArray): TensorData<T, V>

fromIntArray

fun <T : DType, V> fromIntArray(data: IntArray, dtype: T): TensorData<T, V>

Creates a tensor from int array with specified data type.

open override fun <T : DType, V> fromIntArray(shape: Shape, dtype: KClass<T>, data: IntArray): TensorData<T, V>

full

fun <T : DType> full(shape: Shape, value: Number, dtype: T): TensorData<T, *>

Creates a tensor filled with a constant value for the specified dtype.

open override fun <T : DType, V> full(shape: Shape, dtype: KClass<T>, value: Number): TensorData<T, V>

init

open override fun <T : DType, V> init(shape: Shape, dtype: KClass<T>, generator: (indices: IntArray) -> V): TensorData<T, V>

matrix

fun <T : DType, V> matrix(vararg rows: Array<V>): TensorData<T, V>

Creates a matrix tensor from multiple rows of values.

ones

open override fun <T : DType, V> ones(shape: Shape, dtype: KClass<T>): TensorData<T, V>

randn

fun <T : DType> randn(shape: Shape, mean: Float = 0.0f, std: Float = 1.0f, dtype: T, random: Random = Random.Default): TensorData<T, *>

Creates a tensor filled with random values from normal distribution.

open override fun <T : DType, V> randn(shape: Shape, dtype: KClass<T>, mean: Float, std: Float, random: Random): TensorData<T, V>

randomInit

open override fun <T : DType, V> randomInit(shape: Shape, dtype: KClass<T>, generator: (random: Random) -> V, random: Random): TensorData<T, V>

randomInt

fun <T : DType, V> randomInt(shape: Shape, dtype: T, random: Random, generator: (size: Int, random: Random) -> V): TensorData<T, *>

Creates a tensor filled with random values from uniform distribution [0, 1) for floating point types or [0, maxValue) for integer types.

scalar

fun <T : DType, V> scalar(value: V): TensorData<T, V>

Creates a scalar tensor from a single value.

uniform

open override fun <T : DType, V> uniform(shape: Shape, dtype: KClass<T>, min: Float, max: Float, random: Random): TensorData<T, V>

vector

fun <T : DType, V> vector(values: Array<V>): TensorData<T, V>

Creates a vector tensor from an array of values.

wrapByteArray

open override fun <T : DType, V> wrapByteArray(shape: Shape, dtype: KClass<T>, data: ByteArray): TensorData<T, V>

Wraps a ByteArray without copying. The caller must ensure the array is not mutated while the returned TensorData is in use. Default implementation falls back to fromByteArray (which copies).

wrapFloatArray

open override fun <T : DType, V> wrapFloatArray(shape: Shape, dtype: KClass<T>, data: FloatArray): TensorData<T, V>

Wraps a FloatArray without copying. The caller must ensure the array is not mutated while the returned TensorData is in use. Default implementation falls back to fromFloatArray (which copies).

wrapIntArray

open override fun <T : DType, V> wrapIntArray(shape: Shape, dtype: KClass<T>, data: IntArray): TensorData<T, V>

Wraps an IntArray without copying. The caller must ensure the array is not mutated while the returned TensorData is in use. Default implementation falls back to fromIntArray (which copies).

zeros

open override fun <T : DType, V> zeros(shape: Shape, dtype: KClass<T>): TensorData<T, V>