skainet-lang-core/sk.ainet.context/ExecutionContext

ExecutionContext

interface ExecutionContext(source)

Inheritors

DefaultDataExecutionContext

PhaseOverridingExecutionContext

TrainingExecutionContext

NeuralNetworkExecutionContext

Properties

executionStats

abstract val executionStats: ExecutionStats

hooks

open val hooks: ForwardHooks?

inTraining

open val inTraining: Boolean

memoryInfo

abstract val memoryInfo: MemoryInfo

memoryPlanner

open val memoryPlanner: MemoryPlanner

Memory planner for resolving placement intents. Default: CPU-only.

memoryTracker

open val memoryTracker: MemoryTracker?

Memory tracker for observability and copy tracing. Default: no-op (not tracking).

observers

abstract val observers: ExecutionObserverRegistry

ops

abstract val ops: TensorOps

phase

abstract val phase: Phase

tensorDataFactory

abstract val tensorDataFactory: TensorDataFactory

Functions

fromByteArray

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

fromData

open fun <T : DType, V> fromData(data: TensorData<T, V>, dtype: KClass<T>): Tensor<T, V>

fromFloatArray

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

fromIntArray

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

full

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

ones

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

registerObserver

open fun registerObserver(observer: ExecutionObserver)

unregisterObserver

open fun unregisterObserver(observer: ExecutionObserver)

wrapByteArray

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

Wraps a ByteArray without copying (borrow semantics). The caller must ensure the array is not mutated while the tensor is in use.

wrapFloatArray

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

Wraps a FloatArray without copying (borrow semantics). The caller must ensure the array is not mutated while the tensor is in use.

wrapIntArray

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

Wraps an IntArray without copying (borrow semantics). The caller must ensure the array is not mutated while the tensor is in use.

zeros

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