skainet-lang-core/sk.ainet.lang.tensor/TensorView

TensorView

interface TensorView<T : DType, V> : Tensor<T, V> (source)

A tensor view interface that represents a zero-copy slice or subset of a parent tensor.

TensorView extends the base Tensor interface while adding view-specific functionality for efficient tensor slicing operations. Views provide memory-efficient access to portions of larger tensors without copying the underlying data.

Key Characteristics

Zero-Copy: Views reference the parent tensor's data without duplication
Shape Transformation: Views can have different shapes than their parent
Index Mapping: Coordinate transformation between view space and parent space
Memory Efficiency: Multiple views can reference the same underlying data

Usage Patterns

Views are particularly useful for:

Batch processing (extracting mini-batches from larger datasets)
Channel extraction (accessing specific feature maps in NCHW tensors)
Spatial regions (selecting rectangular areas in image tensors)
Sequence windows (sliding window operations on temporal data)

Parameters

T

the data type constraint extending DType, defining the numerical precision

V

the actual value type that will be stored and accessed

Inheritors

SlicedTensorView

Properties

abstract val indexMapping: IndexMapper

The index mapper responsible for coordinate transformation between view and parent.

abstract val parentTensor: Tensor<T, V>

The parent tensor that this view references.

open override val shape: Shape

Override the shape property to return the view-specific shape.

abstract val viewShape: Shape

The shape of this view, which may differ from the parent tensor's shape.

Functions

analyzeContiguity

fun <T : DType, V> TensorView<T, V>.analyzeContiguity(): ContiguityAnalysis

Provides a more detailed contiguity analysis with diagnostic information.

fun <T : DType, V> TensorView<T, V>.canMaterialize(): Boolean

Checks if this tensor view can be materialized using the default strategy.

fun <T : DType, V> TensorView<T, V>.canMaterialize(strategy: MaterializationStrategy<T, V>): Boolean

Checks if this tensor view can be materialized using a specific strategy.

estimateMaterializationCost

fun <T : DType, V> TensorView<T, V>.estimateMaterializationCost(): Long

Estimates the memory overhead of materializing this tensor view.

fun <T : DType, V> TensorView<T, V>.estimateMaterializationCost(strategy: MaterializationStrategy<T, V>): Long

Estimates the memory overhead of materializing this tensor view with a specific strategy.

fun <T : DType, V> TensorView<T, V>.isContiguous(): Boolean

Determines if this tensor view represents a contiguous memory layout.

fun <T : DType, V> TensorView<T, V>.materialize(): Tensor<T, V>

Materializes this tensor view into a standalone tensor using the default strategy.

fun <T : DType, V> TensorView<T, V>.materialize(strategy: MaterializationStrategy<T, V>): Tensor<T, V>

Materializes this tensor view using a specific materialization strategy.

fun <T : DType, V> TensorView<T, V>.sliceView(builder: TensorSliceBuilder<T, V>.() -> Unit): TensorView<T, V>

Creates a view of an existing tensor view, enabling view chaining.