Struct TensorLayout 

pub struct TensorLayout<R = DynRank>
where
    R: TensorRank,
{ /* private fields */ }

Storage-neutral tensor layout metadata.

Examples

use tenferro_tensor_core::{Rank, TensorLayout};

let layout = TensorLayout::<Rank<2>>::compact([2, 3])?;
assert_eq!(layout.shape(), &[2, 3]);
assert_eq!(layout.strides(), &[1, 2]);

Implementations

impl<R> TensorLayout<R>

where R: TensorRank,

pub fn compact( shape: <R as TensorRank>::Shape, ) -> Result<TensorLayout<R>, ValidationError>

Create a compact column-major layout with zero offset.

Examples

use tenferro_tensor_core::{Rank, TensorLayout};

let layout = TensorLayout::<Rank<2>>::compact([2, 3])?;
assert_eq!(layout.strides(), &[1, 2]);

Errors

Returns ValidationError::IntegerOverflow when compact strides cannot be computed for shape.

pub fn from_parts( shape: <R as TensorRank>::Shape, strides: <R as TensorRank>::Strides, offset: isize, buffer_len: usize, ) -> Result<TensorLayout<R>, ValidationError>

Create a layout from shape, strides, element offset, and backing buffer length.

Examples

use tenferro_tensor_core::{DynRank, TensorLayout};

let layout = TensorLayout::<DynRank>::from_parts(
    vec![2, 3].into(),
    vec![1, 2].into(),
    0,
    6,
)?;
assert!(layout.is_compact_col_major()?);

Errors

Returns ValidationError::RankMismatch for incompatible shape and stride ranks, ValidationError::ViewOutOfBounds when the reachable range exceeds buffer_len, or ValidationError::IntegerOverflow when metadata arithmetic overflows.

pub fn shape(&self) -> &[usize]

Return the layout shape.

Examples

use tenferro_tensor_core::{Rank, TensorLayout};

let layout = TensorLayout::<Rank<1>>::compact([4])?;
assert_eq!(layout.shape(), &[4]);

pub fn strides(&self) -> &[isize]

Return the layout strides in element units.

Examples

use tenferro_tensor_core::{Rank, TensorLayout};

let layout = TensorLayout::<Rank<2>>::compact([2, 3])?;
assert_eq!(layout.strides(), &[1, 2]);

pub fn offset(&self) -> isize

Return the layout element offset.

Examples

use tenferro_tensor_core::{DynRank, TensorLayout};

let layout = TensorLayout::<DynRank>::from_parts(vec![3].into(), vec![1].into(), 2, 5)?;
assert_eq!(layout.offset(), 2);

pub fn is_compact_col_major(&self) -> Result<bool, ValidationError>

Return whether the layout has compact column-major strides.

Examples

use tenferro_tensor_core::{Rank, TensorLayout};

let layout = TensorLayout::<Rank<2>>::compact([2, 3])?;
assert!(layout.is_compact_col_major()?);

Errors

Returns ValidationError::IntegerOverflow when compactness validation overflows metadata arithmetic.

pub fn validate_mutable_no_overlap(&self) -> Result<(), ValidationError>

Validate that the layout can be used for mutable access without aliasing.

Empty logical views are accepted. Non-empty layouts are accepted when a conservative stride-span proof succeeds, or when exact enumeration of a small bounded view proves that all logical elements map to distinct physical offsets.

Examples

use tenferro_tensor_core::{DynRank, TensorLayout};

let layout = TensorLayout::<DynRank>::from_parts(vec![3].into(), vec![-1].into(), 2, 3)?;
layout.validate_mutable_no_overlap()?;

Errors

Returns ValidationError::OverlappingMutableLayout when multiple logical elements can alias, or ValidationError::IntegerOverflow when overlap validation arithmetic overflows.

pub fn transpose_view( &self, axes: impl AsRef<[usize]>, ) -> Result<TensorLayout<R>, ValidationError>

Return a metadata-only axis permutation of this layout.

Examples

use tenferro_tensor_core::{Rank, TensorLayout};

let layout = TensorLayout::<Rank<2>>::compact([2, 3])?;
let transposed = layout.transpose_view([1, 0])?;
assert_eq!(transposed.shape(), &[3, 2]);
assert_eq!(transposed.strides(), &[2, 1]);

Errors

Returns ValidationError::InvalidPermutationLength, ValidationError::AxisOutOfBounds, or ValidationError::DuplicateAxis when axes is not a permutation of the layout rank.

pub fn slice_view( &self, spec: impl AsRef<[SliceSpec]>, buffer_len: usize, ) -> Result<TensorLayout<R>, ValidationError>

Return a metadata-only slice of this layout.

Examples

use tenferro_tensor_core::{Rank, SliceSpec, TensorLayout};

let layout = TensorLayout::<Rank<1>>::compact([4])?;
let view = layout.slice_view([SliceSpec { start: 3, end: -1, step: -2 }], 4)?;
assert_eq!(view.shape(), &[2]);
assert_eq!(view.strides(), &[-2]);

Errors

Returns ValidationError::RankMismatch when spec does not cover every axis, ValidationError::InvalidSliceStep or ValidationError::InvalidSliceBounds for invalid slice parameters, or ValidationError::ViewOutOfBounds when the result is outside the backing buffer.

pub fn reshape_view_as<R2>( &self, shape: impl Into<<R2 as TensorRank>::Shape>, buffer_len: usize, ) -> Result<TensorLayout<R2>, ValidationError>

where R2: TensorRank,

Return a metadata-only reshape of this compact column-major layout.

Examples

use tenferro_tensor_core::{Rank, TensorLayout};

let layout = TensorLayout::<Rank<2>>::compact([2, 3])?;
let reshaped = layout.reshape_view_as::<Rank<1>>([6], 6)?;
assert_eq!(reshaped.shape(), &[6]);
assert_eq!(reshaped.strides(), &[1]);

Errors

Returns ValidationError::NonContiguousViewAsSlice for a noncompact source, ValidationError::ShapeMismatch for a different element count, or ValidationError::IntegerOverflow when shape arithmetic overflows.

pub fn broadcast_in_dim_view<R2>( &self, shape: impl Into<<R2 as TensorRank>::Shape>, broadcast_dims: impl AsRef<[usize]>, buffer_len: usize, ) -> Result<TensorLayout<R2>, ValidationError>

where R2: TensorRank,

Return a metadata-only explicit broadcast of this layout into a target rank.

Examples

use tenferro_tensor_core::{Rank, TensorLayout};

let layout = TensorLayout::<Rank<1>>::compact([3])?;
let broadcast = layout.broadcast_in_dim_view::<Rank<2>>([2, 3], [1], 3)?;
assert_eq!(broadcast.shape(), &[2, 3]);
assert_eq!(broadcast.strides(), &[0, 1]);

Errors

Returns ValidationError::RankMismatch, ValidationError::AxisOutOfBounds, or ValidationError::DuplicateAxis for invalid broadcast axes; ValidationError::ShapeDataLengthMismatch for incompatible extents; or ValidationError::ViewOutOfBounds for an invalid result layout.

Trait Implementations

impl<R> Clone for TensorLayout<R>

where R: Clone + TensorRank, <R as TensorRank>::Shape: Clone, <R as TensorRank>::Strides: Clone,

fn clone(&self) -> TensorLayout<R>

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl<R> Debug for TensorLayout<R>

where R: Debug + TensorRank, <R as TensorRank>::Shape: Debug, <R as TensorRank>::Strides: Debug,

fn fmt(&self, f: &mut Formatter<'_>) -> Result<(), Error>

Formats the value using the given formatter.

impl<R> PartialEq for TensorLayout<R>

where R: PartialEq + TensorRank, <R as TensorRank>::Shape: PartialEq, <R as TensorRank>::Strides: PartialEq,

fn eq(&self, other: &TensorLayout<R>) -> bool

Tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl<R> Eq for TensorLayout<R>

where R: Eq + TensorRank, <R as TensorRank>::Shape: Eq, <R as TensorRank>::Strides: Eq,

impl<R> StructuralPartialEq for TensorLayout<R>

where R: TensorRank,