Struct TensorView 

pub struct TensorView<'a, T: 'a, const N: usize, Layout = RowMajor, Ref = &'a [T]> { /* private fields */ }

Zero-copy N-dimensional strided view over a borrowed slice.

Type Parameters

• 'a — lifetime of the underlying data slice.
• T — element type.
• N — tensor rank (number of dimensions). Const generic; resolved at compile time.
• Layout — layout marker ZST (RowMajor or ColMajor). PhantomData; zero size.
• Ref — reference type-state (&'a [T] or &'a mut [T]).

Invariants

• strides[i] * shape[i] must not overflow usize.
• data.len() >= ∑ (shape[i]-1) * strides[i] + 1 for any valid element access.
• new and with_strides both verify product(shape) <= data.len().

Implementations

impl<'a, 'b, T, L> TensorView<'a, T, 2, L, &'b [T]>

pub fn row_view( &self, i: usize, ) -> Result<TensorView<'a, T, 1, RowMajor, &'b [T]>, TensorError>

Return a zero-copy 1-D view of row i.

Errors

Returns TensorError::IndexOutOfBounds if i >= shape[0].

pub fn iter_rows(&self) -> Result<impl Iterator<Item = &'b [T]>, TensorError>

Iterate over row slices of a contiguous 2-D tensor.

Errors

Returns TensorError::NotContiguous if the view is not row-major contiguous.

pub fn transpose_view(&self) -> TensorView<'a, T, 2, ColMajor, &'b [T]>

Return a zero-copy transposed view (swaps shape and strides).

The result is ColMajor-tagged. No allocation.

pub fn col_iter( &self, j: usize, ) -> Result<impl Iterator<Item = T> + '_, TensorError>

where T: Copy,

Iterate over elements of column j, one element per row.

Zero-copy: index arithmetic over the underlying slice.

Errors

Returns TensorError::IndexOutOfBounds if j >= shape[1].

pub fn diag_iter(&self) -> impl Iterator<Item = T> + '_

where T: Copy,

Iterate over main diagonal elements (min(rows, cols) elements).

Zero-copy: index arithmetic, no allocation.

impl<'a, T, L> TensorView<'a, T, 2, L, &mut [T]>

pub fn row_view_mut( &mut self, i: usize, ) -> Result<TensorView<'a, T, 1, RowMajor, &mut [T]>, TensorError>

Return a mutable 1-D view of row i.

Errors

Returns TensorError::IndexOutOfBounds if i >= shape[0].

pub fn iter_rows_mut( &mut self, ) -> Result<impl Iterator<Item = &mut [T]>, TensorError>

Iterate over mutable row slices of a contiguous 2-D tensor.

Errors

Returns TensorError::NotContiguous if not row-major contiguous.

impl<'a, T, L> TensorView<'a, T, 3, L, &'a [T]>

pub fn matrix_at( &self, b: usize, ) -> Result<TensorView<'_, T, 2, RowMajor, &[T]>, TensorError>

Return a 2-D view of the b-th matrix in a batched tensor.

impl<'a, T, L> TensorView<'a, T, 3, L, &'a mut [T]>

pub fn matrix_at_mut( &mut self, b: usize, ) -> Result<TensorView<'_, T, 2, RowMajor, &mut [T]>, TensorError>

Return a mutable 2-D view of the b-th matrix in a batched tensor.

impl<'a, T, Ref> TensorView<'a, T, 2, RowMajor, Ref>

pub fn transpose(self) -> TensorView<'a, T, 2, ColMajor, Ref>

Transpose a row-major 2-D tensor view to column-major.

impl<'a, T, Ref> TensorView<'a, T, 2, ColMajor, Ref>

pub fn transpose(self) -> TensorView<'a, T, 2, RowMajor, Ref>

Transpose a column-major 2-D tensor view to row-major.

impl<'a, T> TensorView<'a, T, 1, RowMajor, &'a [T]>

where T: Scalar,

pub fn into_simd_view<Arch, Align>( &self, ) -> Option<SimdView<'a, T, Arch, Align, Unmasked, &'a [T]>>

where Arch: SimdArch + SimdKernel<T>, Align: Alignment,

Promote this contiguous rank-1 view into a typed SimdView.

Zero-copy: shares the same underlying slice. Returns None if the slice is empty or if the alignment check fails for Align.

Example

use hermes_simd_core::tensor::TensorView;
use hermes_simd_intrinsics::Scalar;
use hermes_simd_core::align::Unaligned;

let data = [1.0f32, 2.0, 3.0, 4.0];
let t = TensorView::<f32, 1>::new(&data, [4]).unwrap();
let view = t.into_simd_view::<Scalar, Unaligned>().unwrap();

impl<'a, 'b, T, const N: usize> TensorView<'a, T, N, RowMajor, &'b [T]>

pub fn new(data: &'b [T], shape: [usize; N]) -> Result<Self, TensorError>

Create a row-major tensor view over data with the given shape.

Strides are computed as strides[i] = ∏_{j=i+1..N} shape[j] (C-order).

Errors

Returns TensorError::ShapeMismatch if ∏ shape > data.len().

Examples

use hermes_simd_core::TensorView;

let data = [0, 1, 2, 3, 4, 5];
let view = TensorView::<i32, 2>::new(&data, [2, 3]).unwrap();

assert_eq!(view.shape(), [2, 3]);
assert_eq!(view.strides(), [3, 1]);
assert_eq!(view.get([1, 2]).unwrap(), 5);

impl<'a, 'b, T, const N: usize> TensorView<'a, T, N, RowMajor, &'b mut [T]>

pub fn new_mut( data: &'b mut [T], shape: [usize; N], ) -> Result<Self, TensorError>

Create a mutable row-major tensor view over data with the given shape.

Errors

Returns TensorError::ShapeMismatch if ∏ shape > data.len().

impl<'a, 'b, T, const N: usize, L: Layout> TensorView<'a, T, N, L, &'b [T]>

pub fn with_strides( data: &'b [T], shape: [usize; N], strides: [usize; N], ) -> Result<Self, TensorError>

Create a tensor view with explicit strides.

Allows column-major, blocked, or any custom layout.

Errors

Returns TensorError::ShapeMismatch if ∏ shape > data.len().

impl<'a, 'b, T, const N: usize, L: Layout> TensorView<'a, T, N, L, &'b mut [T]>

pub fn with_strides_mut( data: &'b mut [T], shape: [usize; N], strides: [usize; N], ) -> Result<Self, TensorError>

Create a mutable tensor view with explicit strides.

Errors

Returns TensorError::ShapeMismatch if ∏ shape > data.len().

pub fn downgrade(self) -> TensorView<'a, T, N, L, &'b [T]>

Downgrade the exclusive mutable view to a shared read-only view.

impl<'a, 'b, T> TensorView<'a, T, 2, ColMajor, &'b [T]>

pub fn new_col_major( data: &'b [T], shape: [usize; 2], ) -> Result<Self, TensorError>

Create a column-major (Fortran-order) 2-D tensor view.

Fortran strides: strides[0] = 1, strides[1] = shape[0].

Errors

Returns TensorError::ShapeMismatch if shape[0] * shape[1] > data.len().

impl<'a, T, const N: usize, L, Ref> TensorView<'a, T, N, L, Ref>

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

The logical shape of this tensor: number of elements per dimension.

pub fn strides(&self) -> [usize; N]

The strides of this tensor in element units.

pub fn num_elements(&self) -> usize

Number of elements in this tensor: ∏ shape[i].

pub fn is_empty(&self) -> bool

Returns true if the tensor is empty (one of its dimensions is 0).

pub fn is_contiguous(&self) -> bool

Whether this view is contiguous in row-major order.

pub fn as_slice(&self) -> &[T]

View the underlying flat slice (in storage order).

pub fn get(&self, idx: [usize; N]) -> Result<T, TensorError>

where T: Copy,

Bounds-checked element access.

pub unsafe fn get_unchecked(&self, idx: [usize; N]) -> T

where T: Copy,

Unchecked element access.

Safety

idx[i] < shape[i] for all i.

pub fn reshape<const M: usize>( self, new_shape: [usize; M], ) -> Result<TensorView<'a, T, M, RowMajor, Ref>, TensorError>

Reshape this view to a different rank M, reusing the same flat slice.

impl<'a, 'b, T, const N: usize, L> TensorView<'a, T, N, L, &'b mut [T]>

pub fn as_slice_mut(&mut self) -> &mut [T]

Access the underlying flat mutable slice.

pub fn set(&mut self, idx: [usize; N], val: T) -> Result<(), TensorError>

Bounds-checked element write access.

pub unsafe fn set_unchecked(&mut self, idx: [usize; N], val: T)

Unchecked element write access.

Safety

idx[i] < shape[i] for all i.

Trait Implementations

impl<'a, T, const N: usize, Layout> Clone for TensorView<'a, T, N, Layout, &'a [T]>

fn clone(&self) -> Self

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl<'a, T, const N: usize, Layout> Copy for TensorView<'a, T, N, Layout, &'a [T]>

impl<'a, T, const N: usize, Layout, Ref> Send for TensorView<'a, T, N, Layout, Ref>

where Ref: Send,

impl<'a, T, const N: usize, Layout, Ref> Sync for TensorView<'a, T, N, Layout, Ref>

where Ref: Sync,