Struct F 

pub struct F<B: Backend, const D: usize>(pub FloatTensor<B>);

A backend float-tensor primitive tagged with a compile-time rank D.

Mirrors the slice of Tensor’s method API needed by the custom backward gradient math, operating directly on B’s primitives.

Tuple Fields

0: FloatTensor<B>

Implementations

impl<B: Backend, const D: usize> F<B, D>

pub fn new(p: FloatTensor<B>) -> Self

Wrap a raw primitive.

pub fn inner(self) -> FloatTensor<B>

Unwrap to the raw primitive.

pub fn dims(&self) -> [usize; D]

Runtime shape as a [usize; D] array.

pub fn device(&self) -> Device<B>

Device the tensor lives on.

pub fn dtype(&self) -> FloatDType

Float dtype of the tensor.

pub fn matmul(self, rhs: Self) -> Self

Batched matrix multiplication over the last two dims.

pub fn permute(self, axes: [usize; D]) -> Self

Permute the axes (rank-preserving).

pub fn swap_dims(self, dim1: usize, dim2: usize) -> Self

Swap two axes.

pub fn exp(self) -> Self

Element-wise exp.

pub fn sum_dim(self, dim: usize) -> Self

Sum along dim, keeping it as a size-1 axis (rank-preserving).

pub fn cumsum(self, dim: usize) -> Self

Cumulative sum along dim.

pub fn flip(self, axes: &[usize]) -> Self

Reverse the order of elements along the given axes (rank-preserving).

pub fn slice<S: SliceArg>(self, slices: S) -> Self

Slice the tensor (rank-preserving), accepting the same s![..] args as the high-level API.

pub fn narrow(self, dim: usize, start: usize, length: usize) -> Self

Narrow dim to [start, start + length) (rank-preserving).

pub fn reshape<const D2: usize>(self, shape: [usize; D2]) -> F<B, D2>

Reshape to a new rank D2.

pub fn expand(self, shape: [usize; D]) -> Self

Broadcast-expand to shape (rank-preserving).

pub fn squeeze_dim<const D2: usize>(self, dim: usize) -> F<B, D2>

Remove the size-1 axis at dim, yielding rank D2 = D - 1.

pub fn unsqueeze_dim<const D2: usize>(self, dim: usize) -> F<B, D2>

Insert a size-1 axis at dim, yielding rank D2 = D + 1.

pub fn unsqueeze_dims<const D2: usize>(self, axes: &[isize]) -> F<B, D2>

Insert size-1 axes at the given output positions, yielding rank D2.

Mirrors Tensor::unsqueeze_dims: negative indices count from the back and duplicates insert multiple axes.

pub fn triu(self, diagonal: i64) -> Self

Zero everything strictly below the diagonal (keeps the upper triangle).

Equivalent to Tensor::triu: builds the triangular bool mask over the last two dims and fills the masked region with 0.

pub fn mask_fill(self, mask: Mask<B>, value: f32) -> Self

Fill the positions where mask is true with value.

pub fn cat(tensors: Vec<F<B, D>>, dim: usize) -> Self

Concatenate same-rank tensors along dim (rank-preserving).

pub fn stack<const D2: usize>(tensors: Vec<F<B, D>>, dim: usize) -> F<B, D2>

Stack same-rank tensors along a fresh axis dim, yielding rank D2 = D + 1.

pub fn zeros(shape: [usize; D], device: &Device<B>, dtype: FloatDType) -> Self

All-zeros tensor of the given shape, dtype and device.

pub fn full( shape: [usize; D], value: f32, device: &Device<B>, dtype: FloatDType, ) -> Self

Constant-filled tensor of the given shape, dtype and device.

Trait Implementations

impl<B: Backend, const D: usize> Add for F<B, D>

type Output = F<B, D>

The resulting type after applying the + operator.

fn add(self, rhs: Self) -> Self

Performs the + operation.

impl<B: Backend, const D: usize> Clone for F<B, D>

fn clone(&self) -> Self

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl<B: Backend, const D: usize> Mul for F<B, D>

type Output = F<B, D>

The resulting type after applying the * operator.

fn mul(self, rhs: Self) -> Self

Performs the * operation.

impl<B: Backend, const D: usize> Neg for F<B, D>

type Output = F<B, D>

The resulting type after applying the - operator.

fn neg(self) -> Self

Performs the unary - operation.

impl<B: Backend, const D: usize> Sub for F<B, D>

type Output = F<B, D>

The resulting type after applying the - operator.

fn sub(self, rhs: Self) -> Self

Performs the - operation.