Trait TensorOps 

pub trait TensorOps: Send + Sync {
    // Required methods
    fn matmul(&self, a: &TensorRef, b: &TensorRef) -> Result<TensorRef>;
    fn add(&self, a: &TensorRef, b: &TensorRef) -> Result<TensorRef>;
    fn sub(&self, a: &TensorRef, b: &TensorRef) -> Result<TensorRef>;
    fn mul(&self, a: &TensorRef, b: &TensorRef) -> Result<TensorRef>;
    fn div(&self, a: &TensorRef, b: &TensorRef) -> Result<TensorRef>;
    fn softmax(&self, tensor: &TensorRef, dim: i32) -> Result<TensorRef>;
    fn layer_norm(
        &self,
        input: &TensorRef,
        weight: &TensorRef,
        bias: Option<&TensorRef>,
        eps: f32,
    ) -> Result<TensorRef>;
    fn rms_norm(
        &self,
        input: &TensorRef,
        weight: &TensorRef,
        eps: f32,
    ) -> Result<TensorRef>;
    fn relu(&self, tensor: &TensorRef) -> Result<TensorRef>;
    fn gelu(&self, tensor: &TensorRef) -> Result<TensorRef>;
    fn silu(&self, tensor: &TensorRef) -> Result<TensorRef>;
    fn concat(&self, tensors: &[&TensorRef], dim: usize) -> Result<TensorRef>;
    fn split(
        &self,
        tensor: &TensorRef,
        sizes: &[usize],
        dim: usize,
    ) -> Result<Vec<TensorRef>>;
    fn transpose(
        &self,
        tensor: &TensorRef,
        dim0: usize,
        dim1: usize,
    ) -> Result<TensorRef>;
    fn permute(&self, tensor: &TensorRef, dims: &[usize]) -> Result<TensorRef>;
}

Basic tensor operations

Required Methods

fn matmul(&self, a: &TensorRef, b: &TensorRef) -> Result<TensorRef>

Matrix multiplication

fn add(&self, a: &TensorRef, b: &TensorRef) -> Result<TensorRef>

Element-wise addition

fn sub(&self, a: &TensorRef, b: &TensorRef) -> Result<TensorRef>

Element-wise subtraction

fn mul(&self, a: &TensorRef, b: &TensorRef) -> Result<TensorRef>

Element-wise multiplication

fn div(&self, a: &TensorRef, b: &TensorRef) -> Result<TensorRef>

Element-wise division

fn softmax(&self, tensor: &TensorRef, dim: i32) -> Result<TensorRef>

Apply softmax along specified dimension

fn layer_norm( &self, input: &TensorRef, weight: &TensorRef, bias: Option<&TensorRef>, eps: f32, ) -> Result<TensorRef>

Apply layer normalization

fn rms_norm( &self, input: &TensorRef, weight: &TensorRef, eps: f32, ) -> Result<TensorRef>

Apply RMS normalization

fn relu(&self, tensor: &TensorRef) -> Result<TensorRef>

Apply ReLU activation

fn gelu(&self, tensor: &TensorRef) -> Result<TensorRef>

Apply GELU activation

fn silu(&self, tensor: &TensorRef) -> Result<TensorRef>

Apply SiLU (Swish) activation

fn concat(&self, tensors: &[&TensorRef], dim: usize) -> Result<TensorRef>

Concatenate tensors along specified dimension

fn split( &self, tensor: &TensorRef, sizes: &[usize], dim: usize, ) -> Result<Vec<TensorRef>>

Split tensor along specified dimension

fn transpose( &self, tensor: &TensorRef, dim0: usize, dim1: usize, ) -> Result<TensorRef>

Transpose tensor dimensions

fn permute(&self, tensor: &TensorRef, dims: &[usize]) -> Result<TensorRef>

Permute tensor dimensions

Implementors