Struct CpuBackend 

pub struct CpuBackend { /* private fields */ }

CPU compute backend using Candle for tensor operations.

Implementations

impl CpuBackend

pub fn new() -> Self

Creates a new CPU backend.

pub fn candle_device(&self) -> &Device

Returns the Candle device.

Trait Implementations

impl ComputeBackend for CpuBackend

type Tensor = CpuTensor

The tensor type for this backend.

type Device = CpuDevice

The device type for this backend.

fn device(&self) -> &Self::Device

Returns the device.

fn allocate(&self, shape: &[usize], dtype: DType) -> Result<Self::Tensor>

Allocates a new tensor filled with zeros.

fn from_slice(&self, data: &[f32], shape: &[usize]) -> Result<Self::Tensor>

Creates a tensor from raw data.

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

Performs matrix multiplication: C = A @ B.

fn batch_matmul( &self, a: &Self::Tensor, b: &Self::Tensor, ) -> Result<Self::Tensor>

Performs batched matrix multiplication.

fn attention( &self, q: &Self::Tensor, k: &Self::Tensor, v: &Self::Tensor, mask: Option<&Self::Tensor>, scale: Option<f32>, ) -> Result<Self::Tensor>

Performs scaled dot-product attention. Returns softmax(Q @ K^T / sqrt(d_k)) @ V with optional causal masking.

fn rms_norm( &self, x: &Self::Tensor, weight: &Self::Tensor, eps: f32, ) -> Result<Self::Tensor>

Applies RMS normalization: x * weight / sqrt(mean(x^2) + eps).

fn layer_norm( &self, x: &Self::Tensor, weight: &Self::Tensor, bias: Option<&Self::Tensor>, eps: f32, ) -> Result<Self::Tensor>

Applies Layer normalization.

fn silu(&self, x: &Self::Tensor) -> Result<Self::Tensor>

Applies SiLU (Swish) activation: x * sigmoid(x).

fn gelu(&self, x: &Self::Tensor) -> Result<Self::Tensor>

Applies GELU activation.

fn relu(&self, x: &Self::Tensor) -> Result<Self::Tensor>

Applies ReLU activation.

fn softmax(&self, x: &Self::Tensor, dim: i32) -> Result<Self::Tensor>

Applies softmax along the specified dimension.

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

Element-wise addition.

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

Element-wise multiplication.

fn transpose(&self, x: &Self::Tensor) -> Result<Self::Tensor>

Transposes the last two dimensions.

fn reshape(&self, x: &Self::Tensor, shape: &[usize]) -> Result<Self::Tensor>

Reshapes a tensor.

fn to_device(&self, tensor: &Self::Tensor) -> Result<Self::Tensor>

Copies tensor to device.

fn to_cpu(&self, tensor: &Self::Tensor) -> Result<Vec<f32>>

Copies tensor data to CPU as f32 vector.

impl Debug for CpuBackend

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

Formats the value using the given formatter.

impl Default for CpuBackend

fn default() -> Self

Returns the “default value” for a type.