Struct Scirs2Exec 

pub struct Scirs2Exec {
    pub tensors: HashMap<String, Scirs2Tensor>,
    /* private fields */
}

Fields

tensors: HashMap<String, Scirs2Tensor>

Implementations

impl Scirs2Exec

pub fn from_vec( data: Vec<f64>, shape: Vec<usize>, ) -> Result<Scirs2Tensor, ExecutorError>

Create a tensor from a flat vector and shape.

pub fn zeros(shape: Vec<usize>) -> Scirs2Tensor

Create a tensor filled with zeros.

pub fn ones(shape: Vec<usize>) -> Scirs2Tensor

Create a tensor filled with ones.

impl Scirs2Exec

pub fn new() -> Self

pub fn with_memory_pool() -> Self

Create executor with memory pooling enabled

pub fn enable_pooling(&mut self)

Enable memory pooling

pub fn disable_pooling(&mut self)

Disable memory pooling

pub fn pool_stats(&self) -> Option<PoolStats>

Get pool statistics if pooling is enabled

pub fn add_tensor(&mut self, name: impl Into<String>, tensor: Scirs2Tensor)

pub fn get_tensor(&self, name: &str) -> Option<&Scirs2Tensor>

Trait Implementations

impl Clone for Scirs2Exec

fn clone(&self) -> Self

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Default for Scirs2Exec

fn default() -> Self

Returns the “default value” for a type.

impl TlAutodiff for Scirs2Exec

type Tape = ForwardTape

fn forward(&mut self, graph: &EinsumGraph) -> Result<Self::Tensor, Self::Error>

Execute forward pass on an EinsumGraph.

fn backward( &mut self, graph: &EinsumGraph, loss_grad: &Self::Tensor, ) -> Result<Self::Tape, Self::Error>

Execute backward pass to compute gradients.

impl TlBatchExecutor for Scirs2Exec

type Tensor = ArrayBase<OwnedRepr<f64>, Dim<IxDynImpl>>

type Error = ExecutorError

fn execute_batch( &mut self, graph: &EinsumGraph, batch_inputs: Vec<Vec<Self::Tensor>>, ) -> Result<BatchResult<Self::Tensor>, Self::Error>

Execute a graph on a batch of inputs

fn execute_batch_parallel( &mut self, graph: &EinsumGraph, batch_inputs: Vec<Vec<Self::Tensor>>, num_threads: Option<usize>, ) -> Result<BatchResult<Self::Tensor>, Self::Error>

Execute a graph on a batch of inputs with parallel processing

fn optimal_batch_size(&self) -> usize

Get optimal batch size for this executor

fn max_batch_size(&self) -> Option<usize>

Get maximum recommended batch size for this executor

impl TlCapabilities for Scirs2Exec

fn capabilities(&self) -> &BackendCapabilities

Get backend capabilities

fn supports_elem_op(&self, op: ElemOp) -> bool

Check if a specific operation is supported

fn supports_reduce_op(&self, op: ReduceOp) -> bool

Check if a specific reduction operation is supported

fn supports_einsum(&self, spec: &str) -> bool

Check if einsum is supported with the given spec

fn available_devices(&self) -> Vec<DeviceType>

Get available devices

fn default_device(&self) -> DeviceType

Get default device

impl TlExecutor for Scirs2Exec

type Tensor = ArrayBase<OwnedRepr<f64>, Dim<IxDynImpl>>

type Error = ExecutorError

fn einsum( &mut self, spec: &str, inputs: &[Self::Tensor], ) -> Result<Self::Tensor, Self::Error>

Execute an einsum operation on input tensors.

fn elem_op( &mut self, op: ElemOp, x: &Self::Tensor, ) -> Result<Self::Tensor, Self::Error>

Apply an element-wise unary operation.

fn elem_op_binary( &mut self, op: ElemOp, x: &Self::Tensor, y: &Self::Tensor, ) -> Result<Self::Tensor, Self::Error>

Apply an element-wise binary operation.

fn reduce( &mut self, op: ReduceOp, x: &Self::Tensor, axes: &[usize], ) -> Result<Self::Tensor, Self::Error>

Reduce a tensor along specified axes.