Struct DummyExecutor 

pub struct DummyExecutor {
    pub tensors: HashMap<String, DummyTensor>,
    /* private fields */
}

Minimal executor implementation for testing and prototyping.

This provides a simple, reference implementation that verifies the execution logic without requiring heavy dependencies.

Fields

tensors: HashMap<String, DummyTensor>

Implementations

impl DummyExecutor

pub fn new() -> Self

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

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

Trait Implementations

impl Default for DummyExecutor

fn default() -> Self

Returns the “default value” for a type.

impl TlAutodiff for DummyExecutor

type Tape = HashMap<usize, DummyTensor>

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

Execute forward pass on an EinsumGraph.

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

Execute backward pass to compute gradients.

impl TlBatchExecutor for DummyExecutor

type Tensor = DummyTensor

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 DummyExecutor

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 DummyExecutor

type Tensor = DummyTensor

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.

impl TlProfiledExecutor for DummyExecutor

fn profiler(&self) -> Option<&Profiler>

Get the current profiler

fn profiler_mut(&mut self) -> Option<&mut Profiler>

Get mutable access to profiler

fn enable_profiling(&mut self)

Enable profiling

fn disable_profiling(&mut self)

Disable profiling

fn get_profile_data(&self) -> Option<&ProfileData>

Get profiling data