Struct InferenceEngine 

pub struct InferenceEngine { /* private fields */ }

The main inference engine for AGSP

Implementations

impl InferenceEngine

pub fn new(config: EngineConfig) -> Self

Create a new inference engine without a model

pub fn with_model( config: EngineConfig, model: Box<dyn AutoregressiveModel>, ) -> Self

Create a new inference engine with a model

pub fn set_model(&mut self, model: Box<dyn AutoregressiveModel>)

Set the model for this engine

This will update the context configuration to match the model’s architecture

pub fn has_model(&self) -> bool

Check if a model is loaded

pub fn step(&mut self, input: &Array1<f32>) -> InferenceResult<Array1<f32>>

Perform a single inference step

This is the core autoregressive prediction: Given input x_t, predict x_{t+1}

pub fn rollout( &mut self, input: &Array1<f32>, steps: usize, ) -> InferenceResult<Vec<Array1<f32>>>

Perform multi-step rollout

Predicts steps future values autoregressively

pub fn reset(&mut self)

Reset the engine state

pub fn step_count(&self) -> usize

Get the current step count

pub fn config(&self) -> &EngineConfig

Get the configuration

pub fn context(&self) -> &InferenceContext

Get the context

pub fn sampler_mut(&mut self) -> &mut Sampler

Get mutable access to the sampler

pub fn sampler(&self) -> &Sampler

Get the sampler

pub fn step_batch( &mut self, inputs: &[Array1<f32>], ) -> InferenceResult<Vec<Array1<f32>>>

Perform batched inference on multiple inputs

This processes multiple inputs in parallel for efficiency. Each input is processed independently with its own hidden state.

pub fn model_info(&self) -> Option<ModelInfo>

Get model information