Enum PreparedModel 

pub enum PreparedModel {
    Cpu(Box<CpuPlan>),
}

A compiled model prepared for a concrete execution backend.

Variants

Cpu(Box<CpuPlan>)

A model prepared for CPU execution.

Implementations

impl PreparedModel

pub fn evaluate_batch( &self, params: &ParamValues, batch: &EventBatch, ) -> RuntimeResult<Vec<Complex64>>

Evaluates the model for every event in a batch.

Errors

Returns RuntimeError when parameters or event columns are incompatible, evaluation fails, or a matrix solve is singular.

pub fn evaluate_batch_with_gradient( &self, params: &ParamValues, batch: &EventBatch, ) -> RuntimeResult<Vec<ValueGradient>>

Evaluates the model and its free-parameter gradient for every event in a batch.

Errors

Returns RuntimeError when inputs are incompatible, differentiation or evaluation fails, or the selected backend lacks event-wise gradients.

pub fn prepare( model: &CompiledModel, execution: &Execution, ) -> RuntimeResult<Self>

Prepares a compiled model for the supplied execution context.

Errors

Returns RuntimeError when model lowering, differentiation, backend initialization, or precision selection fails.

pub fn prepare_dataset( &self, execution: &Execution, dataset: &Dataset, ) -> RuntimeResult<PreparedDataset>

Prepares a dataset for repeated evaluation with this model.

Errors

Returns RuntimeError when the dataset cannot be read or cached, its schema is incompatible, or backend preparation fails.

pub fn reduce( &self, execution: &Execution, params: &ParamValues, dataset: &PreparedDataset, reduction: ReductionPlan, ) -> RuntimeResult<f64>

Executes a weighted scalar reduction over a prepared dataset.

Errors

Returns RuntimeError when model and dataset backends differ, inputs are incompatible, evaluation fails, or the reduction domain is invalid.

pub fn reduce_with_gradient( &self, execution: &Execution, params: &ParamValues, dataset: &PreparedDataset, reduction: ReductionPlan, ) -> RuntimeResult<ReductionEvaluation>

Executes a weighted reduction and computes its free-parameter gradient.

Errors

Returns RuntimeError when model and dataset backends differ, differentiation or evaluation fails, or the reduction domain is invalid.

Trait Implementations

impl Clone for PreparedModel

fn clone(&self) -> PreparedModel

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for PreparedModel

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

Formats the value using the given formatter.