laddu_runtime/
lib.rs

1//! Execution backends, dataset queries, and reduction support for compiled `laddu` models.
2
3mod backend;
4mod cpu;
5mod error;
6mod execution;
7#[cfg(feature = "jit")]
8mod jit;
9mod normalization;
10mod preparation;
11mod query;
12
13pub use backend::{PreparedDataset, PreparedModel};
14pub use cpu::*;
15pub use error::{ExecutionError, RuntimeError, RuntimeResult};
16pub use execution::{
17    CpuOptions, Device, Execution, ExecutionOptions, GpuBackend, GpuDeviceSelector, GpuOptions,
18    JitPolicy, NormalizationMode, Precision, ThreadPolicy,
19};
20pub use laddu_memory::{
21    CapacitySource, DeviceIdentity, MemoryBudget, MemoryDecision, MemoryError, MemoryLease,
22    MemoryPlan, MemoryPool, MemoryPoolReport, MemoryReport, MemoryResource, MemoryResourceKind,
23    MemoryState, ProcessMemoryReport,
24};
25pub use laddu_physics::binning::{
26    BinningAxis, FinalUpperEdge, bin_shape, checked_bin_count, flat_bin_index,
27    flat_bin_index_for_event,
28};
29pub use laddu_physics::joint_histogram::{JointHistogram, JointHistogramDiagnostics};
30pub use normalization::{PreparedNormalization, PreparedNormalizationDiagnostics};
31pub use query::{BinSpec, Comparison, DatasetBin, DatasetExprExt, IntervalClosure, Predicate};
32
33use laddu_compile::CompiledModel;
34use laddu_expr::ExprNode;
35
36pub(crate) fn required_event_scalars(model: &CompiledModel) -> Vec<String> {
37    let mut required = Vec::new();
38    for node in model.graph().nodes() {
39        if let ExprNode::EventScalar(name) = node
40            && !required.iter().any(|required| required == name.as_ref())
41        {
42            required.push(name.to_string());
43        }
44    }
45    required
46}
laddu_runtime/lib.rs

laddu_runtime/
lib.rs
