bench API 参考

仓库 benchmark 共用的 Maremark 规格、成对分析与 auto-tune 归约。

状态

这些内容属于仓库性能基础设施。只有 bench 暴露可复用辅助函数；数据类型子包不提供应用 API。

完整公共接口

以下快照是版本 0.7.1 的完整生成接口。

// Generated using `moon info`, DON'T EDIT IT
package "Luna-Flow/floating/bench"

import {
  "Luna-Flow/mare_mark/event",
  "Luna-Flow/mare_mark/model",
  "Luna-Flow/mare_mark/runner",
  "Luna-Flow/mare_mark/stats",
}

// Values
pub fn confirmatory_regression(Array[Double], Array[Double], UInt64) -> Result[@stats.Comparison, @stats.BootstrapError]

pub fn environment(@model.ExecutionTarget, String, String) -> @model.EnvironmentSnapshot

pub fn[Scale, Input, Expected, Output] immutable_bench(String, String, Array[Scale], (Scale) -> String, (@model.GenerationContext[Scale]) -> Input, (Input) -> String, Array[@runner.Implementation[Input, Output, Unit]], (Input) -> Expected, (Expected, Output) -> Bool, (Input) -> String, (Output) -> String) -> @runner.BenchSpec[Scale, Input, Input, Expected, Output, Unit, Output?, Output?]

pub fn is_significant_regression(@stats.Comparison) -> Bool

pub fn paired_hotspot(Array[@model.Observation], String, Int, String, String, Double, UInt64) -> Result[@stats.Comparison, @stats.BootstrapError]

pub async fn[Scale, Input, Prepared, Expected, Output, Context, State, SinkValue] run(@runner.BenchSpec[Scale, Input, Prepared, Expected, Output, Context, State, SinkValue], @model.EnvironmentSnapshot, @event.ObservationSink, UInt64, @runner.ValidatedProtocol) -> @model.RunSummary

pub fn tune_dataset(Array[@model.Observation], String, Int, Array[String], Double) -> TuneDecision?

// Errors

// Types and methods
pub struct TuneDecision {
  dataset_id : Int
  candidate_id : String
  median_us : Double
  valid_samples : Int
}

// Type aliases

// Traits