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android / toolchain / rustc / refs/heads/main / . / vendor / criterion-0.3.5 / src / lib.rs
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//! A statistics-driven micro-benchmarking library written in Rust.
//!
//! This crate is a microbenchmarking library which aims to provide strong
//! statistical confidence in detecting and estimating the size of performance
//! improvements and regressions, while also being easy to use.
//!
//! See
//! [the user guide](https://bheisler.github.io/criterion.rs/book/index.html)
//! for examples as well as details on the measurement and analysis process,
//! and the output.
//!
//! ## Features:
//! * Collects detailed statistics, providing strong confidence that changes
//! to performance are real, not measurement noise.
//! * Produces detailed charts, providing thorough understanding of your code's
//! performance behavior.
#![warn(missing_docs)]
#![warn(bare_trait_objects)]
#![cfg_attr(feature = "real_blackbox", feature(test))]
#![cfg_attr(
feature = "cargo-clippy",
allow(
clippy::just_underscores_and_digits, // Used in the stats code
clippy::transmute_ptr_to_ptr, // Used in the stats code
clippy::manual_non_exhaustive, // Remove when MSRV bumped above 1.40
)
)]
#[cfg(test)]
extern crate approx;
#[cfg(test)]
extern crate quickcheck;
use clap::value_t;
use regex::Regex;
#[macro_use]
extern crate lazy_static;
#[cfg(feature = "real_blackbox")]
extern crate test;
#[macro_use]
extern crate serde_derive;
// Needs to be declared before other modules
// in order to be usable there.
#[macro_use]
mod macros_private;
#[macro_use]
mod analysis;
mod benchmark;
#[macro_use]
mod benchmark_group;
pub mod async_executor;
mod bencher;
mod connection;
mod csv_report;
mod error;
mod estimate;
mod format;
mod fs;
mod html;
mod kde;
mod macros;
pub mod measurement;
mod plot;
pub mod profiler;
mod report;
mod routine;
mod stats;
use std::cell::RefCell;
use std::collections::HashSet;
use std::default::Default;
use std::env;
use std::fmt;
use std::iter::IntoIterator;
use std::marker::PhantomData;
use std::net::TcpStream;
use std::path::{Path, PathBuf};
use std::process::Command;
use std::sync::{Mutex, MutexGuard};
use std::time::Duration;
use criterion_plot::{Version, VersionError};
use crate::benchmark::BenchmarkConfig;
use crate::benchmark::NamedRoutine;
use crate::connection::Connection;
use crate::connection::OutgoingMessage;
use crate::csv_report::FileCsvReport;
use crate::html::Html;
use crate::measurement::{Measurement, WallTime};
use crate::plot::{Gnuplot, Plotter, PlottersBackend};
use crate::profiler::{ExternalProfiler, Profiler};
use crate::report::{BencherReport, CliReport, Report, ReportContext, Reports};
use crate::routine::Function;
#[cfg(feature = "async")]
pub use crate::bencher::AsyncBencher;
pub use crate::bencher::Bencher;
#[allow(deprecated)]
pub use crate::benchmark::{Benchmark, BenchmarkDefinition, ParameterizedBenchmark};
pub use crate::benchmark_group::{BenchmarkGroup, BenchmarkId};
lazy_static! {
static ref DEBUG_ENABLED: bool = std::env::var_os("CRITERION_DEBUG").is_some();
static ref GNUPLOT_VERSION: Result<Version, VersionError> = criterion_plot::version();
static ref DEFAULT_PLOTTING_BACKEND: PlottingBackend = {
match &*GNUPLOT_VERSION {
Ok(_) => PlottingBackend::Gnuplot,
Err(e) => {
match e {
VersionError::Exec(_) => println!("Gnuplot not found, using plotters backend"),
e => println!(
"Gnuplot not found or not usable, using plotters backend\n{}",
e
),
};
PlottingBackend::Plotters
}
}
};
static ref CARGO_CRITERION_CONNECTION: Option<Mutex<Connection>> = {
match std::env::var("CARGO_CRITERION_PORT") {
Ok(port_str) => {
let port: u16 = port_str.parse().ok()?;
let stream = TcpStream::connect(("localhost", port)).ok()?;
Some(Mutex::new(Connection::new(stream).ok()?))
}
Err(_) => None,
}
};
static ref DEFAULT_OUTPUT_DIRECTORY: PathBuf = {
// Set criterion home to (in descending order of preference):
// - $CRITERION_HOME (cargo-criterion sets this, but other users could as well)
// - $CARGO_TARGET_DIR/criterion
// - the cargo target dir from `cargo metadata`
// - ./target/criterion
if let Some(value) = env::var_os("CRITERION_HOME") {
PathBuf::from(value)
} else if let Some(path) = cargo_target_directory() {
path.join("criterion")
} else {
PathBuf::from("target/criterion")
}
};
}
fn debug_enabled() -> bool {
*DEBUG_ENABLED
}
/// A function that is opaque to the optimizer, used to prevent the compiler from
/// optimizing away computations in a benchmark.
///
/// This variant is backed by the (unstable) test::black_box function.
#[cfg(feature = "real_blackbox")]
pub fn black_box<T>(dummy: T) -> T {
test::black_box(dummy)
}
/// A function that is opaque to the optimizer, used to prevent the compiler from
/// optimizing away computations in a benchmark.
///
/// This variant is stable-compatible, but it may cause some performance overhead
/// or fail to prevent code from being eliminated.
#[cfg(not(feature = "real_blackbox"))]
pub fn black_box<T>(dummy: T) -> T {
unsafe {
let ret = std::ptr::read_volatile(&dummy);
std::mem::forget(dummy);
ret
}
}
/// Representing a function to benchmark together with a name of that function.
/// Used together with `bench_functions` to represent one out of multiple functions
/// under benchmark.
#[doc(hidden)]
pub struct Fun<I: fmt::Debug, M: Measurement + 'static = WallTime> {
f: NamedRoutine<I, M>,
_phantom: PhantomData<M>,
}
impl<I, M: Measurement> Fun<I, M>
where
I: fmt::Debug + 'static,
{
/// Create a new `Fun` given a name and a closure
pub fn new<F>(name: &str, f: F) -> Fun<I, M>
where
F: FnMut(&mut Bencher<'_, M>, &I) + 'static,
{
let routine = NamedRoutine {
id: name.to_owned(),
f: Box::new(RefCell::new(Function::new(f))),
};
Fun {
f: routine,
_phantom: PhantomData,
}
}
}
/// Argument to [`Bencher::iter_batched`](struct.Bencher.html#method.iter_batched) and
/// [`Bencher::iter_batched_ref`](struct.Bencher.html#method.iter_batched_ref) which controls the
/// batch size.
///
/// Generally speaking, almost all benchmarks should use `SmallInput`. If the input or the result
/// of the benchmark routine is large enough that `SmallInput` causes out-of-memory errors,
/// `LargeInput` can be used to reduce memory usage at the cost of increasing the measurement
/// overhead. If the input or the result is extremely large (or if it holds some
/// limited external resource like a file handle), `PerIteration` will set the number of iterations
/// per batch to exactly one. `PerIteration` can increase the measurement overhead substantially
/// and should be avoided wherever possible.
///
/// Each value lists an estimate of the measurement overhead. This is intended as a rough guide
/// to assist in choosing an option, it should not be relied upon. In particular, it is not valid
/// to subtract the listed overhead from the measurement and assume that the result represents the
/// true runtime of a function. The actual measurement overhead for your specific benchmark depends
/// on the details of the function you're benchmarking and the hardware and operating
/// system running the benchmark.
///
/// With that said, if the runtime of your function is small relative to the measurement overhead
/// it will be difficult to take accurate measurements. In this situation, the best option is to use
/// [`Bencher::iter`](struct.Bencher.html#method.iter) which has next-to-zero measurement overhead.
#[derive(Debug, Eq, PartialEq, Copy, Hash, Clone)]
pub enum BatchSize {
/// `SmallInput` indicates that the input to the benchmark routine (the value returned from
/// the setup routine) is small enough that millions of values can be safely held in memory.
/// Always prefer `SmallInput` unless the benchmark is using too much memory.
///
/// In testing, the maximum measurement overhead from benchmarking with `SmallInput` is on the
/// order of 500 picoseconds. This is presented as a rough guide; your results may vary.
SmallInput,
/// `LargeInput` indicates that the input to the benchmark routine or the value returned from
/// that routine is large. This will reduce the memory usage but increase the measurement
/// overhead.
///
/// In testing, the maximum measurement overhead from benchmarking with `LargeInput` is on the
/// order of 750 picoseconds. This is presented as a rough guide; your results may vary.
LargeInput,
/// `PerIteration` indicates that the input to the benchmark routine or the value returned from
/// that routine is extremely large or holds some limited resource, such that holding many values
/// in memory at once is infeasible. This provides the worst measurement overhead, but the
/// lowest memory usage.
///
/// In testing, the maximum measurement overhead from benchmarking with `PerIteration` is on the
/// order of 350 nanoseconds or 350,000 picoseconds. This is presented as a rough guide; your
/// results may vary.
PerIteration,
/// `NumBatches` will attempt to divide the iterations up into a given number of batches.
/// A larger number of batches (and thus smaller batches) will reduce memory usage but increase
/// measurement overhead. This allows the user to choose their own tradeoff between memory usage
/// and measurement overhead, but care must be taken in tuning the number of batches. Most
/// benchmarks should use `SmallInput` or `LargeInput` instead.
NumBatches(u64),
/// `NumIterations` fixes the batch size to a constant number, specified by the user. This
/// allows the user to choose their own tradeoff between overhead and memory usage, but care must
/// be taken in tuning the batch size. In general, the measurement overhead of `NumIterations`
/// will be larger than that of `NumBatches`. Most benchmarks should use `SmallInput` or
/// `LargeInput` instead.
NumIterations(u64),
#[doc(hidden)]
__NonExhaustive,
}
impl BatchSize {
/// Convert to a number of iterations per batch.
///
/// We try to do a constant number of batches regardless of the number of iterations in this
/// sample. If the measurement overhead is roughly constant regardless of the number of
/// iterations the analysis of the results later will have an easier time separating the
/// measurement overhead from the benchmark time.
fn iters_per_batch(self, iters: u64) -> u64 {
match self {
BatchSize::SmallInput => (iters + 10 - 1) / 10,
BatchSize::LargeInput => (iters + 1000 - 1) / 1000,
BatchSize::PerIteration => 1,
BatchSize::NumBatches(batches) => (iters + batches - 1) / batches,
BatchSize::NumIterations(size) => size,
BatchSize::__NonExhaustive => panic!("__NonExhaustive is not a valid BatchSize."),
}
}
}
/// Baseline describes how the baseline_directory is handled.
#[derive(Debug, Clone, Copy)]
pub enum Baseline {
/// Compare ensures a previous saved version of the baseline
/// exists and runs comparison against that.
Compare,
/// Save writes the benchmark results to the baseline directory,
/// overwriting any results that were previously there.
Save,
}
/// Enum used to select the plotting backend.
#[derive(Debug, Clone, Copy)]
pub enum PlottingBackend {
/// Plotting backend which uses the external `gnuplot` command to render plots. This is the
/// default if the `gnuplot` command is installed.
Gnuplot,
/// Plotting backend which uses the rust 'Plotters' library. This is the default if `gnuplot`
/// is not installed.
Plotters,
}
impl PlottingBackend {
fn create_plotter(&self) -> Box<dyn Plotter> {
match self {
PlottingBackend::Gnuplot => Box::new(Gnuplot::default()),
PlottingBackend::Plotters => Box::new(PlottersBackend::default()),
}
}
}
#[derive(Debug, Clone)]
/// Enum representing the execution mode.
pub(crate) enum Mode {
/// Run benchmarks normally.
Benchmark,
/// List all benchmarks but do not run them.
List,
/// Run benchmarks once to verify that they work, but otherwise do not measure them.
Test,
/// Iterate benchmarks for a given length of time but do not analyze or report on them.
Profile(Duration),
}
impl Mode {
pub fn is_benchmark(&self) -> bool {
matches!(self, Mode::Benchmark)
}
}
/// The benchmark manager
///
/// `Criterion` lets you configure and execute benchmarks
///
/// Each benchmark consists of four phases:
///
/// - **Warm-up**: The routine is repeatedly executed, to let the CPU/OS/JIT/interpreter adapt to
/// the new load
/// - **Measurement**: The routine is repeatedly executed, and timing information is collected into
/// a sample
/// - **Analysis**: The sample is analyzed and distilled into meaningful statistics that get
/// reported to stdout, stored in files, and plotted
/// - **Comparison**: The current sample is compared with the sample obtained in the previous
/// benchmark.
pub struct Criterion<M: Measurement = WallTime> {
config: BenchmarkConfig,
filter: Option<Regex>,
report: Reports,
output_directory: PathBuf,
baseline_directory: String,
baseline: Baseline,
load_baseline: Option<String>,
all_directories: HashSet<String>,
all_titles: HashSet<String>,
measurement: M,
profiler: Box<RefCell<dyn Profiler>>,
connection: Option<MutexGuard<'static, Connection>>,
mode: Mode,
}
/// Returns the Cargo target directory, possibly calling `cargo metadata` to
/// figure it out.
fn cargo_target_directory() -> Option<PathBuf> {
#[derive(Deserialize)]
struct Metadata {
target_directory: PathBuf,
}
env::var_os("CARGO_TARGET_DIR")
.map(PathBuf::from)
.or_else(|| {
let output = Command::new(env::var_os("CARGO")?)
.args(&["metadata", "--format-version", "1"])
.output()
.ok()?;
let metadata: Metadata = serde_json::from_slice(&output.stdout).ok()?;
Some(metadata.target_directory)
})
}
impl Default for Criterion {
/// Creates a benchmark manager with the following default settings:
///
/// - Sample size: 100 measurements
/// - Warm-up time: 3 s
/// - Measurement time: 5 s
/// - Bootstrap size: 100 000 resamples
/// - Noise threshold: 0.01 (1%)
/// - Confidence level: 0.95
/// - Significance level: 0.05
/// - Plotting: enabled, using gnuplot if available or plotters if gnuplot is not available
/// - No filter
fn default() -> Criterion {
let reports = Reports {
cli_enabled: true,
cli: CliReport::new(false, false, false),
bencher_enabled: false,
bencher: BencherReport,
html_enabled: true,
html: Html::new(DEFAULT_PLOTTING_BACKEND.create_plotter()),
csv_enabled: true,
csv: FileCsvReport,
};
let mut criterion = Criterion {
config: BenchmarkConfig {
confidence_level: 0.95,
measurement_time: Duration::new(5, 0),
noise_threshold: 0.01,
nresamples: 100_000,
sample_size: 100,
significance_level: 0.05,
warm_up_time: Duration::new(3, 0),
sampling_mode: SamplingMode::Auto,
},
filter: None,
report: reports,
baseline_directory: "base".to_owned(),
baseline: Baseline::Save,
load_baseline: None,
output_directory: DEFAULT_OUTPUT_DIRECTORY.clone(),
all_directories: HashSet::new(),
all_titles: HashSet::new(),
measurement: WallTime,
profiler: Box::new(RefCell::new(ExternalProfiler)),
connection: CARGO_CRITERION_CONNECTION
.as_ref()
.map(|mtx| mtx.lock().unwrap()),
mode: Mode::Benchmark,
};
if criterion.connection.is_some() {
// disable all reports when connected to cargo-criterion; it will do the reporting.
criterion.report.cli_enabled = false;
criterion.report.bencher_enabled = false;
criterion.report.csv_enabled = false;
criterion.report.html_enabled = false;
}
criterion
}
}
impl<M: Measurement> Criterion<M> {
/// Changes the measurement for the benchmarks run with this runner. See the
/// Measurement trait for more details
pub fn with_measurement<M2: Measurement>(self, m: M2) -> Criterion<M2> {
// Can't use struct update syntax here because they're technically different types.
Criterion {
config: self.config,
filter: self.filter,
report: self.report,
baseline_directory: self.baseline_directory,
baseline: self.baseline,
load_baseline: self.load_baseline,
output_directory: self.output_directory,
all_directories: self.all_directories,
all_titles: self.all_titles,
measurement: m,
profiler: self.profiler,
connection: self.connection,
mode: self.mode,
}
}
/// Changes the internal profiler for benchmarks run with this runner. See
/// the Profiler trait for more details.
pub fn with_profiler<P: Profiler + 'static>(self, p: P) -> Criterion<M> {
Criterion {
profiler: Box::new(RefCell::new(p)),
..self
}
}
/// Set the plotting backend. By default, Criterion will use gnuplot if available, or plotters
/// if not.
///
/// Panics if `backend` is `PlottingBackend::Gnuplot` and gnuplot is not available.
pub fn plotting_backend(mut self, backend: PlottingBackend) -> Criterion<M> {
if let PlottingBackend::Gnuplot = backend {
if GNUPLOT_VERSION.is_err() {
panic!("Gnuplot plotting backend was requested, but gnuplot is not available. To continue, either install Gnuplot or allow Criterion.rs to fall back to using plotters.");
}
}
self.report.html = Html::new(backend.create_plotter());
self
}
/// Changes the default size of the sample for benchmarks run with this runner.
///
/// A bigger sample should yield more accurate results if paired with a sufficiently large
/// measurement time.
///
/// Sample size must be at least 10.
///
/// # Panics
///
/// Panics if n < 10
pub fn sample_size(mut self, n: usize) -> Criterion<M> {
assert!(n >= 10);
self.config.sample_size = n;
self
}
/// Changes the default warm up time for benchmarks run with this runner.
///
/// # Panics
///
/// Panics if the input duration is zero
pub fn warm_up_time(mut self, dur: Duration) -> Criterion<M> {
assert!(dur.to_nanos() > 0);
self.config.warm_up_time = dur;
self
}
/// Changes the default measurement time for benchmarks run with this runner.
///
/// With a longer time, the measurement will become more resilient to transitory peak loads
/// caused by external programs
///
/// **Note**: If the measurement time is too "low", Criterion will automatically increase it
///
/// # Panics
///
/// Panics if the input duration in zero
pub fn measurement_time(mut self, dur: Duration) -> Criterion<M> {
assert!(dur.to_nanos() > 0);
self.config.measurement_time = dur;
self
}
/// Changes the default number of resamples for benchmarks run with this runner.
///
/// Number of resamples to use for the
/// [bootstrap](http://en.wikipedia.org/wiki/Bootstrapping_(statistics)#Case_resampling)
///
/// A larger number of resamples reduces the random sampling errors, which are inherent to the
/// bootstrap method, but also increases the analysis time
///
/// # Panics
///
/// Panics if the number of resamples is set to zero
pub fn nresamples(mut self, n: usize) -> Criterion<M> {
assert!(n > 0);
if n <= 1000 {
println!("\nWarning: It is not recommended to reduce nresamples below 1000.");
}
self.config.nresamples = n;
self
}
/// Changes the default noise threshold for benchmarks run with this runner. The noise threshold
/// is used to filter out small changes in performance, even if they are statistically
/// significant. Sometimes benchmarking the same code twice will result in small but
/// statistically significant differences solely because of noise. This provides a way to filter
/// out some of these false positives at the cost of making it harder to detect small changes
/// to the true performance of the benchmark.
///
/// The default is 0.01, meaning that changes smaller than 1% will be ignored.
///
/// # Panics
///
/// Panics if the threshold is set to a negative value
pub fn noise_threshold(mut self, threshold: f64) -> Criterion<M> {
assert!(threshold >= 0.0);
self.config.noise_threshold = threshold;
self
}
/// Changes the default confidence level for benchmarks run with this runner. The confidence
/// level is the desired probability that the true runtime lies within the estimated
/// [confidence interval](https://en.wikipedia.org/wiki/Confidence_interval). The default is
/// 0.95, meaning that the confidence interval should capture the true value 95% of the time.
///
/// # Panics
///
/// Panics if the confidence level is set to a value outside the `(0, 1)` range
pub fn confidence_level(mut self, cl: f64) -> Criterion<M> {
assert!(cl > 0.0 && cl < 1.0);
if cl < 0.5 {
println!("\nWarning: It is not recommended to reduce confidence level below 0.5.");
}
self.config.confidence_level = cl;
self
}
/// Changes the default [significance level](https://en.wikipedia.org/wiki/Statistical_significance)
/// for benchmarks run with this runner. This is used to perform a
/// [hypothesis test](https://en.wikipedia.org/wiki/Statistical_hypothesis_testing) to see if
/// the measurements from this run are different from the measured performance of the last run.
/// The significance level is the desired probability that two measurements of identical code
/// will be considered 'different' due to noise in the measurements. The default value is 0.05,
/// meaning that approximately 5% of identical benchmarks will register as different due to
/// noise.
///
/// This presents a trade-off. By setting the significance level closer to 0.0, you can increase
/// the statistical robustness against noise, but it also weakens Criterion.rs' ability to
/// detect small but real changes in the performance. By setting the significance level
/// closer to 1.0, Criterion.rs will be more able to detect small true changes, but will also
/// report more spurious differences.
///
/// See also the noise threshold setting.
///
/// # Panics
///
/// Panics if the significance level is set to a value outside the `(0, 1)` range
pub fn significance_level(mut self, sl: f64) -> Criterion<M> {
assert!(sl > 0.0 && sl < 1.0);
self.config.significance_level = sl;
self
}
/// Enables plotting
pub fn with_plots(mut self) -> Criterion<M> {
// If running under cargo-criterion then don't re-enable the reports; let it do the reporting.
if self.connection.is_none() {
self.report.html_enabled = true;
}
self
}
/// Disables plotting
pub fn without_plots(mut self) -> Criterion<M> {
self.report.html_enabled = false;
self
}
/// Return true if generation of the plots is possible.
#[deprecated(
since = "0.3.4",
note = "No longer useful; since the plotters backend is available Criterion.rs can always generate plots"
)]
pub fn can_plot(&self) -> bool {
// Trivially true now that we have plotters.
// TODO: Deprecate and remove this.
true
}
/// Names an explicit baseline and enables overwriting the previous results.
pub fn save_baseline(mut self, baseline: String) -> Criterion<M> {
self.baseline_directory = baseline;
self.baseline = Baseline::Save;
self
}
/// Names an explicit baseline and disables overwriting the previous results.
pub fn retain_baseline(mut self, baseline: String) -> Criterion<M> {
self.baseline_directory = baseline;
self.baseline = Baseline::Compare;
self
}
/// Filters the benchmarks. Only benchmarks with names that contain the
/// given string will be executed.
pub fn with_filter<S: Into<String>>(mut self, filter: S) -> Criterion<M> {
let filter_text = filter.into();
let filter = Regex::new(&filter_text).unwrap_or_else(|err| {
panic!(
"Unable to parse '{}' as a regular expression: {}",
filter_text, err
)
});
self.filter = Some(filter);
self
}
/// Override whether the CLI output will be colored or not. Usually you would use the `--color`
/// CLI argument, but this is available for programmmatic use as well.
pub fn with_output_color(mut self, enabled: bool) -> Criterion<M> {
self.report.cli.enable_text_coloring = enabled;
self
}
/// Set the output directory (currently for testing only)
#[doc(hidden)]
pub fn output_directory(mut self, path: &Path) -> Criterion<M> {
self.output_directory = path.to_owned();
self
}
/// Set the profile time (currently for testing only)
#[doc(hidden)]
pub fn profile_time(mut self, profile_time: Option<Duration>) -> Criterion<M> {
match profile_time {
Some(time) => self.mode = Mode::Profile(time),
None => self.mode = Mode::Benchmark,
}
self
}
/// Generate the final summary at the end of a run.
#[doc(hidden)]
pub fn final_summary(&self) {
if !self.mode.is_benchmark() {
return;
}
let report_context = ReportContext {
output_directory: self.output_directory.clone(),
plot_config: PlotConfiguration::default(),
};
self.report.final_summary(&report_context);
}
/// Configure this criterion struct based on the command-line arguments to
/// this process.
#[cfg_attr(feature = "cargo-clippy", allow(clippy::cognitive_complexity))]
pub fn configure_from_args(mut self) -> Criterion<M> {
use clap::{App, Arg};
let matches = App::new("Criterion Benchmark")
.arg(Arg::with_name("FILTER")
.help("Skip benchmarks whose names do not contain FILTER.")
.index(1))
.arg(Arg::with_name("color")
.short("c")
.long("color")
.alias("colour")
.takes_value(true)
.possible_values(&["auto", "always", "never"])
.default_value("auto")
.help("Configure coloring of output. always = always colorize output, never = never colorize output, auto = colorize output if output is a tty and compiled for unix."))
.arg(Arg::with_name("verbose")
.short("v")
.long("verbose")
.help("Print additional statistical information."))
.arg(Arg::with_name("noplot")
.short("n")
.long("noplot")
.help("Disable plot and HTML generation."))
.arg(Arg::with_name("save-baseline")
.short("s")
.long("save-baseline")
.default_value("base")
.help("Save results under a named baseline."))
.arg(Arg::with_name("baseline")
.short("b")
.long("baseline")
.takes_value(true)
.conflicts_with("save-baseline")
.help("Compare to a named baseline."))
.arg(Arg::with_name("list")
.long("list")
.help("List all benchmarks")
.conflicts_with_all(&["test", "profile-time"]))
.arg(Arg::with_name("profile-time")
.long("profile-time")
.takes_value(true)
.help("Iterate each benchmark for approximately the given number of seconds, doing no analysis and without storing the results. Useful for running the benchmarks in a profiler.")
.conflicts_with_all(&["test", "list"]))
.arg(Arg::with_name("load-baseline")
.long("load-baseline")
.takes_value(true)
.conflicts_with("profile-time")
.requires("baseline")
.help("Load a previous baseline instead of sampling new data."))
.arg(Arg::with_name("sample-size")
.long("sample-size")
.takes_value(true)
.help(&format!("Changes the default size of the sample for this run. [default: {}]", self.config.sample_size)))
.arg(Arg::with_name("warm-up-time")
.long("warm-up-time")
.takes_value(true)
.help(&format!("Changes the default warm up time for this run. [default: {}]", self.config.warm_up_time.as_secs())))
.arg(Arg::with_name("measurement-time")
.long("measurement-time")
.takes_value(true)
.help(&format!("Changes the default measurement time for this run. [default: {}]", self.config.measurement_time.as_secs())))
.arg(Arg::with_name("nresamples")
.long("nresamples")
.takes_value(true)
.help(&format!("Changes the default number of resamples for this run. [default: {}]", self.config.nresamples)))
.arg(Arg::with_name("noise-threshold")
.long("noise-threshold")
.takes_value(true)
.help(&format!("Changes the default noise threshold for this run. [default: {}]", self.config.noise_threshold)))
.arg(Arg::with_name("confidence-level")
.long("confidence-level")
.takes_value(true)
.help(&format!("Changes the default confidence level for this run. [default: {}]", self.config.confidence_level)))
.arg(Arg::with_name("significance-level")
.long("significance-level")
.takes_value(true)
.help(&format!("Changes the default significance level for this run. [default: {}]", self.config.significance_level)))
.arg(Arg::with_name("test")
.hidden(true)
.long("test")
.help("Run the benchmarks once, to verify that they execute successfully, but do not measure or report the results.")
.conflicts_with_all(&["list", "profile-time"]))
.arg(Arg::with_name("bench")
.hidden(true)
.long("bench"))
.arg(Arg::with_name("plotting-backend")
.long("plotting-backend")
.takes_value(true)
.possible_values(&["gnuplot", "plotters"])
.help("Set the plotting backend. By default, Criterion.rs will use the gnuplot backend if gnuplot is available, or the plotters backend if it isn't."))
.arg(Arg::with_name("output-format")
.long("output-format")
.takes_value(true)
.possible_values(&["criterion", "bencher"])
.default_value("criterion")
.help("Change the CLI output format. By default, Criterion.rs will use its own format. If output format is set to 'bencher', Criterion.rs will print output in a format that resembles the 'bencher' crate."))
.arg(Arg::with_name("nocapture")
.long("nocapture")
.hidden(true)
.help("Ignored, but added for compatibility with libtest."))
.arg(Arg::with_name("version")
.hidden(true)
.short("V")
.long("version"))
.after_help("
This executable is a Criterion.rs benchmark.
See https://github.com/bheisler/criterion.rs for more details.
To enable debug output, define the environment variable CRITERION_DEBUG.
Criterion.rs will output more debug information and will save the gnuplot
scripts alongside the generated plots.
To test that the benchmarks work, run `cargo test --benches`
NOTE: If you see an 'unrecognized option' error using any of the options above, see:
https://bheisler.github.io/criterion.rs/book/faq.html
")
.get_matches();
if self.connection.is_some() {
if let Some(color) = matches.value_of("color") {
if color != "auto" {
println!("Warning: --color will be ignored when running with cargo-criterion. Use `cargo criterion --color {} -- <args>` instead.", color);
}
}
if matches.is_present("verbose") {
println!("Warning: --verbose will be ignored when running with cargo-criterion. Use `cargo criterion --output-format verbose -- <args>` instead.");
}
if matches.is_present("noplot") {
println!("Warning: --noplot will be ignored when running with cargo-criterion. Use `cargo criterion --plotting-backend disabled -- <args>` instead.");
}
if let Some(backend) = matches.value_of("plotting-backend") {
println!("Warning: --plotting-backend will be ignored when running with cargo-criterion. Use `cargo criterion --plotting-backend {} -- <args>` instead.", backend);
}
if let Some(format) = matches.value_of("output-format") {
if format != "criterion" {
println!("Warning: --output-format will be ignored when running with cargo-criterion. Use `cargo criterion --output-format {} -- <args>` instead.", format);
}
}
if matches.is_present("baseline")
|| matches
.value_of("save-baseline")
.map(|base| base != "base")
.unwrap_or(false)
|| matches.is_present("load-baseline")
{
println!("Error: baselines are not supported when running with cargo-criterion.");
std::process::exit(1);
}
}
let bench = matches.is_present("bench");
let test = matches.is_present("test");
let test_mode = match (bench, test) {
(true, true) => true, // cargo bench -- --test should run tests
(true, false) => false, // cargo bench should run benchmarks
(false, _) => true, // cargo test --benches should run tests
};
self.mode = if test_mode {
Mode::Test
} else if matches.is_present("list") {
Mode::List
} else if matches.is_present("profile-time") {
let num_seconds = value_t!(matches.value_of("profile-time"), u64).unwrap_or_else(|e| {
println!("{}", e);
std::process::exit(1)
});
if num_seconds < 1 {
println!("Profile time must be at least one second.");
std::process::exit(1);
}
Mode::Profile(Duration::from_secs(num_seconds))
} else {
Mode::Benchmark
};
// This is kind of a hack, but disable the connection to the runner if we're not benchmarking.
if !self.mode.is_benchmark() {
self.connection = None;
}
if let Some(filter) = matches.value_of("FILTER") {
self = self.with_filter(filter);
}
match matches.value_of("plotting-backend") {
// Use plotting_backend() here to re-use the panic behavior if Gnuplot is not available.
Some("gnuplot") => self = self.plotting_backend(PlottingBackend::Gnuplot),
Some("plotters") => self = self.plotting_backend(PlottingBackend::Plotters),
Some(val) => panic!("Unexpected plotting backend '{}'", val),
None => {}
}
if matches.is_present("noplot") {
self = self.without_plots();
} else {
self = self.with_plots();
}
if let Some(dir) = matches.value_of("save-baseline") {
self.baseline = Baseline::Save;
self.baseline_directory = dir.to_owned()
}
if let Some(dir) = matches.value_of("baseline") {
self.baseline = Baseline::Compare;
self.baseline_directory = dir.to_owned();
}
if self.connection.is_some() {
// disable all reports when connected to cargo-criterion; it will do the reporting.
self.report.cli_enabled = false;
self.report.bencher_enabled = false;
self.report.csv_enabled = false;
self.report.html_enabled = false;
} else {
match matches.value_of("output-format") {
Some("bencher") => {
self.report.bencher_enabled = true;
self.report.cli_enabled = false;
}
_ => {
let verbose = matches.is_present("verbose");
let stdout_isatty = atty::is(atty::Stream::Stdout);
let mut enable_text_overwrite = stdout_isatty && !verbose && !debug_enabled();
let enable_text_coloring;
match matches.value_of("color") {
Some("always") => {
enable_text_coloring = true;
}
Some("never") => {
enable_text_coloring = false;
enable_text_overwrite = false;
}
_ => enable_text_coloring = stdout_isatty,
};
self.report.bencher_enabled = false;
self.report.cli_enabled = true;
self.report.cli =
CliReport::new(enable_text_overwrite, enable_text_coloring, verbose);
}
};
}
if let Some(dir) = matches.value_of("load-baseline") {
self.load_baseline = Some(dir.to_owned());
}
if matches.is_present("sample-size") {
let num_size = value_t!(matches.value_of("sample-size"), usize).unwrap_or_else(|e| {
println!("{}", e);
std::process::exit(1)
});
assert!(num_size >= 10);
self.config.sample_size = num_size;
}
if matches.is_present("warm-up-time") {
let num_seconds = value_t!(matches.value_of("warm-up-time"), u64).unwrap_or_else(|e| {
println!("{}", e);
std::process::exit(1)
});
let dur = std::time::Duration::new(num_seconds, 0);
assert!(dur.to_nanos() > 0);
self.config.warm_up_time = dur;
}
if matches.is_present("measurement-time") {
let num_seconds =
value_t!(matches.value_of("measurement-time"), u64).unwrap_or_else(|e| {
println!("{}", e);
std::process::exit(1)
});
let dur = std::time::Duration::new(num_seconds, 0);
assert!(dur.to_nanos() > 0);
self.config.measurement_time = dur;
}
if matches.is_present("nresamples") {
let num_resamples =
value_t!(matches.value_of("nresamples"), usize).unwrap_or_else(|e| {
println!("{}", e);
std::process::exit(1)
});
assert!(num_resamples > 0);
self.config.nresamples = num_resamples;
}
if matches.is_present("noise-threshold") {
let num_noise_threshold = value_t!(matches.value_of("noise-threshold"), f64)
.unwrap_or_else(|e| {
println!("{}", e);
std::process::exit(1)
});
assert!(num_noise_threshold > 0.0);
self.config.noise_threshold = num_noise_threshold;
}
if matches.is_present("confidence-level") {
let num_confidence_level = value_t!(matches.value_of("confidence-level"), f64)
.unwrap_or_else(|e| {
println!("{}", e);
std::process::exit(1)
});
assert!(num_confidence_level > 0.0 && num_confidence_level < 1.0);
self.config.confidence_level = num_confidence_level;
}
if matches.is_present("significance-level") {
let num_significance_level = value_t!(matches.value_of("significance-level"), f64)
.unwrap_or_else(|e| {
println!("{}", e);
std::process::exit(1)
});
assert!(num_significance_level > 0.0 && num_significance_level < 1.0);
self.config.significance_level = num_significance_level;
}
self
}
fn filter_matches(&self, id: &str) -> bool {
match self.filter {
Some(ref regex) => regex.is_match(id),
None => true,
}
}
/// Return a benchmark group. All benchmarks performed using a benchmark group will be
/// grouped together in the final report.
///
/// # Examples:
///
/// ```rust
/// #[macro_use] extern crate criterion;
/// use self::criterion::*;
///
/// fn bench_simple(c: &mut Criterion) {
/// let mut group = c.benchmark_group("My Group");
///
/// // Now we can perform benchmarks with this group
/// group.bench_function("Bench 1", |b| b.iter(|| 1 ));
/// group.bench_function("Bench 2", |b| b.iter(|| 2 ));
///
/// group.finish();
/// }
/// criterion_group!(benches, bench_simple);
/// criterion_main!(benches);
/// ```
/// # Panics:
/// Panics if the group name is empty
pub fn benchmark_group<S: Into<String>>(&mut self, group_name: S) -> BenchmarkGroup<'_, M> {
let group_name = group_name.into();
if group_name.is_empty() {
panic!("Group name must not be empty.");
}
if let Some(conn) = &self.connection {
conn.send(&OutgoingMessage::BeginningBenchmarkGroup { group: &group_name })
.unwrap();
}
BenchmarkGroup::new(self, group_name)
}
}
impl<M> Criterion<M>
where
M: Measurement + 'static,
{
/// Benchmarks a function. For comparing multiple functions, see `benchmark_group`.
///
/// # Example
///
/// ```rust
/// #[macro_use] extern crate criterion;
/// use self::criterion::*;
///
/// fn bench(c: &mut Criterion) {
/// // Setup (construct data, allocate memory, etc)
/// c.bench_function(
/// "function_name",
/// |b| b.iter(|| {
/// // Code to benchmark goes here
/// }),
/// );
/// }
///
/// criterion_group!(benches, bench);
/// criterion_main!(benches);
/// ```
pub fn bench_function<F>(&mut self, id: &str, f: F) -> &mut Criterion<M>
where
F: FnMut(&mut Bencher<'_, M>),
{
self.benchmark_group(id)
.bench_function(BenchmarkId::no_function(), f);
self
}
/// Benchmarks a function with an input. For comparing multiple functions or multiple inputs,
/// see `benchmark_group`.
///
/// # Example
///
/// ```rust
/// #[macro_use] extern crate criterion;
/// use self::criterion::*;
///
/// fn bench(c: &mut Criterion) {
/// // Setup (construct data, allocate memory, etc)
/// let input = 5u64;
/// c.bench_with_input(
/// BenchmarkId::new("function_name", input), &input,
/// |b, i| b.iter(|| {
/// // Code to benchmark using input `i` goes here
/// }),
/// );
/// }
///
/// criterion_group!(benches, bench);
/// criterion_main!(benches);
/// ```
pub fn bench_with_input<F, I>(&mut self, id: BenchmarkId, input: &I, f: F) -> &mut Criterion<M>
where
F: FnMut(&mut Bencher<'_, M>, &I),
{
// It's possible to use BenchmarkId::from_parameter to create a benchmark ID with no function
// name. That's intended for use with BenchmarkGroups where the function name isn't necessary,
// but here it is.
let group_name = id.function_name.expect(
"Cannot use BenchmarkId::from_parameter with Criterion::bench_with_input. \
Consider using a BenchmarkGroup or BenchmarkId::new instead.",
);
// Guaranteed safe because external callers can't create benchmark IDs without a parameter
let parameter = id.parameter.unwrap();
self.benchmark_group(group_name).bench_with_input(
BenchmarkId::no_function_with_input(parameter),
input,
f,
);
self
}
/// Benchmarks a function under various inputs
///
/// This is a convenience method to execute several related benchmarks. Each benchmark will
/// receive the id: `${id}/${input}`.
///
/// # Example
///
/// ```rust
/// # #[macro_use] extern crate criterion;
/// # use self::criterion::*;
///
/// fn bench(c: &mut Criterion) {
/// c.bench_function_over_inputs("from_elem",
/// |b: &mut Bencher, size: &usize| {
/// b.iter(|| vec![0u8; *size]);
/// },
/// vec![1024, 2048, 4096]
/// );
/// }
///
/// criterion_group!(benches, bench);
/// criterion_main!(benches);
/// ```
#[doc(hidden)]
#[deprecated(since = "0.3.4", note = "Please use BenchmarkGroups instead.")]
#[allow(deprecated)]
pub fn bench_function_over_inputs<I, F>(
&mut self,
id: &str,
f: F,
inputs: I,
) -> &mut Criterion<M>
where
I: IntoIterator,
I::Item: fmt::Debug + 'static,
F: FnMut(&mut Bencher<'_, M>, &I::Item) + 'static,
{
self.bench(id, ParameterizedBenchmark::new(id, f, inputs))
}
/// Benchmarks multiple functions
///
/// All functions get the same input and are compared with the other implementations.
/// Works similar to `bench_function`, but with multiple functions.
///
/// # Example
///
/// ``` rust
/// # #[macro_use] extern crate criterion;
/// # use self::criterion::*;
/// # fn seq_fib(i: &u32) {}
/// # fn par_fib(i: &u32) {}
///
/// fn bench_seq_fib(b: &mut Bencher, i: &u32) {
/// b.iter(|| {
/// seq_fib(i);
/// });
/// }
///
/// fn bench_par_fib(b: &mut Bencher, i: &u32) {
/// b.iter(|| {
/// par_fib(i);
/// });
/// }
///
/// fn bench(c: &mut Criterion) {
/// let sequential_fib = Fun::new("Sequential", bench_seq_fib);
/// let parallel_fib = Fun::new("Parallel", bench_par_fib);
/// let funs = vec![sequential_fib, parallel_fib];
///
/// c.bench_functions("Fibonacci", funs, 14);
/// }
///
/// criterion_group!(benches, bench);
/// criterion_main!(benches);
/// ```
#[doc(hidden)]
#[deprecated(since = "0.3.4", note = "Please use BenchmarkGroups instead.")]
#[allow(deprecated)]
pub fn bench_functions<I>(
&mut self,
id: &str,
funs: Vec<Fun<I, M>>,
input: I,
) -> &mut Criterion<M>
where
I: fmt::Debug + 'static,
{
let benchmark = ParameterizedBenchmark::with_functions(
funs.into_iter().map(|fun| fun.f).collect(),
vec![input],
);
self.bench(id, benchmark)
}
/// Executes the given benchmark. Use this variant to execute benchmarks
/// with complex configuration. This can be used to compare multiple
/// functions, execute benchmarks with custom configuration settings and
/// more. See the Benchmark and ParameterizedBenchmark structs for more
/// information.
///
/// ```rust
/// # #[macro_use] extern crate criterion;
/// # use criterion::*;
/// # fn routine_1() {}
/// # fn routine_2() {}
///
/// fn bench(c: &mut Criterion) {
/// // Setup (construct data, allocate memory, etc)
/// c.bench(
/// "routines",
/// Benchmark::new("routine_1", |b| b.iter(|| routine_1()))
/// .with_function("routine_2", |b| b.iter(|| routine_2()))
/// .sample_size(50)
/// );
/// }
///
/// criterion_group!(benches, bench);
/// criterion_main!(benches);
/// ```
#[doc(hidden)]
#[deprecated(since = "0.3.4", note = "Please use BenchmarkGroups instead.")]
pub fn bench<B: BenchmarkDefinition<M>>(
&mut self,
group_id: &str,
benchmark: B,
) -> &mut Criterion<M> {
benchmark.run(group_id, self);
self
}
}
trait DurationExt {
fn to_nanos(&self) -> u64;
}
const NANOS_PER_SEC: u64 = 1_000_000_000;
impl DurationExt for Duration {
fn to_nanos(&self) -> u64 {
self.as_secs() * NANOS_PER_SEC + u64::from(self.subsec_nanos())
}
}
/// Enum representing different ways of measuring the throughput of benchmarked code.
/// If the throughput setting is configured for a benchmark then the estimated throughput will
/// be reported as well as the time per iteration.
// TODO: Remove serialize/deserialize from the public API.
#[derive(Debug, Clone, Serialize, Deserialize, PartialEq)]
pub enum Throughput {
/// Measure throughput in terms of bytes/second. The value should be the number of bytes
/// processed by one iteration of the benchmarked code. Typically, this would be the length of
/// an input string or `&[u8]`.
Bytes(u64),
/// Measure throughput in terms of elements/second. The value should be the number of elements
/// processed by one iteration of the benchmarked code. Typically, this would be the size of a
/// collection, but could also be the number of lines of input text or the number of values to
/// parse.
Elements(u64),
}
/// Axis scaling type
#[derive(Debug, Clone, Copy)]
pub enum AxisScale {
/// Axes scale linearly
Linear,
/// Axes scale logarithmically
Logarithmic,
}
/// Contains the configuration options for the plots generated by a particular benchmark
/// or benchmark group.
///
/// ```rust
/// use self::criterion::{Bencher, Criterion, Benchmark, PlotConfiguration, AxisScale};
///
/// let plot_config = PlotConfiguration::default()
/// .summary_scale(AxisScale::Logarithmic);
///
/// // Using Criterion::default() for simplicity; normally you'd use the macros.
/// let mut criterion = Criterion::default();
/// let mut benchmark_group = criterion.benchmark_group("Group name");
/// benchmark_group.plot_config(plot_config);
/// // Use benchmark group
/// ```
#[derive(Debug, Clone)]
pub struct PlotConfiguration {
summary_scale: AxisScale,
}
impl Default for PlotConfiguration {
fn default() -> PlotConfiguration {
PlotConfiguration {
summary_scale: AxisScale::Linear,
}
}
}
impl PlotConfiguration {
/// Set the axis scale (linear or logarithmic) for the summary plots. Typically, you would
/// set this to logarithmic if benchmarking over a range of inputs which scale exponentially.
/// Defaults to linear.
pub fn summary_scale(mut self, new_scale: AxisScale) -> PlotConfiguration {
self.summary_scale = new_scale;
self
}
}
/// This enum allows the user to control how Criterion.rs chooses the iteration count when sampling.
/// The default is Auto, which will choose a method automatically based on the iteration time during
/// the warm-up phase.
#[derive(Debug, Clone, Copy)]
pub enum SamplingMode {
/// Criterion.rs should choose a sampling method automatically. This is the default, and is
/// recommended for most users and most benchmarks.
Auto,
/// Scale the iteration count in each sample linearly. This is suitable for most benchmarks,
/// but it tends to require many iterations which can make it very slow for very long benchmarks.
Linear,
/// Keep the iteration count the same for all samples. This is not recommended, as it affects
/// the statistics that Criterion.rs can compute. However, it requires fewer iterations than
/// the Linear method and therefore is more suitable for very long-running benchmarks where
/// benchmark execution time is more of a problem and statistical precision is less important.
Flat,
}
impl SamplingMode {
pub(crate) fn choose_sampling_mode(
&self,
warmup_mean_execution_time: f64,
sample_count: u64,
target_time: f64,
) -> ActualSamplingMode {
match self {
SamplingMode::Linear => ActualSamplingMode::Linear,
SamplingMode::Flat => ActualSamplingMode::Flat,
SamplingMode::Auto => {
// Estimate execution time with linear sampling
let total_runs = sample_count * (sample_count + 1) / 2;
let d =
(target_time / warmup_mean_execution_time / total_runs as f64).ceil() as u64;
let expected_ns = total_runs as f64 * d as f64 * warmup_mean_execution_time;
if expected_ns > (2.0 * target_time) {
ActualSamplingMode::Flat
} else {
ActualSamplingMode::Linear
}
}
}
}
}
/// Enum to represent the sampling mode without Auto.
#[derive(Debug, Clone, Copy, Serialize, Deserialize)]
pub(crate) enum ActualSamplingMode {
Linear,
Flat,
}
impl ActualSamplingMode {
pub(crate) fn iteration_counts(
&self,
warmup_mean_execution_time: f64,
sample_count: u64,
target_time: &Duration,
) -> Vec<u64> {
match self {
ActualSamplingMode::Linear => {
let n = sample_count;
let met = warmup_mean_execution_time;
let m_ns = target_time.to_nanos();
// Solve: [d + 2*d + 3*d + ... + n*d] * met = m_ns
let total_runs = n * (n + 1) / 2;
let d = ((m_ns as f64 / met / total_runs as f64).ceil() as u64).max(1);
let expected_ns = total_runs as f64 * d as f64 * met;
if d == 1 {
let recommended_sample_size =
ActualSamplingMode::recommend_linear_sample_size(m_ns as f64, met);
let actual_time = Duration::from_nanos(expected_ns as u64);
print!("\nWarning: Unable to complete {} samples in {:.1?}. You may wish to increase target time to {:.1?}",
n, target_time, actual_time);
if recommended_sample_size != n {
println!(
", enable flat sampling, or reduce sample count to {}.",
recommended_sample_size
);
} else {
println!(" or enable flat sampling.");
}
}
(1..(n + 1) as u64).map(|a| a * d).collect::<Vec<u64>>()
}
ActualSamplingMode::Flat => {
let n = sample_count;
let met = warmup_mean_execution_time;
let m_ns = target_time.to_nanos() as f64;
let time_per_sample = m_ns / (n as f64);
// This is pretty simplistic; we could do something smarter to fit into the allotted time.
let iterations_per_sample = ((time_per_sample / met).ceil() as u64).max(1);
let expected_ns = met * (iterations_per_sample * n) as f64;
if iterations_per_sample == 1 {
let recommended_sample_size =
ActualSamplingMode::recommend_flat_sample_size(m_ns, met);
let actual_time = Duration::from_nanos(expected_ns as u64);
print!("\nWarning: Unable to complete {} samples in {:.1?}. You may wish to increase target time to {:.1?}",
n, target_time, actual_time);
if recommended_sample_size != n {
println!(", or reduce sample count to {}.", recommended_sample_size);
} else {
println!(".");
}
}
vec![iterations_per_sample; n as usize]
}
}
}
fn is_linear(&self) -> bool {
matches!(self, ActualSamplingMode::Linear)
}
fn recommend_linear_sample_size(target_time: f64, met: f64) -> u64 {
// Some math shows that n(n+1)/2 * d * met = target_time. d = 1, so it can be ignored.
// This leaves n(n+1) = (2*target_time)/met, or n^2 + n - (2*target_time)/met = 0
// Which can be solved with the quadratic formula. Since A and B are constant 1,
// this simplifies to sample_size = (-1 +- sqrt(1 - 4C))/2, where C = (2*target_time)/met.
// We don't care about the negative solution. Experimentation shows that this actually tends to
// result in twice the desired execution time (probably because of the ceil used to calculate
// d) so instead I use c = target_time/met.
let c = target_time / met;
let sample_size = (-1.0 + (4.0 * c).sqrt()) / 2.0;
let sample_size = sample_size as u64;
// Round down to the nearest 10 to give a margin and avoid excessive precision
let sample_size = (sample_size / 10) * 10;
// Clamp it to be at least 10, since criterion.rs doesn't allow sample sizes smaller than 10.
if sample_size < 10 {
10
} else {
sample_size
}
}
fn recommend_flat_sample_size(target_time: f64, met: f64) -> u64 {
let sample_size = (target_time / met) as u64;
// Round down to the nearest 10 to give a margin and avoid excessive precision
let sample_size = (sample_size / 10) * 10;
// Clamp it to be at least 10, since criterion.rs doesn't allow sample sizes smaller than 10.
if sample_size < 10 {
10
} else {
sample_size
}
}
}
#[derive(Debug, Serialize, Deserialize)]
pub(crate) struct SavedSample {
sampling_mode: ActualSamplingMode,
iters: Vec<f64>,
times: Vec<f64>,
}
/// Custom-test-framework runner. Should not be called directly.
#[doc(hidden)]
pub fn runner(benches: &[&dyn Fn()]) {
for bench in benches {
bench();
}
Criterion::default().configure_from_args().final_summary();
}
/// Print a warning informing users about upcoming changes to features
#[cfg(not(feature = "html_reports"))]
#[doc(hidden)]
pub fn __warn_about_html_reports_feature() {
if CARGO_CRITERION_CONNECTION.is_none() {
println!(
"WARNING: HTML report generation will become a non-default optional feature in Criterion.rs 0.4.0."
);
println!(
"This feature is being moved to cargo-criterion \
(https://github.com/bheisler/cargo-criterion) and will be optional in a future \
version of Criterion.rs. To silence this warning, either switch to cargo-criterion or \
enable the 'html_reports' feature in your Cargo.toml."
);
println!();
}
}
/// Print a warning informing users about upcoming changes to features
#[cfg(feature = "html_reports")]
#[doc(hidden)]
pub fn __warn_about_html_reports_feature() {
// They have the feature enabled, so they're ready for the update.
}
/// Print a warning informing users about upcoming changes to features
#[cfg(not(feature = "cargo_bench_support"))]
#[doc(hidden)]
pub fn __warn_about_cargo_bench_support_feature() {
if CARGO_CRITERION_CONNECTION.is_none() {
println!(
"WARNING: In Criterion.rs 0.4.0, running criterion benchmarks outside of cargo-criterion will become a default optional feature."
);
println!(
"The statistical analysis and reporting is being moved to cargo-criterion \
(https://github.com/bheisler/cargo-criterion) and will be optional in a future \
version of Criterion.rs. To silence this warning, either switch to cargo-criterion or \
enable the 'cargo_bench_support' feature in your Cargo.toml."
);
println!();
}
}
/// Print a warning informing users about upcoming changes to features
#[cfg(feature = "cargo_bench_support")]
#[doc(hidden)]
pub fn __warn_about_cargo_bench_support_feature() {
// They have the feature enabled, so they're ready for the update.
}