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use crate::ValidationError;
use std::fmt::Display;
/// Use nucleus sampling.
///
/// In nucleus sampling, we compute the cumulative distribution over all the options for each subsequent token in decreasing probability order and cut it off once it reaches a particular probability specified by top_p. You should either alter temperature or top_p, but not both.
///
/// Recommended for advanced use cases only. You usually only need to use temperature.
#[derive(
Debug,
Clone,
Copy,
PartialEq,
PartialOrd,
serde::Serialize,
serde::Deserialize,
)]
#[serde(transparent)]
pub struct TopP {
value: f32,
}
impl Default for TopP {
fn default() -> Self {
Self {
value: 1.0,
}
}
}
impl Display for TopP {
fn fmt(
&self,
f: &mut std::fmt::Formatter<'_>,
) -> std::fmt::Result {
write!(f, "{}", self.value)
}
}
impl TopP {
/// Creates a new top_p.
///
/// ## Arguments
/// - `value` - The value of the top_p.
///
/// ## Errors
/// It returns a validation error if the value is not in range: `[0.0, 1.0]`.
pub fn new(value: f32) -> Result<Self, ValidationError<f32>> {
if value < 0.0 || value > 1.0 {
return Err(ValidationError {
_type: "TopP".to_string(),
expected: "The top_p must be in range: [0.0, 1.0].".to_string(),
actual: value,
});
}
Ok(Self {
value,
})
}
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn new() {
let top_p = TopP::new(1.0);
assert_eq!(top_p.unwrap().value, 1.0);
}
#[test]
fn validate() {
assert!(TopP::new(-0.1).is_err());
assert!(TopP::new(0.0).is_ok());
assert!(TopP::new(0.5).is_ok());
assert!(TopP::new(1.0).is_ok());
assert!(TopP::new(1.1).is_err());
}
#[test]
fn default() {
assert_eq!(TopP::default().value, 1.0);
}
#[test]
fn display() {
let top_p = TopP::new(1.0);
assert_eq!(top_p.unwrap().to_string(), "1");
}
#[test]
fn serialize() {
let top_p = TopP::new(1.0);
assert_eq!(
serde_json::to_string(&top_p.unwrap()).unwrap(),
"1.0"
);
}
#[test]
fn deserialize() {
let top_p = TopP::new(1.0);
assert_eq!(
serde_json::from_str::<TopP>("1.0").unwrap(),
top_p.unwrap()
);
}
}