Struct InferenceResult 

pub struct InferenceResult {
    pub labels: Vec<String>,
    pub scores: Vec<f32>,
    pub predicted_class: usize,
    pub max_score: f32,
}

Inference result with classification predictions

Fields

labels: Vec<String>

Predicted class labels

scores: Vec<f32>

Confidence scores for each class (after post-processing)

predicted_class: usize

Predicted class index (highest score)

max_score: f32

Maximum confidence score

Implementations

impl InferenceResult

pub fn predicted_label(&self) -> Option<&str>

Get the predicted label

Example

use llm_shield_models::InferenceResult;

let result = InferenceResult {
    labels: vec!["SAFE".to_string(), "INJECTION".to_string()],
    scores: vec![0.8, 0.2],
    predicted_class: 0,
    max_score: 0.8,
};

assert_eq!(result.predicted_label(), Some("SAFE"));

pub fn exceeds_threshold(&self, threshold: f32) -> bool

Check if prediction confidence exceeds threshold

Arguments

• threshold - Minimum confidence threshold (0.0 to 1.0)

Example

use llm_shield_models::InferenceResult;

let result = InferenceResult {
    labels: vec!["SAFE".to_string(), "INJECTION".to_string()],
    scores: vec![0.3, 0.7],
    predicted_class: 1,
    max_score: 0.7,
};

assert!(result.exceeds_threshold(0.5));
assert!(!result.exceeds_threshold(0.8));

pub fn get_score_for_label(&self, label: &str) -> Option<f32>

Get score for a specific label

Arguments

• label - The label to get the score for

Returns

The confidence score for the label, or None if not found

pub fn is_binary(&self) -> bool

Check if this is a binary classification result

pub fn get_threshold_violations(&self, thresholds: &[f32]) -> Vec<usize>

Get indices of labels that exceed their respective thresholds

Used for multi-label classification where each class has its own threshold.

Arguments

• thresholds - Per-class thresholds (must match number of labels)

Returns

Vector of class indices that exceed their thresholds

pub fn from_binary_logits(logits: Vec<f32>, labels: Vec<String>) -> Self

Create InferenceResult from logits using softmax (single-label)

Arguments

• logits - Raw model output logits
• labels - Class labels

Example

use llm_shield_models::InferenceResult;

let logits = vec![1.0, 2.0, 0.5];
let labels = vec!["A".to_string(), "B".to_string(), "C".to_string()];
let result = InferenceResult::from_binary_logits(logits, labels);

// B should have highest probability
assert_eq!(result.predicted_class, 1);

pub fn from_multilabel_logits(logits: Vec<f32>, labels: Vec<String>) -> Self

Create InferenceResult from logits using sigmoid (multi-label)

Arguments

• logits - Raw model output logits
• labels - Class labels

Example

use llm_shield_models::InferenceResult;

let logits = vec![2.0, -1.0, 1.0];
let labels = vec!["toxic".to_string(), "threat".to_string(), "insult".to_string()];
let result = InferenceResult::from_multilabel_logits(logits, labels);

// All scores should be in [0, 1]
for score in &result.scores {
    assert!(*score >= 0.0 && *score <= 1.0);
}

Trait Implementations

impl Clone for InferenceResult

fn clone(&self) -> InferenceResult

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for InferenceResult

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

Formats the value using the given formatter.

impl<'de> Deserialize<'de> for InferenceResult

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl PartialEq for InferenceResult

fn eq(&self, other: &InferenceResult) -> bool

Tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl Serialize for InferenceResult

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.

impl StructuralPartialEq for InferenceResult