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ActivationStats

kizzasi_model::interpretability

Struct ActivationStats 

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pub struct ActivationStats {
    pub mean: Array1<f32>,
    pub variance: Array1<f32>,
    pub max: Array1<f32>,
    pub min: Array1<f32>,
    pub sparsity: f32,
    pub l2_norm: f32,
    pub num_steps: usize,
    /* private fields */
}
Expand description

Running statistics over a sequence of activations.

Uses Welford’s online algorithm for numerically stable mean/variance.

Fields§

§mean: Array1<f32>

Per-dimension mean

§variance: Array1<f32>

Per-dimension variance (population variance)

§max: Array1<f32>

Per-dimension maximum encountered value

§min: Array1<f32>

Per-dimension minimum encountered value

§sparsity: f32

Fraction of values with absolute value below eps (default 1e-6)

§l2_norm: f32

Global L2 norm (average over all steps)

§num_steps: usize

Number of activation vectors accumulated

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impl ActivationStats

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pub fn from_sequence(activations: &[Array1<f32>]) -> ModelResult<Self>

Compute statistics from a fixed batch of activations.

Returns an error if the slice is empty or dimensions are inconsistent.

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pub fn update(&mut self, activation: &Array1<f32>)

Incrementally incorporate a new activation vector (Welford’s algorithm).

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pub fn reset(&mut self)

Reset all statistics back to zero.

Trait Implementations§

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impl Clone for ActivationStats

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fn clone(&self) -> ActivationStats

Returns a duplicate of the value. Read more
1.0.0 · Source§

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

Performs copy-assignment from source. Read more
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impl Debug for ActivationStats

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

Formats the value using the given formatter. Read more

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