Struct AttentionVisualizer 

pub struct AttentionVisualizer { /* private fields */ }

Attention pattern visualizer for transformer models

Implementations

impl AttentionVisualizer

pub fn new() -> Self

Create a new attention visualizer

Example

use trustformers_debug::AttentionVisualizer;

let visualizer = AttentionVisualizer::new();

pub fn with_config(config: AttentionVisualizerConfig) -> Self

Create a new attention visualizer with custom configuration

pub fn set_token_vocab(&mut self, tokens: Vec<String>)

Set token vocabulary for labeling

pub fn register( &mut self, layer_name: &str, weights: Vec<Vec<Vec<f64>>>, source_tokens: Vec<String>, target_tokens: Vec<String>, attention_type: AttentionType, ) -> Result<()>

Register attention weights for a layer

Arguments

• layer_name - Name of the layer
• weights - Attention weights [num_heads, seq_len, seq_len]
• source_tokens - Source (query) tokens
• target_tokens - Target (key) tokens
• attention_type - Type of attention mechanism

Example

let weights = vec![
    vec![vec![0.5, 0.3, 0.2], vec![0.1, 0.6, 0.3], vec![0.2, 0.3, 0.5]]
];
let tokens = vec!["Hello".to_string(), "world".to_string(), "!".to_string()];

visualizer.register(
    "layer.0.attention",
    weights,
    tokens.clone(),
    tokens.clone(),
    AttentionType::SelfAttention,
).unwrap();

pub fn get_attention(&self, layer_name: &str) -> Option<&AttentionWeights>

Get attention weights for a specific layer

pub fn create_heatmap( &self, layer_name: &str, head: usize, ) -> Result<AttentionHeatmap>

Create a heatmap for a specific head in a layer

pub fn analyze(&self, layer_name: &str) -> Result<AttentionAnalysis>

Analyze attention patterns for a layer

pub fn plot_heatmap_ascii( &self, layer_name: &str, head: usize, ) -> Result<String>

Plot attention heatmap as ASCII art

pub fn export_to_json(&self, layer_name: &str, output_path: &Path) -> Result<()>

Export attention weights to JSON

pub fn export_to_bertviz( &self, layer_name: &str, output_path: &Path, ) -> Result<()>

Export to BertViz-compatible format (HTML)

pub fn summary(&self) -> String

Get summary statistics for all layers

pub fn clear(&mut self)

Clear all stored attention weights

pub fn num_layers(&self) -> usize

Get number of stored layers

Trait Implementations

impl Debug for AttentionVisualizer

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

Formats the value using the given formatter.

impl Default for AttentionVisualizer

fn default() -> Self

Returns the “default value” for a type.