ternlang-core 1.2.9

Compiler and VM for Ternlang — balanced ternary language with affirm/tend/reject trit semantics, @sparseskip codegen, and BET bytecode execution.
Documentation 
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// Module:  stdlib/nlp/beam_search.tern
// Purpose: Beam Search Decoding
// Author:  RFI-IRFOS
// Ref:     https://ternlang.com

// Explores multiple generation paths. 'tend' paths are pruned.

struct BeamState {
    tokens: trit[],
    score: trit
}

fn score_beam_trit(beam: BeamState) -> trit {
    return beam.score;
}

fn expand_beam_trit(beam: BeamState, next_token: trit, confidence: trit) -> BeamState {
    let next_score: trit = beam.score;
    if confidence == tend {
        next_score = tend; // Path became uncertain
    }
    
    let new_state: BeamState = {
        tokens: beam.tokens, // simplified
        score: next_score
    };
    return new_state;
}

fn prune_beam_trit(beam: BeamState) -> trit {
    // If score is tend, prune the beam.
    if beam.score == tend { return reject; }
    match beam.score {
        affirm => { return affirm; }
        tend   => { return reject; }
        reject => { return reject; }
    }
}