@astermind/astermind-synth/dist/omegasynth/generators/HybridGenerator.d.ts

OmegaSynth - Label-Conditioned Synthetic Data Generator for AsterMind ELM/KELM Pipelines

/**
 * HybridGenerator - Blends Retrieval + ELM jitter for realism + variation
 * 1. Retrieve real sample
 * 2. Encode
 * 3. Apply ELM noise
 * 4. Decode
 */
import { LabeledSample } from '../types';
export interface HybridGeneratorConfig {
    maxLength: number;
    elmHiddenUnits?: number;
    elmActivation?: 'tanh' | 'relu' | 'leakyrelu' | 'sigmoid' | 'linear' | 'gelu';
    elmRidgeLambda?: number;
    noiseSize?: number;
    jitterStrength?: number;
    exactMode?: boolean;
    useOneHot?: boolean;
    useClassification?: boolean;
    usePatternCorrection?: boolean;
    seed?: number;
}
export declare class HybridGenerator {
    private retrieval;
    private elm;
    private encoder;
    private config;
    private jitterStrength;
    private patternCorrector;
    constructor(config: HybridGeneratorConfig);
    /**
     * Train the hybrid generator on labeled samples
     */
    train(samples: LabeledSample[]): void;
    /**
     * Generate a hybrid sample (retrieval + jitter)
     * @param label Label to generate for
     * @param noiseSeed Optional seed for deterministic output
     */
    generate(label: string, noiseSeed?: number): string;
    /**
     * Apply jitter to an encoded vector
     */
    private applyJitter;
    /**
     * Generate an ELM vector for jittering
     */
    private generateELMVector;
    /**
     * Generate multiple hybrid samples
     */
    generateBatch(label: string, count: number): string[];
    /**
     * Get all available labels
     */
    getLabels(): string[];
    /**
     * Check if generator is trained
     */
    isTrained(): boolean;
}