tasq/node_modules/@claude-flow/neural/dist/modes/batch.d.ts

82 lines
2.2 KiB
TypeScript

/**
* Batch Mode Implementation
*
* Optimized for high-throughput processing with:
* - Large batch sizes (128)
* - Rank-8 LoRA
* - Gradient accumulation
* - Async batch processing
* - 50ms latency budget
*/
import type { SONAModeConfig, Trajectory, Pattern, PatternMatch, LoRAWeights, EWCState } from '../types.js';
import { BaseModeImplementation } from './base.js';
/**
* Batch mode for high-throughput processing
*/
export declare class BatchMode extends BaseModeImplementation {
readonly mode = "batch";
private patternQueue;
private learningQueue;
private embeddingBuffer;
private batchEmbeddings;
private accumulatedGradients;
private gradientSteps;
private isBatchProcessing;
private batchTimer;
private totalBatches;
private totalItems;
private totalBatchTime;
private learnIterations;
initialize(): Promise<void>;
cleanup(): Promise<void>;
/**
* Find patterns - queues for batch processing
*/
findPatterns(embedding: Float32Array, k: number, patterns: Pattern[]): Promise<PatternMatch[]>;
/**
* Learn from trajectories - accumulates for batch
*/
learn(trajectories: Trajectory[], config: SONAModeConfig, ewcState: EWCState): Promise<number>;
/**
* Apply LoRA with rank-8
*/
applyLoRA(input: Float32Array, weights?: LoRAWeights): Promise<Float32Array>;
getStats(): Record<string, number>;
/**
* Direct pattern matching without batching
*/
private findPatternsDirect;
/**
* Direct LoRA application
*/
private applyLoRADirect;
/**
* Schedule batch processing
*/
private scheduleBatchProcessing;
/**
* Process pattern requests in batch
*/
private processBatchPatterns;
/**
* Batch similarity search
*/
private batchSimilaritySearch;
/**
* Process batch learning
*/
private processBatchLearning;
/**
* Accumulate gradient from trajectory
*/
private accumulateTrajectoryGradient;
/**
* Apply accumulated gradients with EWC
*/
private applyAccumulatedGradients;
/**
* Apply LoRA to batch of inputs
*/
private applyLoRABatch;
}
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