import { Logger } from '../../utils/logger';
import { WasmPerformanceManager } from '../performance/wasm-manager';
import { NeuralCoordinationModels } from '../neural/coordination-models';

/**
 * @interface NeuralOptimizerConfig
 * @description Configuration for the Neural Performance Optimizer.
 */
export interface NeuralOptimizerConfig {
  projectID: string;
  // Add configuration for model quantization, GPU acceleration, etc.
}

/**
 * @interface NeuralOptimizerOperations
 * @description Defines operations for optimizing neural network performance.
 */
export interface NeuralOptimizerOperations {
  tuneWasmNeuralPerformance(): Promise<void>;
  optimizeModelForInference(modelId: string): Promise<void>;
  optimizeBatchProcessing(): Promise<void>;
  optimizeNeuralMemoryAllocation(): Promise<void>;
  enableGpuAcceleration(): Promise<void>;
  quantizeAndCompressModel(modelId: string): Promise<void>;
}

/**
 * @class NeuralOptimizer
 * @description Optimizes neural network performance, including WASM tuning, model optimization, and GPU acceleration.
 */
export class NeuralOptimizer implements NeuralOptimizerOperations {
  private config: NeuralOptimizerConfig;
  private logger: Logger;
  private wasmManager: WasmPerformanceManager;
  private neuralModels: NeuralCoordinationModels;

  constructor(
    config: NeuralOptimizerConfig,
    wasmManager: WasmPerformanceManager,
    neuralModels: NeuralCoordinationModels
  ) {
    this.config = config;
    this.logger = new Logger('NeuralOptimizer');
    this.wasmManager = wasmManager;
    this.neuralModels = neuralModels;
    this.logger.info('Neural Performance Optimizer initialized.');
  }

  /**
   * Tunes WASM neural network performance.
   * @returns {Promise<void>}
   */
  public async tuneWasmNeuralPerformance(): Promise<void> {
    this.logger.info('Tuning WASM neural network performance (conceptual)...');
    // This would involve using WasmPerformanceOptimizer to auto-tune the WASM engine.
    await this.wasmManager.autoTuneWasmEngine();
    this.logger.debug('WASM neural performance tuned.');
  }

  /**
   * Optimizes a neural network model for production inference speed.
   * @param {string} modelId The ID of the model to optimize.
   * @returns {Promise<void>}
   */
  public async optimizeModelForInference(modelId: string): Promise<void> {
    this.logger.info(`Optimizing model ${modelId} for inference speed (conceptual)...`);
    // This would involve techniques like model pruning, graph optimization, etc.
    await new Promise(resolve => setTimeout(resolve, 300));
    this.logger.debug(`Model ${modelId} optimized for inference.`);
  }

  /**
   * Optimizes batch processing for high-throughput scenarios.
   * @returns {Promise<void>}
   */
  public async optimizeBatchProcessing(): Promise<void> {
    this.logger.info('Optimizing neural network batch processing (conceptual)...');
    // This would involve using WasmPerformanceOptimizer to optimize batch processing.
    await this.wasmManager.optimizeBatchProcessing([]); // Pass empty array for simulation
    this.logger.debug('Neural network batch processing optimized.');
  }

  /**
   * Optimizes memory allocation for neural computations.
   * @returns {Promise<void>}
   */
  public async optimizeNeuralMemoryAllocation(): Promise<void> {
    this.logger.info('Optimizing neural memory allocation (conceptual)...');
    // This would involve using WasmPerformanceOptimizer to manage memory pools.
    await this.wasmManager.manageMemoryPools();
    this.logger.debug('Neural memory allocation optimized.');
  }

  /**
   * Enables GPU acceleration for neural computations (conceptual).
   * @returns {Promise<void>}
   */
  public async enableGpuAcceleration(): Promise<void> {
    this.logger.info('Enabling GPU acceleration for neural computations (conceptual)...');
    // This would involve configuring TensorFlow.js to use WebGL backend or similar.
    await new Promise(resolve => setTimeout(resolve, 100));
    this.logger.debug('GPU acceleration enabled.');
  }

  /**
   * Quantizes and compresses a neural network model for smaller size and faster inference (conceptual).
   * @param {string} modelId The ID of the model to quantize and compress.
   * @returns {Promise<void>}
   */
  public async quantizeAndCompressModel(modelId: string): Promise<void> {
    this.logger.info(`Quantizing and compressing model ${modelId} (conceptual)...`);
    // This would involve using TensorFlow.js converter or similar tools.
    await new Promise(resolve => setTimeout(resolve, 400));
    this.logger.debug(`Model ${modelId} quantized and compressed.`);
  }
}