""" Main pipeline runner for temporal reasoning audio dataset generation. This script orchestrates the generation of all task datasets. """ import argparse import sys import yaml from pathlib import Path from typing import List, Optional # Add project root to path sys.path.append(str(Path(__file__).parent)) from utils import setup_logger, set_random_seed from tasks.task_count import CountTaskGenerator from tasks.task_duration import DurationTaskGenerator from tasks.task_order import OrderTaskGenerator from tasks.task_volume import VolumeTaskGenerator def load_config(config_path: str) -> dict: """Load configuration from YAML file.""" with open(config_path, 'r') as f: config = yaml.safe_load(f) return config def run_count_task(config: dict, logger): """Run the count task generation.""" if not config['tasks']['count']['enabled']: logger.info("Count task is disabled, skipping...") return logger.info("=" * 80) logger.info("STARTING COUNT TASK GENERATION") logger.info("=" * 80) generator = CountTaskGenerator(config, logger) generator.dataset.reset_category_usage() # Reset counter for this task generator.generate_dataset() # Log category usage statistics usage_stats = generator.dataset.get_category_usage_stats() sorted_stats = sorted(usage_stats.items(), key=lambda x: x[1], reverse=True) logger.info("Category usage statistics (as answers):") logger.info(f" Min usage: {sorted_stats[-1][1]} (category: {sorted_stats[-1][0]})") logger.info(f" Max usage: {sorted_stats[0][1]} (category: {sorted_stats[0][0]})") logger.info(f" Mean usage: {sum(usage_stats.values()) / len(usage_stats):.2f}") logger.info("Count task completed successfully!") def run_duration_task(config: dict, logger): """Run the duration task generation.""" if not config['tasks']['duration']['enabled']: logger.info("Duration task is disabled, skipping...") return logger.info("=" * 80) logger.info("STARTING DURATION TASK GENERATION") logger.info("=" * 80) generator = DurationTaskGenerator(config, logger) generator.dataset.reset_category_usage() # Reset counter for this task generator.generate_dataset() # Log category usage statistics usage_stats = generator.dataset.get_category_usage_stats() sorted_stats = sorted(usage_stats.items(), key=lambda x: x[1], reverse=True) logger.info("Category usage statistics (as longest/shortest answers):") logger.info(f" Min usage: {sorted_stats[-1][1]} (category: {sorted_stats[-1][0]})") logger.info(f" Max usage: {sorted_stats[0][1]} (category: {sorted_stats[0][0]})") logger.info(f" Mean usage: {sum(usage_stats.values()) / len(usage_stats):.2f}") logger.info("Duration task completed successfully!") def run_order_task(config: dict, logger): """Run the order task generation.""" if not config['tasks']['order']['enabled']: logger.info("Order task is disabled, skipping...") return logger.info("=" * 80) logger.info("STARTING ORDER TASK GENERATION") logger.info("=" * 80) generator = OrderTaskGenerator(config, logger) generator.dataset.reset_category_usage() # Reset counter for this task generator.generate_dataset() # Log category usage statistics usage_stats = generator.dataset.get_category_usage_stats() sorted_stats = sorted(usage_stats.items(), key=lambda x: x[1], reverse=True) logger.info("Category usage statistics (as first/last/after/before answers):") logger.info(f" Min usage: {sorted_stats[-1][1]} (category: {sorted_stats[-1][0]})") logger.info(f" Max usage: {sorted_stats[0][1]} (category: {sorted_stats[0][0]})") logger.info(f" Mean usage: {sum(usage_stats.values()) / len(usage_stats):.2f}") logger.info("Order task completed successfully!") def run_volume_task(config: dict, logger): """Run the volume task generation.""" if not config['tasks']['volume']['enabled']: logger.info("Volume task is disabled, skipping...") return logger.info("=" * 80) logger.info("STARTING VOLUME TASK GENERATION") logger.info("=" * 80) generator = VolumeTaskGenerator(config, logger) generator.dataset.reset_category_usage() # Reset counter for this task generator.generate_dataset() # Log category usage statistics usage_stats = generator.dataset.get_category_usage_stats() sorted_stats = sorted(usage_stats.items(), key=lambda x: x[1], reverse=True) logger.info("Category usage statistics (as loudest/softest answers):") logger.info(f" Min usage: {sorted_stats[-1][1]} (category: {sorted_stats[-1][0]})") logger.info(f" Max usage: {sorted_stats[0][1]} (category: {sorted_stats[0][0]})") logger.info(f" Mean usage: {sum(usage_stats.values()) / len(usage_stats):.2f}") logger.info("Volume task completed successfully!") def run_pipeline( config_path: str, tasks: Optional[List[str]] = None, output_path: Optional[str] = None ): """ Run the complete dataset generation pipeline. Args: config_path: Path to configuration YAML file tasks: Optional list of specific tasks to run (default: all enabled tasks) output_path: Optional custom output path (overrides config) """ # Load configuration config = load_config(config_path) # Override output path if provided if output_path: config['output']['base_path'] = output_path # Create output directory output_base = Path(config['output']['base_path']) output_base.mkdir(parents=True, exist_ok=True) # Set random seed set_random_seed(config['random_seed']) # Setup main logger logger = setup_logger( 'pipeline', log_file=str(output_base / config['logging']['log_file']), level=config['logging']['level'], console_output=config['logging']['console_output'] ) logger.info("=" * 80) logger.info("TEMPORAL REASONING AUDIO DATASET GENERATION PIPELINE") logger.info("=" * 80) logger.info(f"Configuration: {config_path}") logger.info(f"Output directory: {output_base}") logger.info(f"Random seed: {config['random_seed']}") logger.info(f"ESC-50 audio path: {config['esc50']['audio_path']}") logger.info(f"ESC-50 metadata path: {config['esc50']['metadata_path']}") # Determine which tasks to run task_map = { 'count': run_count_task, 'duration': run_duration_task, 'order': run_order_task, 'volume': run_volume_task } if tasks: tasks_to_run = {k: v for k, v in task_map.items() if k in tasks} logger.info(f"Running specific tasks: {', '.join(tasks)}") else: tasks_to_run = task_map logger.info("Running all enabled tasks") # Run tasks for task_name, task_func in tasks_to_run.items(): try: task_func(config, logger) except Exception as e: logger.error(f"Error running {task_name} task: {e}", exc_info=True) raise logger.info("=" * 80) logger.info("PIPELINE COMPLETED SUCCESSFULLY!") logger.info("=" * 80) logger.info(f"All outputs saved to: {output_base}") def main(): """Main entry point with argument parsing.""" parser = argparse.ArgumentParser( description="Temporal Reasoning Audio Dataset Generation Pipeline", formatter_class=argparse.RawDescriptionHelpFormatter, epilog=""" Examples: # Run all tasks with default config python main.py # Run with custom config python main.py --config my_config.yaml # Run specific tasks only python main.py --tasks count duration # Use custom output directory python main.py --output /path/to/output # Combine options python main.py --config custom.yaml --tasks count order --output ./my_dataset """ ) parser.add_argument( '--config', '-c', type=str, default='config.yaml', help='Path to configuration YAML file (default: config.yaml)' ) parser.add_argument( '--tasks', '-t', nargs='+', choices=['count', 'duration', 'order', 'volume'], help='Specific tasks to run (default: all enabled tasks)' ) parser.add_argument( '--output', '-o', type=str, help='Custom output directory (overrides config)' ) args = parser.parse_args() # Check if config file exists config_path = Path(args.config) if not config_path.exists(): # Try relative to script directory script_dir = Path(__file__).parent config_path = script_dir / args.config if not config_path.exists(): print(f"Error: Config file not found: {args.config}") sys.exit(1) # Run pipeline try: run_pipeline( config_path=str(config_path), tasks=args.tasks, output_path=args.output ) except Exception as e: print(f"Pipeline failed with error: {e}") sys.exit(1) if __name__ == '__main__': main()