| """ |
| Logging utilities for enterprise-grade monitoring |
| """ |
|
|
| import logging |
| import sys |
| from pathlib import Path |
| from datetime import datetime |
| import json |
|
|
| def setup_logger(name: str, log_file: str = None, level=logging.INFO): |
| """Setup logger with file and console handlers""" |
| |
| |
| logger = logging.getLogger(name) |
| logger.setLevel(level) |
| logger.handlers.clear() |
| |
| |
| file_formatter = logging.Formatter( |
| '%(asctime)s - %(name)s - %(levelname)s - %(message)s' |
| ) |
| console_formatter = logging.Formatter( |
| '%(levelname)s - %(message)s' |
| ) |
| |
| |
| if log_file: |
| log_path = Path(log_file) |
| log_path.parent.mkdir(parents=True, exist_ok=True) |
| file_handler = logging.FileHandler(log_file, encoding='utf-8') |
| file_handler.setLevel(level) |
| file_handler.setFormatter(file_formatter) |
| logger.addHandler(file_handler) |
| |
| |
| console_handler = logging.StreamHandler(sys.stdout) |
| console_handler.setLevel(logging.INFO) |
| console_handler.setFormatter(console_formatter) |
| logger.addHandler(console_handler) |
| |
| return logger |
|
|
|
|
|
|
| def log_metrics(metrics_dict, logger_name="default", level="INFO"): |
| """ |
| Log metrics dictionary |
| |
| Args: |
| metrics_dict: Dictionary of metrics to log |
| logger_name: Name of logger |
| level: Log level |
| """ |
| logger = setup_logger(logger_name) |
| |
| if level.upper() == "INFO": |
| log_func = logger.info |
| elif level.upper() == "WARNING": |
| log_func = logger.warning |
| elif level.upper() == "ERROR": |
| log_func = logger.error |
| else: |
| log_func = logger.info |
| |
| |
| metrics_str = ", ".join([f"{k}: {v}" for k, v in metrics_dict.items()]) |
| log_func(f"METRICS: {metrics_str}") |
|
|
| class TrainingLogger: |
| """Structured logger for training metrics""" |
| |
| def __init__(self, log_dir="reports/logs"): |
| self.log_dir = Path(log_dir) |
| self.log_dir.mkdir(parents=True, exist_ok=True) |
| |
| self.metrics_file = self.log_dir / "training_metrics.json" |
| self.metrics = [] |
| |
| def log_epoch(self, epoch: int, train_metrics: dict, val_metrics: dict): |
| """Log epoch metrics""" |
| |
| epoch_log = { |
| 'epoch': epoch, |
| 'timestamp': str(datetime.now()), |
| 'train': train_metrics, |
| 'validation': val_metrics |
| } |
| |
| self.metrics.append(epoch_log) |
| |
| |
| with open(self.metrics_file, 'w', encoding='utf-8') as f: |
| json.dump(self.metrics, f, indent=2) |
| |
| def log_training_end(self, final_metrics: dict): |
| """Log final training results""" |
| |
| summary = { |
| 'training_completed': str(datetime.now()), |
| 'final_metrics': final_metrics, |
| 'total_epochs': len(self.metrics) |
| } |
| |
| summary_file = self.log_dir / "training_summary.json" |
| with open(summary_file, 'w', encoding='utf-8') as f: |
| json.dump(summary, f, indent=2) |
|
|