| from typing import List |
|
|
| from utils.early_stopping import EarlyStoppingCallback |
| from utils.tensorboard import TensorboardLoggerCallback |
|
|
|
|
| def setup_callbacks(ckpt_path: str, |
| log_dir: str, |
| early_patience: int, |
| early_monitor: str = "val_loss", |
| early_mode: str = "min", |
| use_tensorboard: bool = False, |
| **kwargs) -> List[object]: |
|
|
| delta = kwargs.get("delta", 0) |
| verbose = kwargs.get("verbose", True) |
| restore_best_weights = kwargs.get("restore_best_weights", False) |
| save_final_model = kwargs.get("save_final_model", True) |
|
|
| es_call = EarlyStoppingCallback(patience=early_patience, |
| delta=delta, |
| checkpoint_path=ckpt_path, |
| verbose=verbose, |
| restore_best_weights=restore_best_weights, |
| monitor=early_monitor, |
| mode=early_mode, |
| save_final_model=save_final_model |
| ) |
|
|
| log_histograms = kwargs.get("log_histograms", False) |
| log_images_every = kwargs.get("log_images_every", 10) |
| tb_port = kwargs.get("tb_port", 6006) |
| tb_browser = kwargs.get("tb_browser", False) |
|
|
| tb_logger = TensorboardLoggerCallback(log_dir=log_dir, |
| log_histograms=log_histograms, |
| launch_tb=use_tensorboard, |
| tb_port=tb_port, |
| open_tb_in_browser=tb_browser |
| ) |
| return [es_call, tb_logger] |
