SideEffects#

class t3w.TqdmSideEffect(postfix_keys: Sequence[str] = [], smoothing: float = 0.9)#
__init__(postfix_keys: Sequence[str] = [], smoothing: float = 0.9) → None#

show a tqdm progress bar for training and evaluation, write eval metrics at the end of eval epoch.

Parameters:

  • postfix_keys (Sequence[str], optional) – control the losses and metrics to be displayed on the bar. Empty sequence will show all.

  • smoothing (float, optional) – low pass filter value. Defaults to 0.9.

on_eval_started(loop: EvalLoop)#
on_eval_step_finished(loop: EvalLoop, step: int, mb: IMiniBatch)#
on_eval_finished(loop: EvalLoop)#
on_train_started(loop: TrainLoop)#
on_train_epoch_started(loop: TrainLoop, epoch: int)#
on_train_step_finished(loop: TrainLoop, step: int, mb: IMiniBatch, step_return: StepReturnDict)#
on_train_epoch_finished(loop: TrainLoop, epoch: int)#
on_train_finished(loop: TrainLoop)#
class t3w.AimSideEffect(experiment: str, hparams_dict: Dict[str, Any], run_hash: str | None = None, description: str | None = None, repo: str | Path = './', track_weights_every_n_steps: int | None = None)#
__init__(experiment: str, hparams_dict: Dict[str, Any], run_hash: str | None = None, description: str | None = None, repo: str | Path = './', track_weights_every_n_steps: int | None = None) → None#
on_eval_started(loop: EvalLoop)#
on_train_started(loop: TrainLoop)#
on_eval_finished(loop: EvalLoop)#
on_train_step_finished(loop: TrainLoop, step: int, mb: IMiniBatch, step_return: StepReturnDict)#
on_eval_step_finished(loop: EvalLoop, step: int, mb: IMiniBatch)#
handle_medias(step: int, media_cache: Sequence[MediaData])#
class t3w.SaveBestModelsSideEffect(metric_name: str, num_max_keep: int, save_path_prefix: str = './')#
__init__(metric_name: str, num_max_keep: int, save_path_prefix: str = './') → None#
on_train_started(loop: TrainLoop)#
on_eval_finished(loop: EvalLoop)#