pyFDN.TrainLog#

class pyFDN.TrainLog(train_loss=<factory>, loss_log=<factory>, steps_run=0, stopped_early=False)[source]#

Per-step loss history and stopping info from a training run.

Variables:

  • train_loss (list of float) – Total (weighted) loss at each step.

  • loss_log (dict of str to list of float) – Per-term loss history, keyed by each term’s name and stored unweighted, so terms stay comparable to their own scale.

  • steps_run (int) – Steps actually run.

  • stopped_early (bool) – Whether a plateau stopped it before max_steps.

__init__(train_loss=<factory>, loss_log=<factory>, steps_run=0, stopped_early=False)#

Methods

__init__([train_loss, loss_log, steps_run, ...])

Attributes

steps_run

stopped_early

train_loss

loss_log

loss_log: dict[str, list[float]]#
steps_run: int = 0#
stopped_early: bool = False#
train_loss: list[float]#