evolvepy.integrations.wandb package

Submodules

evolvepy.integrations.wandb.wandb module

class evolvepy.integrations.wandb.wandb.WandbLogger(name: str | None = None, project: str | None = None, entity: str | None = None, group: str | None = None, log_fitness: bool = True, log_generator: bool = True, log_evaluator: bool = True, log_scores: bool = False)[source]

Bases: Logger

Logger class to log data to “Weights & Biases”.

__init__(name: str | None = None, project: str | None = None, entity: str | None = None, group: str | None = None, log_fitness: bool = True, log_generator: bool = True, log_evaluator: bool = True, log_scores: bool = False)[source]

WandbLogger constructor.

Parameters:

  • name (str, optional) – Run name. Defaults to None (wandb autogenerated name).

  • project (str, optional) – Wandb run name. Defaults to None.

  • entity (str, optional) – Wandb entity name. Defaults to None.

  • group (str, optional) – Run group name. Defaults to None.

  • log_fitness (bool, optional) – Whether it should log the fitness of all individuals of each generation. Defaults to True.

  • log_generator (bool, optional) – Whether it should log the generator dynamic parameters. Defaults to True.

  • log_evaluator (bool, optional) – Whether it should log the evaluator dynamic parameters. Defaults to True.

  • log_scores (bool, optional) – Whether it should log all the evaluator individual scores. Defaults to False.

on_stop() → None[source]

Stops wandb run.

save_dynamic_log(log: Dict[str, Dict]) → None[source]

Saves dynamic log between generations.

Parameters:

log (Dict[str, Dict]) – Dynamic log to save.

save_static_log(log: Dict[str, Dict]) → None[source]

Saves static log. It should only be called at the beginning of the log (does nothing otherwise).

Parameters:

log (Dict[str, Dict]) – Static log to save.

Module contents

Integration with “Weights & Biases” (https://wandb.ai/site)