setup_visdom_logging#
- ignite.handlers.logger_utils.setup_visdom_logging(trainer, optimizers=None, evaluators=None, log_every_iters=100, **kwargs)[source]#
Method to setup Visdom logging on trainer and a list of evaluators. Logged metrics are:
Training metrics, e.g. running average loss values
Learning rate(s)
Evaluation metrics
Warning
This function uses VisdomLogger which is currently untested due to the visdom package being unmaintained and difficult to install with modern Python packages. Use at your own risk.
- Parameters:
trainer (Engine) – trainer engine
optimizers (Optimizer | dict[str, torch.optim.optimizer.Optimizer] | None) – single or dictionary of torch optimizers. If a dictionary, keys are used as tags arguments for logging.
evaluators (Engine | dict[str, ignite.engine.engine.Engine] | None) – single or dictionary of evaluators. If a dictionary, keys are used as tags arguments for logging.
log_every_iters (int) – interval for loggers attached to iteration events. To log every iteration, value can be set to 1 or None.
kwargs (Any) – optional keyword args to be passed to construct the logger.
- Returns:
- Return type: