ray.tune.logger.TBXLoggerCallback
ray.tune.logger.TBXLoggerCallback#
- class ray.tune.logger.TBXLoggerCallback[source]#
Bases:
ray.tune.logger.logger.LoggerCallbackTensorBoardX Logger.
Note that hparams will be written only after a trial has terminated. This logger automatically flattens nested dicts to show on TensorBoard:
{“a”: {“b”: 1, “c”: 2}} -> {“a/b”: 1, “a/c”: 2}
PublicAPI: This API is stable across Ray releases.
Methods
Get the state of the callback.
log_trial_restore(trial)Handle logging when a trial restores.
log_trial_save(trial)Handle logging when a trial saves a checkpoint.
on_checkpoint(iteration, trials, trial, ...)Called after a trial saved a checkpoint with Tune.
on_experiment_end(trials, **info)Called after experiment is over and all trials have concluded.
on_step_begin(iteration, trials, **info)Called at the start of each tuning loop step.
on_step_end(iteration, trials, **info)Called at the end of each tuning loop step.
on_trial_recover(iteration, trials, trial, ...)Called after a trial instance failed (errored) but the trial is scheduled for retry.
set_state(state)Set the state of the callback.
setup([stop, num_samples, total_num_samples])Called once at the very beginning of training.
Attributes