optuna.integration.MXNetPruningCallback
- class optuna.integration.MXNetPruningCallback(trial, eval_metric)[source]
MXNet callback to prune unpromising trials.
See the example if you want to add a pruning callback which observes accuracy.
- Parameters:
trial (Trial) – A
Trial
corresponding to the current evaluation of the objective function.eval_metric (str) – An evaluation metric name for pruning, e.g.,
cross-entropy
andaccuracy
. If using default metrics like mxnet.metrics.Accuracy, use it’s default metric name. For custom metrics, use the metric_name provided to constructor. Please refer to mxnet.metrics reference for further details.