Source code for optuna.integration.mxnet

from __future__ import absolute_import

import optuna

try:
    import mxnet as mx  # NOQA
    _available = True
except ImportError as e:
    _import_error = e
    _available = False


[docs]class MXNetPruningCallback(object): """MXNet callback to prune unpromising trials. Example: Add a pruning callback which observes validation accuracy. .. code:: model.fit(train_data=X, eval_data=Y, eval_end_callback=MXNetPruningCallback(trial, eval_metric='accuracy')) Args: trial: A :class:`~optuna.trial.Trial` corresponding to the current evaluation of the objective function. eval_metric: An evaluation metric name for pruning, e.g., ``cross-entropy`` and ``accuracy``. 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 <https://mxnet.apache.org/api/python/metric/metric.html>`_ for further details. """ def __init__(self, trial, eval_metric): # type: (optuna.trial.Trial, str) -> None _check_mxnet_availability() self.trial = trial self.eval_metric = eval_metric def __call__(self, param): # type: (mx.model.BatchEndParams,) -> None if param.eval_metric is not None: metric_names, metric_values = param.eval_metric.get() if type(metric_names) == list and self.eval_metric in metric_names: current_score = metric_values[metric_names.index(self.eval_metric)] elif metric_names == self.eval_metric: current_score = metric_values else: raise ValueError('The entry associated with the metric name "{}" ' 'is not found in the evaluation result list {}.'.format( self.eval_metric, str(metric_names))) self.trial.report(current_score, step=param.epoch) if self.trial.should_prune(): message = "Trial was pruned at epoch {}.".format(param.epoch) raise optuna.exceptions.TrialPruned(message)
def _check_mxnet_availability(): # type: () -> None if not _available: raise ImportError( 'MXNet is not available. Please install MXNet to use this feature. ' 'MXNet can be installed by executing `$ pip install mxnet`. ' 'For further information, please refer to the installation guide of MXNet. ' '(The actual import error is as follows: ' + str(_import_error) + ')')