Bump 0.3.2

hypernets/__init__.py

@@ -1,3 +1,3 @@
 # -*- coding:utf-8 -*-
 __author__ = 'yangjian'
-__version__ = '0.3.1'
+__version__ = '0.3.2'

hypernets/experiment/_maker.py

@@ -51,8 +51,7 @@ def to_objective_object(o, force_minimize=False, **kwargs):
 
 
 def to_search_object(search_space, optimize_direction, searcher, searcher_options,
- reward_metric=None, scorer=None, objectives=None, task=None, pos_label=None):
-
+ reward_metric=None, scorer=None, objectives=None, task=None, pos_label=None):
  def to_searcher(cls, options):
  assert search_space is not None, '"search_space" should be specified if "searcher" is None or str.'
  assert optimize_direction in {'max', 'min'}
@@ -352,7 +351,7 @@ def append_early_stopping_callbacks(cbs):
 
  if eval_data is not None:
  from hypernets.experiment import MLEvaluateCallback
- if task in [const.TASK_REGRESSION, const.TASK_BINARY, const.TASK_MULTICLASS]\
+ if task in [const.TASK_REGRESSION, const.TASK_BINARY, const.TASK_MULTICLASS] \
  and searcher.kind() == const.SEARCHER_SOO:
  if evaluation_persist_prediction is True:
  persist_dir = evaluation_persist_prediction_dir
@@ -371,7 +370,7 @@ def append_early_stopping_callbacks(cbs):
  discriminator = make_discriminator(cfg.experiment_discriminator,
  optimize_direction=optimize_direction,
  **(cfg.experiment_discriminator_options or {}))
- elif discriminator is False:
+ elif isinstance(discriminator, bool):
  discriminator = None
 
  if id is None: