Update discriminator option

hypernets/experiment/_maker.py

@@ -206,8 +206,8 @@ def make_experiment(hyper_model_cls,
             - nf
     optimize_direction : str, optional
         Hypernets search reward metric direction, default is detected from reward_metric.
-    discriminator : instance of hypernets.discriminator.BaseDiscriminator, optional
-        Discriminator is used to determine whether to continue training
+    discriminator : instance of hypernets.discriminator.BaseDiscriminator or bool, optional
+        Discriminator is used to determine whether to continue training, set False to disable it.
     hyper_model_options: dict, optional
         Options to initlize HyperModel except *reward_metric*, *task*, *callbacks*, *discriminator*.
     evaluation_metrics: str, list, or None (default='auto'),
@@ -365,10 +365,14 @@ def append_early_stopping_callbacks(cbs):
         report_render = to_report_render_object(report_render, report_render_options)
         callbacks.append(MLReportCallback(report_render))
 
-    if discriminator is None and cfg.experiment_discriminator is not None and len(cfg.experiment_discriminator) > 0:
+    if ((discriminator is None or discriminator is True)
+            and cfg.experiment_discriminator is not None
+            and len(cfg.experiment_discriminator) > 0):
         discriminator = make_discriminator(cfg.experiment_discriminator,
                                            optimize_direction=optimize_direction,
                                            **(cfg.experiment_discriminator_options or {}))
+    elif discriminator is False:
+        discriminator = None
 
     if id is None:
         hasher = tb.data_hasher()