          dropouts = dict(fc=self.config["fc_dropout"],
                          gblock=self.config["fc_gblock_dropout"])
          logger.debug("Config dropouts: %s", dropouts)
          updated = False
          for mod in _get_all_sub_models(model):
              if not mod.name.startswith("fc_"):
                  continue
              key = "gblock" if "gblock" in mod.name else mod.name.split("_")[0]
              rate = dropouts[key]
              log_once = False
 
</s> remove         assert output.dtype == "float32" and not np.isnan(output)
 </s> add         assert output.dtype == "float32" and not np.any(np.isnan(output)) </s> remove         assert output.dtype == "float32" and not np.isnan(output)
 </s> add         assert output.dtype == "float32" and not np.any(np.isnan(output)) </s> remove from ._base import KerasModel, ModelBase, logger, _get_all_sub_models
 </s> add from ._base import KerasModel, ModelBase, get_all_sub_models

logger = logging.getLogger(__name__)  # pylint: disable=invalid-name

        for mod in get_all_sub_models(model):
          dropouts = dict(fc=self.config["fc_dropout"],
                          gblock=self.config["fc_gblock_dropout"])
          logger.debug("Config dropouts: %s", dropouts)
          updated = False
        for mod in get_all_sub_models(model):
              if not mod.name.startswith("fc_"):
                  continue
              key = "gblock" if "gblock" in mod.name else mod.name.split("_")[0]
              rate = dropouts[key]
              log_once = False
keep keep keep keep replace keep keep keep keep keep
 Refactoring and TravisCI to Github Actions (#1239)

* refactor training

* travis to actions 
plugins/train/model/phaze_a.py