def model(self):
if self._wrapped_model is None:
if self.args['distributed_training']['distributed_world_size'] > 1 and \
not self.args['optimization']['use_bmuf']:
self._wrapped_model = models.DistributedNccModel(self.args, self._model)
else:
self._wrapped_model = self._model
return self._wrapped_model
def criterion(self):
if self._wrapped_criterion is None:
if (utils.has_parameters(self._criterion) and
self.args['distributed_training']['distributed_world_size']
> 1 and not self.args['optimization']['use_bmuf']):
self._wrapped_criterion = models.DistributedNccModel(
self.args, self._criterion)
else:
self._wrapped_criterion = self._criterion
return self._wrapped_criterion