def _setup_initial_blobs(self): self._update_rate_blob = self.model_id + "_update_rate" workspace.FeedBlob(self._update_rate_blob, np.array([1], dtype=np.float32)) self._retain_rate_blob = self.model_id + "_retain_rate" workspace.FeedBlob(self._retain_rate_blob, np.array([0], dtype=np.float32)) DNN._setup_initial_blobs(self)
def __init__(self, name: str, parameters: TrainingParameters) -> None: """ :param name: A unique name for this trainer used to create the data on the caffe2 workspace :param parameters: The set of training parameters """ self.optimizer = parameters.optimizer self.learning_rate = parameters.learning_rate self.lr_decay = parameters.lr_decay self.lr_policy = parameters.lr_policy DNN.__init__(self, name, parameters)
def __init__( self, name: str, parameters: TrainingParameters, target_update_rate: float, source_trainer: MLTrainer, ) -> None: self._target_update_rate = target_update_rate self.enabled_slow_updates = False DNN.__init__(self, name, parameters) self._setup_update_net(source_trainer) workspace.RunNetOnce(self._update_model.param_init_net) workspace.CreateNet(self._update_model.net)