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)