gluonts.nursery.tsbench.src.tsbench.gluonts.callbacks.save module#

class gluonts.nursery.tsbench.src.tsbench.gluonts.callbacks.save.ModelSaverCallback(directory: pathlib.Path, milestones: List[float])[source]#

Bases: gluonts.nursery.tsbench.src.tsbench.gluonts.callbacks.base.Callback

The model saver callback saves the model during training at exponential frequency.

network#: The network that was trained. Not available prior to training.

saved_parameters#: The parameters saved for the different milestones. Should only be accessed after training has finished and should not be modified.

training_times#: The training times in seconds for the different milestones.

num_gradient_updates#: The number of gradient updates for the different milestones.

on_network_initialization_end(network: mxnet.gluon.block.HybridBlock) → None[source]#: Hook called once the network is initialized.

on_train_batch_end(network: mxnet.gluon.block.HybridBlock, time_elapsed: float) → None[source]#: Hook called after every training batch.

on_train_start(trainer: mxnet.gluon.trainer.Trainer) → None[source]#: Hook called before training is run.