IO

torch_load_checkpoint

load_checkpoint(file, **kwargs)

Loads a saved model

Parameters:

• file (str) – filepath to a file containing a saved model
• **kwargs – Additional keyword arguments (passed to torch.load) Especially “map_location” is important to change the device the state_dict should be loaded to

Returns:

checkpoint state_dict

Return type:

OrderedDict

torch_save_checkpoint

save_checkpoint(file: str, model=None, optimizers={}, epoch=None, **kwargs)

Save model’s parameters

Parameters:

• file (str) – filepath the model should be saved to
• model (AbstractNetwork or None) – the model which should be saved if None: empty dict will be saved as state dict
• optimizers (dict) – dictionary containing all optimizers
• epoch (int) – current epoch (will also be pickled)

tf_load_checkpoint

load_checkpoint(file: str, model=None)

Loads a saved model

Parameters:

• file (str) – filepath to a file containing a saved model
• model (TfNetwork) – the model which should be loaded

tf_save_checkpoint

save_checkpoint(file: str, model=None)

Save model’s parameters contained in it’s graph

Parameters:

• file (str) – filepath the model should be saved to
• model (TfNetwork) – the model which should be saved