shamboflow.callbacks.ModelCheckpoint

class documentation

class ModelCheckpoint(BaseCallback): (source)

Constructor: ModelCheckpoint(save_path, monitor, save_best_only, verbose, ...)

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Model Checkpointing

This callback function monitors a metric and saves the instance of model to disk at every epoch or on a condition

Method __init__ Initialize
Method run The callback method that will be called after each epoch
Instance Variable _metric_old Undocumented
Instance Variable _monitor Undocumented
Instance Variable _save_best Undocumented
Instance Variable _save_path Undocumented
Instance Variable _verbose Undocumented
def __init__(self, save_path: str = 'model.ckpt', monitor: str = 'loss', save_best_only: bool = True, verbose: bool = False, **kwargs): (source)
overrides shamboflow.engine.base_callback.BaseCallback.__init__

Initialize

Args
save_path:
Save path for the model
monitor:
The metric to monitor. It is one of the 4: loss, acc, val_loss, val_acc
save_best_only:
whether to save only the best model according to the monitor
verbose:
Log callback function logs
def run(self, model: BaseModel): (source)
overrides shamboflow.engine.base_callback.BaseCallback.run

The callback method that will be called after each epoch

Args
model: The model on which callback wil be called
_metric_old = (source)

Undocumented

_monitor = (source)

Undocumented

_save_best = (source)

Undocumented

_save_path = (source)

Undocumented

_verbose = (source)

Undocumented