dmlcloud.TrainingHistory

class dmlcloud.TrainingHistory

Stores the training history of a model.

Metrics can either be ArrayLike objects or any pickleable object.

Usage:

history = TrainingHistory() history.append_metric(‘loss’, 0.5) history.append_metric(‘accuracy’, 0.99) history.next_step()

for metric in history:

print(f’{metric}’: history[metric])

__init__()

Methods

__init__()
append_metric(name, value)	Adds a value for a metric at the current step.
append_metrics(**metrics)	Adds multiple metrics at the current step.
items()
keys()
last()	Returns the last value for each metric.
max()	Returns a namedtuple (value, step) containing the maximum value and the corresponding step for each metric across all steps.
min()	Returns a namedtuple (value, step) containing the minimum value and the corresponding step for each metric across all steps.
rows()
values()