def __init__(monitor,
minimize=['loss'],
maximize=[],
smoothing=.6,
patience=None,
max_epoch=1000):
# Internal attributes
monitor._ewma = util.ExpMovingAve(alpha=1 - smoothing)
monitor._raw_metrics = []
monitor._smooth_metrics = []
monitor._epochs = []
monitor._is_good = []
# Bookkeeping
monitor._best_raw_metrics = None
monitor._best_smooth_metrics = None
monitor._best_epoch = None
monitor._n_bad_epochs = 0
# Keep track of which metrics we want to maximize / minimize
monitor.minimize = minimize
monitor.maximize = maximize
# early stopping
monitor.patience = patience
monitor.max_epoch = max_epoch
def __init__(monitor,
minimize=['loss'],
maximize=[],
smoothing=.6,
patience=None,
max_epoch=1000):
monitor.ewma = util.ExpMovingAve(alpha=1 - smoothing)
monitor.raw_metrics = []
monitor.smooth_metrics = []
monitor.epochs = []
monitor.is_good = []
# monitor.other_data = []
# Keep track of which metrics we want to maximize / minimize
monitor.minimize = minimize
monitor.maximize = maximize
# print('monitor.minimize = {!r}'.format(monitor.minimize))
# print('monitor.maximize = {!r}'.format(monitor.maximize))
monitor.best_raw_metrics = None
monitor.best_smooth_metrics = None
monitor.best_epoch = None
# early stopping
monitor.patience = patience
monitor.n_bad_epochs = 0
monitor.max_epoch = max_epoch
def __setstate__(monitor, state):
ewma_state = state.pop('ewma_state', None)
if ewma_state is not None:
monitor._ewma = util.ExpMovingAve()
monitor._ewma.__dict__.update(ewma_state)
monitor.__dict__.update(**state)