def display_progress(self, iter_, train_losses, val_losses):
print("Iteration {} of {}".format(iter_, self.iterations))
print(" training loss = {:.6f}".format(train_losses[-1]))
print(" validation loss = {:.6f}".format(val_losses[-1]))
if self.plot and iter_ % self.plot == 0:
plotUtil.plotTwoCurves(range(len(train_losses)), train_losses,
range(len(val_losses)), val_losses,
label1='training loss',
label2='validation loss', showLegend=True,
figureIdx=2,
figureTitle="%s: Training and Validation Loss" % self.__class__.__name__)
def display_progress(self, iter_, train_losses, val_losses):
print("Iteration {} of {}".format(iter_, self.iterations))
print(" training loss = {:.6f}".format(train_losses[-1]))
print(" validation loss = {:.6f}".format(val_losses[-1]))
if self.plot and iter_ % self.plot == 0:
plotUtil.plotTwoCurves(range(len(train_losses)), train_losses,
range(len(val_losses)), val_losses,
label1='training loss',
label2='validation loss', showLegend=True,
figureIdx=2,
figureTitle="%s: Training and Validation Loss" % self.__class__.__name__)
