def plot_epoch_current_valid_errors(self, epoch, errors):
if not hasattr(self, 'epoch_plot_data_valid'):
self.epoch_plot_data_valid = {'X': [], 'Y': [], 'legend': 'test'}
self.epoch_plot_data_valid['X'].append(epoch)
self.epoch_plot_data_valid['Y'].append(util.tensor2float(errors))
self.vis.line(X=np.array(self.epoch_plot_data_valid['X']),
Y=np.array(self.epoch_plot_data_valid['Y']),
opts={
'title': ' validing epoch mean loss over time',
'xlabel': 'epoch',
'ylabel': 'loss'
},
win=4)
def plot_current_errors(self, epoch, counter_ratio, errors):
if not hasattr(self, 'plot_data'):
self.plot_data = {'X': [], 'Y': [], 'legend': 'test'}
self.plot_data['X'].append(epoch + counter_ratio)
self.plot_data['Y'].append(util.tensor2float(errors))
self.vis.line(X=np.array(self.plot_data['X']),
Y=np.array(self.plot_data['Y']),
opts={
'title': ' training loss over time',
'xlabel': 'epoch',
'ylabel': 'loss'
},
win=1)