def print_meter()

in torchnet/logger/meterlogger.py [0:0]

• 24 lines of code
• 7 McCabe index (conditional complexity)

    def print_meter(self, mode, iepoch, ibatch=1, totalbatch=1, meterlist=None):
        pstr = "%s:\t[%d][%d/%d] \t"
        tval = []
        tval.extend([mode, iepoch, ibatch, totalbatch])
        if meterlist is None:
            meterlist = self.meter.keys()
            for meter in meterlist:
                if meter in ['confusion', 'histogram', 'image']:
                    continue
                if meter == 'accuracy':
                    pstr += "Acc@1 %.2f%% \t Acc@" + str(self.topk) + " %.2f%% \t"
                    tval.extend([self.meter[meter].value()[0], self.meter[meter].value()[1]])
                elif meter == 'map':
                    pstr += "mAP %.3f \t"
                    tval.extend([self.meter[meter].value()])
                elif meter == 'auc':
                    pstr += "AUC %.3f \t"
                    tval.extend([self.meter[meter].value()])
                else:
                    pstr += meter + " %.3f (%.3f)\t"
                    tval.extend([self.meter[meter].val, self.meter[meter].mean])
                    pstr += " %.2fs/its\t"
                    tval.extend([self.timer.value()])
        print(pstr % tuple(tval))