2017.9.21.py 文件源码

def prog(self):#Show progress
        nb_batches_total=(self.params['nb_epoch'] if not kv-1 else self.params['epochs'])*self.params['nb_sample']/self.params['batch_size']
        nb_batches_epoch=self.params['nb_sample']/self.params['batch_size']
        prog_total=(self.t_batches/nb_batches_total if nb_batches_total else 0)+0.01
        prog_epoch=(self.c_batches/nb_batches_epoch if nb_batches_epoch else 0)+0.01
        if self.t_epochs:
            now=time.time()
            t_mean=float(sum(self.t_epochs)) / len(self.t_epochs)
            eta_t=(now-self.train_start)*((1/prog_total)-1)
            eta_e=t_mean*(1-prog_epoch)
            t_end=time.asctime(time.localtime(now+eta_t))
            e_end=time.asctime(time.localtime(now+eta_e))
            m='\nTotal:\nProg:'+str(prog_total*100.)[:5]+'%\nEpoch:'+str(self.epoch[-1])+'/'+str(self.stopped_epoch)+'\nETA:'+str(eta_t)[:8]+'sec\nTrain will be finished at '+t_end+'\nCurrent epoch:\nPROG:'+str(prog_epoch*100.)[:5]+'%\nETA:'+str(eta_e)[:8]+'sec\nCurrent epoch will be finished at '+e_end
            self.t_send(m)
            print(m)
        else:
            now=time.time()
            eta_t=(now-self.train_start)*((1/prog_total)-1)
            eta_e=(now-self.train_start)*((1/prog_epoch)-1)
            t_end=time.asctime(time.localtime(now+eta_t))
            e_end=time.asctime(time.localtime(now+eta_e))
            m='\nTotal:\nProg:'+str(prog_total*100.)[:5]+'%\nEpoch:'+str(len(self.epoch))+'/'+str(self.stopped_epoch)+'\nETA:'+str(eta_t)[:8]+'sec\nTrain will be finished at '+t_end+'\nCurrent epoch:\nPROG:'+str(prog_epoch*100.)[:5]+'%\nETA:'+str(eta_e)[:8]+'sec\nCurrent epoch will be finished at '+e_end
            self.t_send(m)
            print(m)