input_ff_rec_learnoutput_nengo_ocl.py 文件源码

def sim_run_flush(tFlush,nFlush):
        '''
            Run simulation for nFlush*tFlush seconds,
            Flush probes every tFlush of simulation time,
              (only flush those that don't have 'weights' in their label names)
        '''        
        weighttimeidxold = 0
        #doubledLearningRate = False
        for duration in [tFlush]*nFlush:
            _,_,_,_,realtime = os.times()
            print("Finished till",sim.time,'s, in',realtime-realtimeold,'s')
            sys.stdout.flush()
            # save weights if weightdt or more has passed since last save
            weighttimeidx = int(sim.time/weightdt)
            if weighttimeidx > weighttimeidxold:
                weighttimeidxold = weighttimeidx
                save_current_weights(False,sim.time)
            # flush probes
            for probe in sim.model.probes:
                # except weight probes (flushed in save_current_weights)
                # except error probe which is saved fully in ..._end.shelve
                if probe.label is not None:
                    if 'weights' in probe.label or 'error' in probe.label:
                        break
                del sim._probe_outputs[probe][:]
            ## if time > 1000s, double learning rate
            #if sim.time>1000. and not doubledLearningRate:
            #    changeLearningRate(4.)  # works only if excPESDecayRate = None
            #    doubledLearningRate = True
            # run simulation for tFlush duration
            sim.run(duration,progress_bar=False)

    ###
    ### run the simulation, with flushing for learning simulations ###
    ###