pytorch 視覺化
阿新 • • 發佈:2018-12-31
1.利用tnt
2.啟用visdon
python -m visdom.server -port 8097 &
3.加log就可以看了,比tensorboard感覺還簡單,雖然介面看起來還比較簡陋
port = 8097
train_loss_logger = VisdomPlotLogger(
'line', port=port, opts={'title': 'Train Loss'})
train_err_logger = VisdomPlotLogger(
'line', port=port, opts={'title' : 'Train Class Error'})
test_loss_logger = VisdomPlotLogger(
'line', port=port, opts={'title': 'Test Loss'})
test_err_logger = VisdomPlotLogger(
'line', port=port, opts={'title': 'Test Class Error'})
confusion_logger = VisdomLogger('heatmap', port=port, opts={'title': 'Confusion matrix' ,
'columnnames': list(range(10)),
'rownames': list(range(10))})
train_loss_logger.log(state['epoch'], meter_loss.value()[0])
train_err_logger.log(state['epoch' ], classerr.value()[0])
# do validation at the end of each epoch
reset_meters()
engine.test(h, get_iterator(False))
test_loss_logger.log(state['epoch'], meter_loss.value()[0])
test_err_logger.log(state['epoch'], classerr.value()[0])
confusion_logger.log(confusion_meter.value())
print('Testing loss: %.4f, accuracy: %.2f%%' % (meter_loss.value()[0], classerr.value()[0]))