1. 程式人生 > >pytorch 視覺化

pytorch 視覺化

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]))