pytorch 可视化

1.利用tnt

https://github.com/pytorch/tnt/blob/master/example/mnist_with_visdom.py#L9

2.启用visdon

python -m visdom.server -port 8097 &

3.加log就可以看了，比tensorboard感觉还简单，虽然界面看起来还比较简陋

    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]))