How does one use tnt.meter.ConfusionMeter? It would be good if a snippet is available.

just used it a few minutes ago in a classifier network

```
confusion_matrix = meter.ConfusionMeter(2) #I have 2 classes here
for ii, data in enumerate(val_dataloader):
input, label = data
val_input = Variable(input, volatile=True).cuda()
val_label = Variable(label.type(t.LongTensor), volatile=True).cuda()
score = model(val_input)
confusion_matrix.add(score.data.squeeze(), label.type(t.LongTensor))
print confusion_matrix.conf
```

got something like:

```
[[1152, 434],
[764, 722]]
```

that is

```
[true negative, false postive]
[false negative,ture postive]
```

6 Likes

Thank you. I figured that I had to convert the Autograd `Variable`

back into a tensor for `ConfusionMeter`

to do the `.numpy()`

conversion to get it to work properly.

score and label are Autograd variables so

Confusion_matrix.add(score.data, label.data) will work