Here is actually where i wanna get the individual class precisions :
def test(epoch):
    model.eval()
    test_loss = AverageMeter()
    acc = AverageMeter()
    for data, target in test_loader:
        if use_cuda:
            data, target = data.cuda(), target.cuda()
        data, target = Variable(data, volatile=True), Variable(target)
        data = data.float()
        output = model(data)
        entr = F.cross_entropy(output, torch.max(target, 1)[0], size_average=True).data[0]
        test_loss.update(entr,target.data.size(0))
        prec1, = accuracy(output.data[i], target.data[i]) # test precison in one batch
        acc.update(prec1, target.data.size(0))
    print('\nTest set: Average loss: {:.4f}, Accuracy: {:.2f}%\n'.format(test_loss.avg, acc.avg))
    writer.add_scalar('Loss/Test', test_loss.avg, epoch)
    writer.add_scalar('Accuracy/Test', acc.avg, epoch)
    return acc.avg


Want to have something like this :
class 1 92% 
class 2 93%
....
class i  xx%