pytorch中计算准确率，召回率和F1值的方法

predict = output.argmax(dim = 1)
confusion_matrix =torch.zeros(2,2)
for t, p in zip(predict.view(-1), target.view(-1)):
    confusion_matrix[t.long(), p.long()] += 1
a_p =(confusion_matrix.diag() / confusion_matrix.sum(1))[0]
b_p = (confusion_matrix.diag() / confusion_matrix.sum(1))[1]
a_r =(confusion_matrix.diag() / confusion_matrix.sum(0))[0]
b_r = (confusion_matrix.diag() / confusion_matrix.sum(0))[1]