当尝试使用以下函数计算两个张量rPPG = (shape(torch.Size([4, 128]))
和BVP_label = (shape(torch.Size([4, 128])))
之间的损失时:
class Neg_Pearson(nn.Module): # Pearson range [-1, 1] so if < 0, abs|loss| ; if >0, 1- loss
def __init__(self):
super(Neg_Pearson,self).__init__()
return
def forward(self, preds, labels): # tensor [Batch, Temporal]
loss = 0
for i in range(preds.shape[0]):
sum_x = torch.sum(preds[i]) # x
sum_y = torch.sum(labels[i]) # y
sum_xy = torch.sum(preds[i]*labels[i]) # xy
sum_x2 = torch.sum(torch.pow(preds[i],2)) # x^2
sum_y2 = torch.sum(torch.pow(labels[i],2)) # y^2
N = preds.shape[1]
pearson = (N*sum_xy - sum_x*sum_y)/(torch.sqrt((N*sum_x2 - torch.pow(sum_x,2))*(N*sum_y2 - torch.pow(sum_y,2))))
print(N)
#if (pearson>=0).data.cpu().numpy(): # torch.cuda.ByteTensor --> numpy
# loss += 1 - pearson
#else:
# loss += 1 - torch.abs(pearson)
loss += 1 - pearson
loss = loss/preds.shape[0]
return loss
#3. Calculate the loss
loss_ecg = Neg_Pearson(rPPG, BVP_label)
我不断收到以下错误:---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-15-f14cbf0fc84b> in <module>
1 #3. Calculate the loss
----> 2 loss_ecg = Neg_Pearson(rPPG, BVP_label)
TypeError: __init__() takes 1 positional argument but 3 were given
我是Pytorch的新手,我不确定这是怎么回事。有什么建议? 最佳答案
你那里有错字。而是尝试:
neg_pears_loss = Neg_Pearson()
loss = neg_pears_loss(rPPG, BVP_label)