def forward(self, pred, target):
if pred.dim() > 2:
pred = pred.view(pred.size(0), pred.size(1),
-1) # N,C,H,W => N,C,H*W
pred = pred.transpose(1, 2) # N,C,H*W => N,H*W,C
pred = pred.contiguous().view(-1,
pred.size(2)) # N,H*W,C => N*H*W,C
target = target.view(-1, 1)
pred_softmax = F.softmax(pred)
pred_softmax = pred_softmax.gather(1, target)
pred_softmax = pred_softmax.view(-1)
pt = Variable(pred_softmax.data)
diff = (1 - pt)**self.gamma
if self.alpha is not None:
if self.alpha.type() != input.data.type():
self.alpha = self.alpha.type_as(input.data)
alpha_t = self.alpha.gather(0, target.data.view(-1))
loss = -1 * alpha_t * diff * pt._log()
else:
loss = -1 * diff * pt.log_()
if self.reduction == 'mean':
return loss.mean()
else:
return loss.sum()
