def losses(self, outputs):
logits, feats, targets = outputs
loss_dict = {}
loss_dict.update(
reid_losses(self._cfg, logits[0], feats[0], targets, 'b1_'))
loss_dict.update(
reid_losses(self._cfg, logits[1], feats[1], targets, 'b2_'))
loss_dict.update(
reid_losses(self._cfg, logits[2], feats[2], targets, 'b3_'))
loss_dict.update(
reid_losses(self._cfg, logits[3], feats[3], targets, 'b21_'))
loss_dict.update(
reid_losses(self._cfg, logits[5], feats[4], targets, 'b31_'))
part_ce_loss = [(CrossEntropyLoss(self._cfg)(logits[4], None,
targets), 'b22_'),
(CrossEntropyLoss(self._cfg)(logits[6], None,
targets), 'b32_'),
(CrossEntropyLoss(self._cfg)(logits[7], None,
targets), 'b33_')]
named_ce_loss = {}
for item in part_ce_loss:
named_ce_loss[item[1] + [*item[0]][0]] = [*item[0].values()][0]
loss_dict.update(named_ce_loss)
return loss_dict
def losses(self, outputs):
pred_logits, global_feat, fore_pred_logits, fore_feat, targets = outputs
loss_dict = {}
loss_dict.update(
reid_losses(self._cfg, pred_logits, global_feat, targets,
'avg_branch_'))
loss_dict.update(
reid_losses(self._cfg, fore_pred_logits, fore_feat, targets,
'fore_branch_'))
return loss_dict
def losses(self, outputs):
logits, feat, targets = outputs
return reid_losses(self._cfg, logits, feat, targets)