def transt_loss(settings):
num_classes = 1
matcher = build_matcher()
weight_dict = {'loss_ce': 8.334, 'loss_bbox': 5}
weight_dict['loss_giou'] = 2
losses = ['labels', 'boxes']
criterion = SetCriterion(num_classes, matcher=matcher, weight_dict=weight_dict,
eos_coef=0.0625, losses=losses)
device = torch.device(settings.device)
criterion.to(device)
return criterion
def transt_loss(settings):
num_classes = 1
matcher = build_matcher()
weight_dict = {'loss_ce': 8.334, 'loss_bbox': 5}
weight_dict['loss_giou'] = 2
weight_dict['loss_giou_circuit'] = 0
losses = ['labels', 'boxes']
criterion = SetCriterion(num_classes,
matcher=matcher,
weight_dict=weight_dict,
eos_coef=0.0625,
losses=losses)
device = torch.device(settings.device)
criterion.to(device)
return criterion
print([
n for n, p in model.named_parameters() if "exc" in n or "circuit" in n
or "mix" in n or "new" in n or "rnn" in n
])
