Question about loss_cls_ic

[Yifei-Y]

Nice job! I am trying to reproduce your work. But I find that loss_cls_ic is 0 for most of the time after the training started. Is it normal? (I set batch_size=4 because of the limited computational resources.)
Thanks.

[csuhan]

You can check our training log at here, loss_cls_ic should not be zero. Note that we use 8 GPUs and a batch size of 16 by default.

Besides, you can set break points in the following code:

opendet2/opendet2/modeling/roi_heads/fast_rcnn.py

Lines 366 to 381 in 18b8077

	def get_ic_loss(self, feat, gt_classes, ious):
	# select foreground and iou > thr instance in a mini-batch
	pos_inds = (ious > self.ic_loss_batch_iou_thr) & (
	gt_classes != self.num_classes)
	feat, gt_classes = feat[pos_inds], gt_classes[pos_inds]
	queue = self.queue.reshape(-1, self.ic_loss_out_dim)
	queue_label = self.queue_label.reshape(-1)
	queue_inds = queue_label != -1 # filter empty queue
	queue, queue_label = queue[queue_inds], queue_label[queue_inds]
	loss_ic_loss = self.ic_loss_loss(feat, gt_classes, queue, queue_label)
	# loss decay
	storage = get_event_storage()
	decay_weight = 1.0 - storage.iter / self.max_iters
	return {"loss_cls_ic": self.ic_loss_weight * decay_weight * loss_ic_loss}

[Yifei-Y]

Thanks! I have found the error in my code.

[Kyfafyd]

Thanks! I have found the error in my code.

hi, how you solve the error?