can i use 640x360 to my model?

[LiaoZihZrong]

Hello dear author,

(when trian my own dataset)
I'd like to inquire if it's possible to adjust the model to dimensions of 640 pixels width by 360 pixels height ( input dimensions not the shape of image).

when my yaml set input_size: [640 360] got bug, but set [640,640] is ok

loading COCO dataset…
loading cache from ./dataset/our/train_cache.edgeyolo.
DONE(t=0.07s)
max label number in one image: 14
20240510_100419 edgeyolo.train.trainer:168 - init data prefetcher…
20240510_100420 edgeyolo.train.trainer:178 - prefetcher loaded!
20240510_100420 edgeyolo.train.trainer:257 - init learning rate scheduler…
20240510_100420 edgeyolo.train.trainer:184 - loading evaluator…
20240510_100420 edgeyolo.train.trainer:219 - evaluator loaded.
20240510_100420 edgeyolo.train.trainer:355 - Training start…
20240510_100420 edgeyolo.models:146 - weight file saved to output/train/edgeyolo_tiny_coco/last_augmentation_epoch.pth
20240510_100420 edgeyolo.train.trainer:380 - Start Train Epoch 250 (No mosaic aug, L1 loss enabled)
20240510_100420 edgeyolo.train.loss:371 - error msg: selected index k out of range
––––––CPU Mode for This Batch––––––-
Traceback (most recent call last):
File "/media/kh1070/extt/edgeyolo-main/edgeyolo/train/loss.py", line 355, in get_losses
) = self.get_assignments( # noqa
File "/home/kh1070/anaconda3/envs/DAMO/lib/python3.8/site-packages/torch/autograd/grad_mode.py", line 28, in decorate_context
return func(*args, **kwargs)
File "/media/kh1070/extt/edgeyolo-main/edgeyolo/train/loss.py", line 553, in get_assignments
) = self.dynamic_k_matching(cost, pair_wise_ious, gt_classes, num_gt, fg_mask)
File "/media/kh1070/extt/edgeyolo-main/edgeyolo/train/loss.py", line 667, in dynamic_k_matching
_, pos_idx = torch.topk(
RuntimeError: selected index k out of range

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "train.py", line 16, in <module>
train("DEFAULT" if args.default else args.cfg)
File "/media/kh1070/extt/edgeyolo-main/edgeyolo/train/launch_train.py", line 112, in launch
train_single(params=params)
File "/media/kh1070/extt/edgeyolo-main/edgeyolo/train/launch_train.py", line 73, in train_single
trainer.train()
File "/media/kh1070/extt/edgeyolo-main/edgeyolo/train/trainer.py", line 500, in train
train_one_epoch()
File "/media/kh1070/extt/edgeyolo-main/edgeyolo/train/trainer.py", line 486, in train_one_epoch
train_one_iter()
File "/media/kh1070/extt/edgeyolo-main/edgeyolo/train/trainer.py", line 461, in train_one_iter
train_in_iter()
File "/media/kh1070/extt/edgeyolo-main/edgeyolo/train/trainer.py", line 411, in train_in_iter
outputs = self.loss(outputs, (targets, mask_edge))
File "/home/kh1070/anaconda3/envs/DAMO/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "/media/kh1070/extt/edgeyolo-main/edgeyolo/train/loss.py", line 241, in forward
loss, bbox_loss, confidence_loss, class_loss, l1_loss, num_fg = self.get_losses(
File "/media/kh1070/extt/edgeyolo-main/edgeyolo/train/loss.py", line 389, in get_losses
) = self.get_assignments( # noqa
File "/home/kh1070/anaconda3/envs/DAMO/lib/python3.8/site-packages/torch/autograd/grad_mode.py", line 28, in decorate_context
return func(*args, **kwargs)
File "/media/kh1070/extt/edgeyolo-main/edgeyolo/train/loss.py", line 553, in get_assignments
) = self.dynamic_k_matching(cost, pair_wise_ious, gt_classes, num_gt, fg_mask)
File "/media/kh1070/extt/edgeyolo-main/edgeyolo/train/loss.py", line 667, in dynamic_k_matching
_, pos_idx = torch.topk(
RuntimeError: selected index k out of range

otherwise, is input dimensions must square(like 416x416 or 640x640) ?

Thank you.