RuntimeError: torch.cat(): expected a non-empty list of Tensors,when train p6 ?

[hjl0202]

 Epoch   gpu_mem       box       obj       cls     total    labels  img_size
 4/299       16G       nan   0.01189         0       nan         1      1280: 100%|██████████| 1014/1014 [11:14<00:00,  1.50it/s]
           Class      Images      Labels           P           R      mAP@.5  mAP@.5:.95: 100%|██████████| 127/127 [00:44<00:00,  2.87it/s]
             all        4053        4737       0.703       0.517       0.615       0.302

 Epoch   gpu_mem       box       obj       cls     total    labels  img_size
 5/299       16G   0.05048   0.01145         0   0.06193        44      1280: 100%|█████████▉| 1013/1014 [11:15<00:00,  1.50it/s]

Traceback (most recent call last): File "/home/gdu/work/hjl/yolov7-main/train_aux.py", line 609, in train(hyp, opt, device, tb_writer) File "/home/gdu/work/hjl/yolov7-main/train_aux.py", line 362, in train loss, loss_items = compute_loss_ota(pred, targets.to(device), imgs) # loss scaled by batch_size File "/home/gdu/work/hjl/yolov7-main/utils/loss.py", line 1197, in call bs_aux, asaux, gjs_aux, gis_aux, targets_aux, anchors_aux = self.build_targets2(p[:self.nl], targets, imgs) File "/home/gdu/work/hjl/yolov7-main/utils/loss.py", line 1551, in build_targets2 matching_bs[i] = torch.cat(matching_bs[i], dim=0) RuntimeError: torch.cat(): expected a non-empty list of Tensors

[hjl0202]

if name == 'main': parser = argparse.ArgumentParser() parser.add_argument('--weights', type=str, default='', help='initial weights path') parser.add_argument('--cfg', type=str, default='cfg/training/yolov7-w6.yaml', help='model.yaml path') parser.add_argument('--data', type=str, default='data/fish.yaml', help='data.yaml path') parser.add_argument('--hyp', type=str, default='data/hyp.scratch.p6.yaml', help='hyperparameters path') parser.add_argument('--epochs', type=int, default=300) parser.add_argument('--batch-size', type=int, default=16, help='total batch size for all GPUs') parser.add_argument('--img-size', nargs='+', type=int, default=[1280, 1280], help='[train, test] image sizes') parser.add_argument('--rect', action='store_true', help='rectangular training') parser.add_argument('--resume', nargs='?', const=True, default=False, help='resume most recent training') parser.add_argument('--nosave', action='store_true', help='only save final checkpoint') parser.add_argument('--notest', action='store_true', help='only test final epoch') parser.add_argument('--noautoanchor', action='store_true', help='disable autoanchor check') parser.add_argument('--evolve', action='store_true', help='evolve hyperparameters') parser.add_argument('--bucket', type=str, default='', help='gsutil bucket') parser.add_argument('--cache-images', action='store_true', help='cache images for faster training') parser.add_argument('--image-weights', action='store_true', help='use weighted image selection for training') parser.add_argument('--device', default='', help='cuda device, i.e. 0 or 0,1,2,3 or cpu') parser.add_argument('--multi-scale', action='store_true', help='vary img-size +/- 50%%') parser.add_argument('--single-cls', action='store_true', help='train multi-class data as single-class') parser.add_argument('--adam', action='store_true', help='use torch.optim.Adam() optimizer') parser.add_argument('--sync-bn', action='store_true', help='use SyncBatchNorm, only available in DDP mode') parser.add_argument('--local_rank', type=int, default=-1, help='DDP parameter, do not modify') parser.add_argument('--workers', type=int, default=8, help='maximum number of dataloader workers') parser.add_argument('--project', default='runs/train', help='save to project/name') parser.add_argument('--entity', default=None, help='W&B entity') parser.add_argument('--name', default='exp', help='save to project/name') parser.add_argument('--exist-ok', action='store_true', help='existing project/name ok, do not increment') parser.add_argument('--quad', action='store_true', help='quad dataloader') parser.add_argument('--linear-lr', action='store_true', help='linear LR') parser.add_argument('--label-smoothing', type=float, default=0.0, help='Label smoothing epsilon') parser.add_argument('--upload_dataset', action='store_true', help='Upload dataset as W&B artifact table') parser.add_argument('--bbox_interval', type=int, default=-1, help='Set bounding-box image logging interval for W&B') parser.add_argument('--save_period', type=int, default=-1, help='Log model after every "save_period" epoch') parser.add_argument('--artifact_alias', type=str, default="latest", help='version of dataset artifact to be used')

[WongKinYiu]

Thanks. Fixed.

[2u4dk123]

how to fix this problem ? i met this error and dont know how to do now. thanks for any answer.

[Nirvana0005]

i met this error and dont know how to do now too