Layer Decay impl only supports convnext_small/base/large/xlarge

[ZackSong0319]

When I execute the command

python -m torch.distributed.launch --nproc_per_node=2 main.py \ --model unireplknet_xl --drop_path 0.3 --input_size 384 \ --batch_size 32 --lr 5e-5 --update_freq 2 \ --model_ema true --model_ema_eval true \ --warmup_epochs 0 --epochs 20 --weight_decay 1e-8 --smoothing 0.3 \ --layer_decay 0.8 --head_init_scale 0.001 --cutmix 0 --mixup 0 \ --finetune unireplknet_xl_in22k_to_in1k_384_acc87.96.pth \ --data_path UniRepLKNet/dataset \ --output_dir UniRepLKNet/dataset/results

this code： if args.layer_decay < 1.0 or args.layer_decay > 1.0: num_layers = 12 # convnext layers divided into 12 parts, each with a different decayed lr value. assert args.model in ['convnext_small', 'convnext_base', 'convnext_large', 'convnext_xlarge'], \ "Layer Decay impl only supports convnext_small/base/large/xlarge" assigner = LayerDecayValueAssigner(list(args.layer_decay ** (num_layers + 1 - i) for i in range(num_layers + 2))) else: assigner = None run wrong！！！ Do you think it's a typo in the name that caused this?How can I resolve it? Thank you.

[invictus717]

Yes, this can be easily replaced with "unireplknet_s", "unireplknet_l", etc.