tracking/train_mixformer_vit.sh
# There are the detailed training settings for MixFormer-ViT-B and MixFormer-ViT-L.
# 1. download pretrained ViT-MAE models (mae_pretrain_vit_base.pth.pth/mae_pretrain_vit_large.pth) at https://github.com/facebookresearch/mae
# 2. set the proper pretrained CvT models path 'MODEL:BACKBONE:PRETRAINED_PATH' at experiment/mixformer_vit/CONFIG_NAME.yaml.
# 3. uncomment the following code to train corresponding trackers.

### Training MixFormer-ViT-B
# Stage1: train mixformer without SPM
python tracking/train.py --script mixformer_vit --config baseline --save_dir /YOUR/PATH/TO/SAVE/MIXFORMER --mode multiple --nproc_per_node 8
## Stage2: train mixformer_online, i.e., SPM (score prediction module)
# python tracking/train.py --script mixformer_vit_online --config baseline --save_dir /YOUR/PATH/TO/SAVE/MIXFORMER --mode multiple --nproc_per_node 8 --stage1_model /STAGE1/MODEL


### Training MixFormer-L
#python tracking/train.py --script mixformer_vit --config baseline_large --save_dir /YOUR/PATH/TO/SAVE/MIXFORMERL --mode multiple --nproc_per_node 8
#python tracking/train.py --script mixformer_vit_online --config baseline_large --save_dir /YOUR/PATH/TO/SAVE/MIXFORMERL_ONLINE --mode multiple --nproc_per_node 8 --stage1_model /STAGE1/MODEL


### Training MixFormer-B_GOT
#python tracking/train.py --script mixformer_vit --config baseline_got --save_dir /YOUR/PATH/TO/SAVE/MIXFORMER_GOT --mode multiple --nproc_per_node 8
#python tracking/train.py --script mixformer_vit_online --config baseline_got --save_dir /YOUR/PATH/TO/SAVE/MIXFORMER_GOT_ONLINE --mode multiple --nproc_per_node 8 \
#    --stage1_model /STAGE1/MODEL
