| # Set the CUDA devices to use | |
| export CUDA_VISIBLE_DEVICES=0,1,2,3; | |
| # Launch the distributed training | |
| python -m torch.distributed.launch \ | |
| --nproc_per_node=4 \ | |
| --use_env \ | |
| --master_port=29501 \ | |
| 3_train_fill50k_rescale.py \ | |
| --batch-size 32 \ | |
| --total_train_steps 50000 \ | |
| --teacher-model vit_large \ | |
| --target_model vit_base \ | |
| --model models_proteus_dinov2 \ | |
| --patch_size 14 \ | |
| --cldm_learning_rate 1e-4 \ | |
| --lambda_token 1.0 \ | |
| --lambda_fea 1.0 \ | |
| --lambda_patch 1.0 \ | |
| --finetune "/home/t2vg-a100-G4-1/projects/qiyp/1_feature_extractor/1_feature_extractor/checkpoint0160.pth" \ | |
| --log_dir '/home/t2vg-a100-G4-1/projects/qiyp/3_ControlNet/log/' \ | |
| --resume_path '/home/t2vg-a100-G4-1/projects/qiyp/3_ControlNet/models/control_sd15_fill50k.ckpt' \ | |
| --image_floder '/home/t2vg-a100-G4-1/projects/dataset/train2017' \ | |
| --txt_path '/home/t2vg-a100-G4-1/projects/dataset/annotations/captions_train2017.json' \ | |
| --log_every 25 \ | |
| --ckpt_every 2500 \ | |
| --image_every 100 \ | |
| --cldm_yaml './models/cldm_fill50k.yaml' \ | |
| --exp_dir './exp_fill50k_rescale' \ | |
| --controlnet_dir '/home/t2vg-a100-G4-1/projects/qiyp/3_ControlNet/exp_fill50k_rescale/checkpoints/0002500.pt' \ | |