DiffICM / 3_ControlNet /3_train_controlnet.sh
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code of stage1 & 3, remove large files
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#### access DINOv2
export CUDA_VISIBLE_DEVICES=0,1;
python -m torch.distributed.launch --nproc_per_node=2 --use_env --master_port=29501 3_train_controlnet.py \
--batch-size 32 --total_train_steps 60000 \
--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_ini.ckpt' \
--image_floder '/home/t2vg-a100-G4-1/projects/dataset/LSDIR_raw/images/train' \
--txt_path '/home/t2vg-a100-G4-1/projects/dataset/annotations/captions_train2017.json' \
--log_every 20 --ckpt_every 5000 --image_every 100 \
# --controlnet_dir '/home/t2vg-a100-G4-1/projects/qiyp/3_ControlNet/exp/checkpoints/0015000.pt' \