# 1) Clone
git clone https://github.com/Alphawarheads/Watermark_Spoofing.git
cd Watermark_Spoofing

# 2) (Optional) Use the bundled Fairseq snapshot
unzip fairseq-a54021305d6b3c4c5959ac9395135f63202db8f1.zip

# 3) Conda env
conda create -n kpwl python=3.7 -y
conda activate kpwl

# 4) PyTorch (adjust CUDA/ROCm wheels as needed)
pip install torch==1.12.1 torchvision==0.13.1 torchaudio==0.12.1

# 5) Fairseq (editable)
cd fairseq-a54021305d6b3c4c5959ac9395135f63202db8f1
pip install --editable ./
cd ..

# 6) Project requirements
pip install -r requirements.txt

TRACK=LA
PROTOCOLS=/public/home/qinxy/.../ASVspoof2021.LA.cm.eval.trl.txt
DATABASE_PATH=/public/home/qinxy/AudioData/Antispoofing/ASVspoof2021/ASVspoof2021_LA_eval/flac/
EVAL_OUTPUT=/public/home/qinxy/.../test2/${COMMENT}_eval_ori_LA21.txt
CUDA_VISIBLE_DEVICES=0,1,2,3 \
torchrun --standalone --nproc_per_node=4 \
    main_multinodes.py --track="$TRACK" --is_eval --eval \
  --model_path models/model_4dcu_kpwl.pth \
  --protocols_path="$PROTOCOLS" \
  --database_path="$DATABASE_PATH" \
  --eval_output="$EVAL_OUTPUT"

TRACK=LA
PROTOCOLS=/public/home/qinxy/zhangzs/watermarking/The-A-Files-master/protocols/tagged/LA21/protocol_wm_75_only.txt
DATABASE_PATH=/public/home/qinxy/AudioData/Antispoofing/LA21_phase1/
EVAL_OUTPUT=/public/home/qinxy/.../test2/${COMMENT}_eval_wm_seen_LA21.txt

TRACK=LA
PROTOCOLS=/public/home/qinxy/zhangzs/watermarking/The-A-Files-master/protocols/tagged_phase2/LA21/split/protocol_wm_75_only.txt
DATABASE_PATH=/public/home/qinxy/AudioData/Antispoofing/LA21_phase2/
EVAL_OUTPUT=/public/home/qinxy/.../test2/${COMMENT}_eval_wm_unseen_LA21.txt

# If auto_merge_scores is not in the same file, import it:
# from your_module import auto_merge_scores

TRACK = "ITW"     # one of {"LA21", "DF21", "ITW"}
comment = "ori"   # label used in your score filenames

outs = auto_merge_scores(
    track=TRACK,
    score_wm_path=f"/public/.../test2/{comment}_train_eval_wm_SLS_{TRACK}.txt",
    score_ori_path=f"/public/.../test2/{comment}_train_eval_ori_SLS_{TRACK}.txt",
)

print("Output Results:")
for p in outs:
    print(" -", p)

CUDA_VISIBLE_DEVICES=0,1,2,3 \
torchrun --standalone --nproc_per_node=4 \
  main_multinodes.py \
  --track=DF --lr=0.000001 --batch_size=5 --loss=WCE \
  --num_epochs=50 --comment 4dcu_baseline

CUDA_VISIBLE_DEVICES=0,1,2,3 \
torchrun --standalone --nproc_per_node=4 \
    main_kpwl.py \
  --eval_track=DF --lr=5e-7 --batch_size=5 --num_epochs=2 \
  --model_path best_model.pth \
  --comment model_4dcu_kpwl