################ We collect data using LinUCB, and optimal 
################ action is the next action (lookahead)

# # Collect data using TS
CUDA_VISIBLE_DEVICES=0 python3 collect_data_lookahead.py --env linear_bandit_train_lookahead_wt \
    --envs 200001 \
    --H 200 \
    --dim 10 \
    --var 0.3 \
    --cov 0.0 \
    --lin_d 2 \
    --envs_eval 200 \
    --data_type TS_wt

# # Train
CUDA_VISIBLE_DEVICES=0 python3 train_new_wt.py --env linear_bandit_train_lookahead_wt \
    --envs 200001 \
    --H 200 \
    --dim 10 \
    --lin_d 2 \
    --var 0.3 \
    --cov 0.0 \
    --lr 0.00015 \
    --layer 4 \
    --head 4 \
    --num_epochs 1000 \
    --seed 1

# # Evaluate, choose an appropriate epoch
CUDA_VISIBLE_DEVICES=0 python3 eval_new.py --env linear_bandit_train_lookahead_wt \
    --envs 200001 \
    --H 200 \
    --dim 10 \
    --lin_d 2 \
    --var 0.3 \
    --cov 0.0 \
    --lr 0.00015 \
    --layer 4 \
    --head 4 \
    --epoch 1000 \
    --n_eval 200 \
    --seed 1
