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

# # # # Evaluate, choose an appropriate epoch
# CUDA_VISIBLE_DEVICES=0 python3 eval_new.py --env linear_bandit_train_original_emp_opt \
#     --envs 5000 \
#     --H 20 \
#     --dim 40 \
#     --lin_d 10 \
#     --var 0.3 \
#     --cov 0.0 \
#     --lr 0.00015 \
#     --layer 4 \
#     --head 4 \
#     --epoch 450 \
#     --n_eval 200 \
#     --seed 1 \
#     --pred_reward_type linear \
#     --eval_type Test_more_models \
#     --eval_new_env linear_bandit_train_lookahead_pred_reward \
#     --eval_new_env1 linear_bandit_train_AD


# # # # Evaluate, choose an appropriate epoch
# CUDA_VISIBLE_DEVICES=0 python3 eval_new.py --env linear_bandit_train_original_emp_opt \
#     --envs 10000 \
#     --H 20 \
#     --dim 40 \
#     --lin_d 10 \
#     --var 0.3 \
#     --cov 0.0 \
#     --lr 0.00015 \
#     --layer 4 \
#     --head 4 \
#     --epoch 450 \
#     --n_eval 200 \
#     --seed 1 \
#     --pred_reward_type linear \
#     --eval_type Test_more_models \
#     --eval_new_env linear_bandit_train_lookahead_pred_reward \
#     --eval_new_env1 linear_bandit_train_AD



# # # # Evaluate, choose an appropriate epoch
# CUDA_VISIBLE_DEVICES=0 python3 eval_new.py --env linear_bandit_train_original_emp_opt \
#     --envs 50000 \
#     --H 20 \
#     --dim 40 \
#     --lin_d 10 \
#     --var 0.3 \
#     --cov 0.0 \
#     --lr 0.00015 \
#     --layer 4 \
#     --head 4 \
#     --epoch 450 \
#     --n_eval 200 \
#     --seed 1 \
#     --pred_reward_type linear \
#     --eval_type Test_more_models \
#     --eval_new_env linear_bandit_train_lookahead_pred_reward \
#     --eval_new_env1 linear_bandit_train_AD




# # # # Evaluate, choose an appropriate epoch
# CUDA_VISIBLE_DEVICES=0 python3 eval_new.py --env linear_bandit_train_original_emp_opt \
#     --envs 100000 \
#     --H 20 \
#     --dim 40 \
#     --lin_d 10 \
#     --var 0.3 \
#     --cov 0.0 \
#     --lr 0.00015 \
#     --layer 4 \
#     --head 4 \
#     --epoch 450 \
#     --n_eval 200 \
#     --seed 1 \
#     --pred_reward_type linear \
#     --eval_type Test_more_models \
#     --eval_new_env linear_bandit_train_lookahead_pred_reward \
#     --eval_new_env1 linear_bandit_train_AD





# # # # Evaluate, choose an appropriate epoch
# CUDA_VISIBLE_DEVICES=0 python3 eval_new.py --env linear_bandit_train_original_emp_opt \
#     --envs 150001 \
#     --H 20 \
#     --dim 40 \
#     --lin_d 10 \
#     --var 0.3 \
#     --cov 0.0 \
#     --lr 0.00015 \
#     --layer 4 \
#     --head 4 \
#     --epoch 450 \
#     --n_eval 200 \
#     --seed 1 \
#     --pred_reward_type linear \
#     --eval_type Test_more_models \
#     --eval_new_env linear_bandit_train_lookahead_pred_reward \
#     --eval_new_env1 linear_bandit_train_AD




# # # Evaluate, choose an appropriate epoch
CUDA_VISIBLE_DEVICES=0 python3 eval_new.py --env linear_bandit_train_original_emp_opt \
    --envs 200008 \
    --H 20 \
    --dim 40 \
    --lin_d 10 \
    --var 0.3 \
    --cov 0.0 \
    --lr 0.00015 \
    --layer 4 \
    --head 4 \
    --epoch 450 \
    --n_eval 200 \
    --seed 1 \
    --pred_reward_type linear \
    --eval_type Test_more_models \
    --eval_new_env linear_bandit_train_lookahead_pred_reward \
    --eval_new_env1 linear_bandit_train_AD


