experiments/scripts/eval_action_scripts/run_evaluation.sh

#!/bin/bash

set -x
ulimit -c 0

set -x
ulimit -c 0

script_name=${1}
dataset=${2}


echo "--------------------------------------------------" >> ~/history.txt
echo "Slurm job id | job id | command | model | dataset" >> ~/history.txt
echo "$SLURM_JOB_ID | $JOB_ID | evaluation | $script_name | $dataset" >> ~/history.txt
WANDB_KEY=4c1540ebf8cb9964703ac212a937c00848a79b67
wandb login ${WANDB_KEY}
export WANDB__SERVICE_WAIT=300

############################ Teacher Forcing ############################
# evaluate
CUDA_VISIBLE_DEVICES=0 python genie/evaluate.py --checkpoint_dir data/${script_name}  \
    --val_data_dir data/${dataset}_magvit_traj1000000_val --save_outputs_dir data/${script_name}_${dataset} &
CUDA_VISIBLE_DEVICES=1 python genie/evaluate.py --checkpoint_dir data/${script_name}  \
    --val_data_dir data/${dataset}_magvit_traj1000000_val --autoregressive_time  --save_outputs_dir data/${script_name}_${dataset}

mkdir -p data/${script_name}_${dataset}/output


CUDA_VISIBLE_DEVICES=0  python genie/generate.py  --checkpoint_dir data/${script_name}  \
--val_data_dir data/${dataset}_magvit_traj1000000_val  \
--output_dir data/${script_name}_${dataset}/output

# visualize
CUDA_VISIBLE_DEVICES=0 python visualize.py --token_dir data/${script_name}_${dataset}/output


############################ Autoregressive ############################