| DATA_DIR=$1 | |
| TRAINTASK=${2-'[rainbow-stack,bowl-ball-placement]'} | |
| TESTTASK=${3-'[rainbow-stack,bowl-ball-placement]'} | |
| TASKNAME=${4-'mix-two'} | |
| STEPS=${5-'10000'} | |
| DISP=False | |
| echo "Training multi-task dataset... Folder: $DATA_DIR Task $TRAINTASK" | |
| # You can parallelize these depending on how much resources you have | |
| ############################# | |
| ## Language-Conditioned Tasks | |
| # [align-rope,assembling-kits-seq-seen-colors,assembling-kits-seq-unseen-colors,packing-shapes,stack-block-pyramid-seq-unseen-colors, | |
| # separating-piles-seen-colors,separating-piles-unseen-colors,towers-of-hanoi-seq-seen-colors,towers-of-hanoi-seq-unseen-colors] | |
| # example: sh scripts/traintest_scripts/train_test_multi_task_indistribution.sh data "[align-rope,sweeping-piles,align-box-corner,block-insertion,manipulating-rope,place-red-in-green]" 6taskindomain | |
| # sh scripts/traintest_scripts/train_test_multi_task_goal.sh data "[align-rope,sweeping-piles,align-box-corner,block-insertion,manipulating-rope,place-red-in-green]" "[towers-of-hanoi]" 6taskgen | |
| # sh scripts/traintest_scripts/train_test_multi_task_goal.sh data "[align-rope,sweeping-piles,align-box-corner]" "[towers-of-hanoi]" 3taskgen | |
| # sh scripts/traintest_scripts/train_test_multi_task_goal.sh data "[align-rope]" "[towers-of-hanoi]" 1taskgen | |
| # sh scripts/traintest_scripts/train_test_multi_task_goal.sh data "[align-rope,sweeping-piles,align-box-corner,block-insertion,manipulating-rope,place-red-in-green]" "[towers-of-hanoi]" 10taskgen | |
| trap "kill 0" SIGINT | |
| python cliport/train.py train.task=$TRAINTASK \ | |
| train.agent=cliport \ | |
| train.model_task=$TASKNAME \ | |
| train.attn_stream_fusion_type=add \ | |
| train.trans_stream_fusion_type=conv \ | |
| train.lang_fusion_type=mult \ | |
| train.n_demos=10 \ | |
| train.n_steps=${STEPS} \ | |
| dataset.cache=True \ | |
| train.exp_folder=exps/exp-$TASKNAME-smaller \ | |
| dataset.type=multi \ | |
| train.load_from_last_ckpt=False \ | |
| train.training_step_scale=500 # scale up training steps | |
| # Convert Python list to Bash array | |
| bash_array=$(python3 -c "import sys; print(' '.join((sys.argv[1])[1:-1].split(',')))" "$TRAINTASK") | |
| # Convert the space-separated string to a bash array | |
| echo "Testing multi-task dataset... Folder: $DATA_DIR Task $TESTTASK" | |
| for task in $bash_array | |
| do | |
| echo "Testing $task" | |
| # TEST | |
| # bash scripts/generate_gpt_datasets.sh data $task | |
| python cliport/eval.py model_task=$TASKNAME \ | |
| eval_task=$task \ | |
| agent=cliport \ | |
| mode=test \ | |
| n_demos=100 \ | |
| train_demos=10 \ | |
| checkpoint_type=test_best \ | |
| type=single \ | |
| exp_folder=exps/exp-$TASKNAME-smaller \ | |
| update_results=True & | |
| done | |
| wait | |
| python notebooks/print_results.py -r=exps/exp-$TASKNAME-smaller | |
| echo "Finished Training." |