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adding final commands for tuning, training final models, testing them

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Arec Jamgochian
2022-03-03 12:12:12 -08:00
parent f5f1c24f45
commit fc04f8e9ee
2 changed files with 39 additions and 12 deletions
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21
evaluate_models.sh
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@@ -1,19 +1,18 @@
# can add --skip_running if you've run the runs before on the saved policies # can add --skip_running if you've already run the saved policies through the test environments and have appropriate
# metrics in the out folder. Doing so will generate average metrics quickly.
# Experiment A
python -m eval_experiments python -m eval_experiments
python -m eval_experiments --locations='[(0,4)]'
python -m eval_experiments --method idm python -m eval_experiments --method idm
python -m eval_experiments --method idm --locations='[(0,4)]'
python -m eval_experiments --method bc --folder='test_policies/bc/expA' python -m eval_experiments --method bc --folder='test_policies/bc/expA'
python -m eval_experiments --method bc --folder='test_policies/bc/expB' --locations='[(0,4)]'
python -m eval_experiments --method gail --folder='test_policies/gail/expA' python -m eval_experiments --method gail --folder='test_policies/gail/expA'
python -m eval_experiments --method gail --folder='test_policies/gail/expB' --locations='[(0,4)]'
python -m eval_experiments --method hail --folder='test_policies/hail/expA' python -m eval_experiments --method hail --folder='test_policies/hail/expA'
python -m eval_experiments --method hail --folder='test_policies/hail/expB' --locations='[(0,4)]'
python -m eval_experiments --method shail --folder='test_policies/shail/expA' python -m eval_experiments --method shail --folder='test_policies/shail/expA'
python -m eval_experiments --method shail --folder='test_policies/shail/expB' --locations='[(0,4)]'
python -m eval_experiments --method hail --folder='test_policies/hail-etienne/expA' # Experiment B
python -m eval_experiments --method hail --folder='test_policies/hail-etienne/expB' --locations='[(0,4)]' python -m eval_experiments --locations='[(0,4)]'
python -m eval_experiments --method shail --folder='test_policies/shail-etienne/expA' python -m eval_experiments --method idm --locations='[(0,4)]' --skip_running
python -m eval_experiments --method shail --folder='test_policies/shail-etienne/expB' --locations='[(0,4)]' python -m eval_experiments --method bc --folder='test_policies/bc/expB' --locations='[(0,4)]' --skip_running
python -m eval_experiments --method gail --folder='test_policies/gail/expB' --locations='[(0,4)]' --skip_running
python -m eval_experiments --method hail --folder='test_policies/hail/expB' --locations='[(0,4)]' --skip_running
python -m eval_experiments --method shail --folder='test_policies/shail/expB' --locations='[(0,4)]' --skip_running

28
train_models.sh Executable file
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# Hyperparameter tuning runs (will run search defined in files)
# Can add --epochs kwarg to change number of training epochs
# shail-experiment.py will generate the hail config aswell
# Experiment A
python bc-experiment.py --train A
python gail-experiment.py --train A
python shail-experiment.py --train A
# Experiment B
python bc-experiment.py --train B
python gail-experiment.py --train B
python shail-experiment.py --train B
# Retrain best models with 5 seeds
# Can add --test_seeds and --test_cpus kwargs to change number of seeds, allocate more memory
# Experiment A
python bc-experiment.py --test best_configs/bc_expA.json
python gail-experiment.py --test best_configs/gail_expA.json
python shail-experiment.py --train best_configs/hail_expA.json
python shail-experiment.py --train best_configs/shail_expA.json
# Experiment B
python bc-experiment.py --test best_configs/bc_expB.json
python gail-experiment.py --test best_configs/gail_expB.json
python shail-experiment.py --train best_configs/hail_expB.json
python shail-experiment.py --train best_configs/shail_expB.json