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# Support for PyTorch mps mode (https://pytorch.org/docs/stable/notes/mps.html)
import os
os.environ["PYTORCH_ENABLE_MPS_FALLBACK"] = "1"
from rl_algo_impls.runner.evaluate import EvalArgs, evaluate_model
from rl_algo_impls.runner.running_utils import base_parser
def enjoy() -> None:
parser = base_parser(multiple=False)
parser.add_argument("--render", default=True, type=bool)
parser.add_argument("--best", default=True, type=bool)
parser.add_argument("--n_envs", default=1, type=int)
parser.add_argument("--n_episodes", default=3, type=int)
parser.add_argument("--deterministic-eval", default=None, type=bool)
parser.add_argument(
"--no-print-returns", action="store_true", help="Limit printing"
)
# wandb-run-path overrides base RunArgs
parser.add_argument("--wandb-run-path", default=None, type=str)
parser.set_defaults(
algo=["ppo"],
wandb_run_path="sgoodfriend/rl-algo-impls/m5c1t7g5",
)
args = parser.parse_args()
args.algo = args.algo[0]
args.env = args.env[0]
args = EvalArgs(**vars(args))
evaluate_model(args, os.getcwd())
if __name__ == "__main__":
enjoy()
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