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2026SEL3-project-Brittle_St.../experiments/train.py

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Python

import time
import tyro
from brittle_star_project.dataclasses import PPOArgs
from PPOTrainer import PPOTrainer
from brittle_star_project.environment.BrittleStarJaxEnvWrapper import BrittleStarJaxEnvWrapper
def make_env(config_path: str | None, num_envs: int) -> BrittleStarJaxEnvWrapper:
if config_path is None:
return BrittleStarJaxEnvWrapper.default(num_envs=num_envs)
return BrittleStarJaxEnvWrapper.from_config(config_path, num_envs=num_envs)
if __name__ == "__main__":
args = tyro.cli(PPOArgs)
args.batch_size = args.num_envs * args.num_steps
args.minibatch_size = args.batch_size // args.num_minibatches
# args.num_iterations = args.total_timesteps // args.batch_size
args.num_iterations = 5
run_name = f"{args.exp_name}__seed_{args.seed}__{int(time.time())}"
env = make_env(args.config_path, args.num_envs)
ppo_trainer = PPOTrainer(args, env, run_name)
ppo_trainer.train()