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How to use load_environments method in lisa

Best Python code snippet using lisa_python

a_star_transfer_main.py

Source:a_star_transfer_main.py

...157    models = {'final': ecco_pretrain.model, 'transfer': ecco_transfer.model,158              'explore': a_star.model}159    from env.env_utils import load_environments160    if args.load_environments is not None:161        environments_cache = load_environments(162            args.load_environments, args.num_cache, args.task,163            args.episode_length, args.seed164        )165    else:166        environments_cache = None167    train(dqn_transfer_trainer.trainer, dqn_transfer_task_sampler,168          dqn_transfer_worker, models, args, None,169          {'transfer_fnc': transfer, 'transfer_thread': a_star_transfer_trainer},170          environments_cache)171if __name__ == '__main__':...

dqn_transfer_st_main.py

Source:dqn_transfer_st_main.py

...154    models = {'final': ecco_pretrain.model, 'transfer': ecco_transfer.model,155           'base': base_model.model}156    from env.env_utils import load_environments157    if args.load_environments is not None:158        environments_cache = load_environments(159            args.load_environments, args.num_cache, args.task,160            args.episode_length, args.seed161        )162    else:163        environments_cache = None164    train(dqn_transfer_trainer.trainer, dqn_transfer_task_sampler, 165          dqn_transfer_worker, models, args,166          {'pretrain_fnc':pretrain, 'pretrain_thread': dqn_transfer_jwt},167          environments_cache)168    169if __name__ == '__main__':...

vis.py

Source:vis.py

...8from utils.load_envs import load_environments9from learning_algs.amp_models import ActorCriticNet10if __name__ == '__main__':11    args = load_args()12    # _, env, _ = load_environments(args)13    env = HumanoidTreadmillEnv(args=args)14    model = ActorCriticNet(env.observation_space.shape[0], env.action_space.shape[0], [128, 128])15    model.load_state_dict(torch.load('results/models/fc_test/fc_test_iter3400.pt'))  # relative file path16    model.cuda()17    # print(env.action_space.shape[0])18    while True:19        state = env.reset()20        done = False21        while not done:22            with torch.no_grad():23                act = model.sample_best_actions(torch.from_numpy(state).cuda().type(torch.cuda.FloatTensor)).cpu().numpy()24                # act = np.zeros(env.action_space.shape[0])25            next_state, reward, done, info = env.step(act)26            # print("in loop")...

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