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isk03276 / LearnToMoveUR3

Learning various robotic manipulations tasks of the UR3
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QMutex: destroying locked mutex #3

Open deavn2236 opened 9 months ago

deavn2236 commented 9 months ago

"Hello, when I use the command to run the pre-trained model you provided, the following issue occurs. Could you please tell me the reason for this?

python main.py --env-id reach --load-from pretrained_models/reach/checkpoint_000575/checkpoint-575 --test

error 2023-12-11 17:22:15,948 WARNING ppo.py:395 -- train_batch_size (5000) cannot be achieved with your other settings (num_workers=4 num_envs_per_worker=1 rollout_fragment_length=100)! Auto-adjusting rollout_fragment_length to 1250. 2023-12-11 17:22:15,949 INFO ppo.py:415 -- In multi-agent mode, policies will be optimized sequentially by the multi-GPU optimizer. Consider setting simple_optimizer=True if this doesn't work for you. 2023-12-11 17:22:15,949 INFO trainer.py:906 -- Current log_level is WARN. For more information, set 'log_level': 'INFO' / 'DEBUG' or use the -v and -vv flags. (RolloutWorker pid=11459) 2023-12-11 17:22:18,686 WARNING env.py:136 -- Your env doesn't have a .spec.max_episode_steps attribute. This is fine if you have set 'horizon' in your config dictionary, or soft_horizon. However, if you haven't, 'horizon' will default to infinity, and your environment will not be reset. (RolloutWorker pid=11462) 2023-12-11 17:22:18,719 WARNING env.py:136 -- Your env doesn't have a .spec.max_episode_steps attribute. This is fine if you have set 'horizon' in your config dictionary, or soft_horizon. However, if you haven't, 'horizon' will default to infinity, and your environment will not be reset. (RolloutWorker pid=11461) 2023-12-11 17:22:18,715 WARNING env.py:136 -- Your env doesn't have a .spec.max_episode_steps attribute. This is fine if you have set 'horizon' in your config dictionary, or soft_horizon. However, if you haven't, 'horizon' will default to infinity, and your environment will not be reset. (RolloutWorker pid=11460) 2023-12-11 17:22:18,748 WARNING env.py:136 -- Your env doesn't have a .spec.max_episode_steps attribute. This is fine if you have set 'horizon' in your config dictionary, or soft_horizon. However, if you haven't, 'horizon' will default to infinity, and your environment will not be reset. 2023-12-11 17:22:19,701 WARNING util.py:65 -- Install gputil for GPU system monitoring. 2023-12-11 17:22:19,708 INFO trainable.py:589 -- Restored on 172.25.216.219 from checkpoint: pretrained_models/reach/checkpoint_000575/checkpoint-575 2023-12-11 17:22:19,708 INFO trainable.py:597 -- Current state after restoring: {'_iteration': 575, '_timesteps_total': None, '_time_total': 24399.69826555252, '_episodes_total': 19362} 2023-12-11 17:22:21,457 WARNING deprecation.py:47 -- DeprecationWarning: compute_action has been deprecated. Use Trainer.compute_single_action() instead. This will raise an error in the future! [Test] 1 reward -0.01 len 85.00, success mean 1.00 [Test] 2 reward -0.01 len 60.00, success mean 1.00 [Test] 3 reward -0.01 len 78.00, success mean 1.00 [Test] 4 reward -0.01 len 300.00, success mean 0.75 [Test] 5 reward -0.01 len 85.00, success mean 0.80 [Test] 6 reward -0.01 len 48.00, success mean 0.83 [Test] 7 reward -0.01 len 95.00, success mean 0.86 [Test] 8 reward -0.01 len 98.00, success mean 0.88 [Test] 9 reward -0.02 len 51.00, success mean 0.89 [Test] 10 reward -0.01 len 35.00, success mean 0.90 QMutex: destroying locked mutex

lgortiz1 commented 8 months ago

hello friend, could you tell me what version of Ubuntu and ROS are you using ?