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When running the iddpg algorithm in the MAMujoco environment, the memory keeps increasing. #245

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whbeats opened this issue Sep 21, 2024 · 1 comment

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@whbeats
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whbeats commented Sep 21, 2024

Hello! When running the iddpg algorithm in the MAMujoco environment, the memory keeps increasing. Finally, when the memory is full, an error will be reported and stopped. But when I run the mappo algorithm, the memory does not increase significantly.
thank you very much

Current time: 2024-09-21 22:49:39 (running for 00:00:42.09)
Memory usage on this node: 8.6/31.2 GiB
Using FIFO scheduling algorithm.
Resources requested: 2.0/20 CPUs, 1.0/1 GPUs, 0.0/13.19 GiB heap, 0.0/10.0 GiB objects (0.0/1.0 accelerator_type:G)
Result logdir: /home/wang/Codes/MyCodes/010_MAMJC/MARLlib/exp_results/iddpg_mlp_2AgentHalfCheetah
Number of trials: 1/1 (1 RUNNING)
...
Memory usage on this node: 10.6/31.2 GiB
...
Memory usage on this node: 10.8/31.2 GiB
...
Memory usage on this node: 16.0/31.2 GiB

@whbeats
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whbeats commented Sep 21, 2024

In addition, after I run the code, the following prompt appears. Is it related to the memory gradually filling up?

[HyperEdge({bfoot, bshin}), HyperEdge({bshin, bthigh}), HyperEdge({bthigh, fthigh}), HyperEdge({fshin, fthigh}), HyperEdge({fshin, ffoot})]
[HyperEdge({bfoot, bshin}), HyperEdge({bshin, bthigh}), HyperEdge({bthigh, fthigh}), HyperEdge({fshin, fthigh}), HyperEdge({fshin, ffoot})]
/home/wang/.conda/envs/MAMJC/lib/python3.8/site-packages/gym/logger.py:34: UserWarning: WARN: Box bound precision lowered by casting to float32
warnings.warn(colorize("%s: %s" % ("WARN", msg % args), "yellow"))
2024-09-21 22:48:57,669 INFO logger.py:605 -- pip install 'ray[tune]' to see TensorBoard files.
2024-09-21 22:48:57,669 WARNING callback.py:114 -- The TensorboardX logger cannot be instantiated because either TensorboardX or one of it's dependencies is not installed. Please make sure you have the latest version of TensorboardX installed: pip install -U tensorboardx
2024-09-21 22:48:57,784 WARNING worker.py:496 -- ray.get_gpu_ids() will always return the empty list when called from the driver. This is because Ray does not manage GPU allocations to the driver process.
:task_name:bundle_reservation_check_func
:actor_name:IDDPGTrainer
2024-09-21 22:48:57,832 WARNING deprecation.py:38 -- DeprecationWarning: simple_optimizer has been deprecated. This will raise an error in the future!
2024-09-21 22:48:57,832 INFO trainer.py:770 -- Current log_level is WARN. For more information, set 'log_level': 'INFO' / 'DEBUG' or use the -v and -vv flags.
:actor_name:RolloutWorker
[HyperEdge({bshin, bfoot}), HyperEdge({bshin, bthigh}), HyperEdge({fthigh, bthigh}), HyperEdge({fthigh, fshin}), HyperEdge({ffoot, fshin})]
[HyperEdge({bshin, bfoot}), HyperEdge({bshin, bthigh}), HyperEdge({fthigh, bthigh}), HyperEdge({fthigh, fshin}), HyperEdge({ffoot, fshin})]
2024-09-21 22:48:57,895 WARNING deprecation.py:38 -- DeprecationWarning: SampleBatch['is_training'] has been deprecated. Use SampleBatch.is_training instead. This will raise an error in the future!
2024-09-21 22:48:57,899 WARNING rollout_worker.py:578 -- You are running ray with local_mode=True, but have configured 1 GPUs to be used! In local mode, Policies are placed on the CPU and the num_gpus setting is ignored.
/home/wang/.conda/envs/MAMJC/lib/python3.8/site-packages/ray/rllib/agents/ddpg/ddpg_torch_model.py:103: UserWarning: The given NumPy array is not writeable, and PyTorch does not support non-writeable tensors. This means you can write to the underlying (supposedly non-writeable) NumPy array using the tensor. You may want to copy the array to protect its data or make it writeable before converting it to a tensor. This type of warning will be suppressed for the rest of this program. (Triggered internally at /pytorch/torch/csrc/utils/tensor_numpy.cpp:180.)
torch.from_numpy(self.action_space.low).float())
2024-09-21 22:48:57,908 WARNING deprecation.py:38 -- DeprecationWarning: simple_optimizer has been deprecated. This will raise an error in the future!
/home/wang/.conda/envs/MAMJC/lib/python3.8/site-packages/gym/logger.py:34: UserWarning: WARN: Box bound precision lowered by casting to float32
warnings.warn(colorize("%s: %s" % ("WARN", msg % args), "yellow"))
2024-09-21 22:48:57,914 WARNING rollout_worker.py:578 -- You are running ray with local_mode=True, but have configured 1 GPUs to be used! In local mode, Policies are placed on the CPU and the num_gpus setting is ignored.
2024-09-21 22:48:57,920 WARNING util.py:57 -- Install gputil for GPU system monitoring.
[HyperEdge({bfoot, bshin}), HyperEdge({bshin, bthigh}), HyperEdge({fthigh, bthigh}), HyperEdge({fthigh, fshin}), HyperEdge({ffoot, fshin})]
[HyperEdge({bfoot, bshin}), HyperEdge({bshin, bthigh}), HyperEdge({fthigh, bthigh}), HyperEdge({fthigh, fshin}), HyperEdge({ffoot, fshin})]
:actor_name:IDDPGTrainer

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