Stuck on an issue?

Lightrun Answers was designed to reduce the constant googling that comes with debugging 3rd party libraries. It collects links to all the places you might be looking at while hunting down a tough bug.

And, if you’re still stuck at the end, we’re happy to hop on a call to see how we can help out.

[question] Cannot enjoy the trained agents.

See original GitHub issue

After cloning the rl-baselines3-zoo, I was trying to train my own agent. By : python --algo algo_name --env env_id After that, I used python --algo td3 --env AntBulletEnv-v0 -f logs/ However I got the following problem

Loading latest experiment, id=2 pybullet build time: Jun 2 2020 06:49:02 
/home/dell/gym/gym/ UserWarning: 
WARN: Box bound precision lowered by casting to float32 warnings.warn(colorize('%s: %s'%('WARN', msg % args), 'yellow')) 
Process ForkServerProcess-1: Traceback (most recent call last):
File "/home/dell/anaconda3/lib/python3.8/multiprocessing/", 
line 315, in _bootstrap 

File "/home/dell/anaconda3/lib/python3.8/multiprocessing/", 
line 108, in run self._target(*self._args, **self._kwargs) File "/home/dell/stable-baselines3/stable_baselines3/common/vec_env/", 
line 42, in _worker 
**raise NotImplementedError
 NotImplemented Error**

 Traceback (most recent call last): File "", 
line 201, in <module> main() File "", line 116, in main
 model = ALGOS[algo].load(model_path, env=env) 
File "/home/dell/stable-baselines3/stable_baselines3/common/",
 line 362, in load model._setup_model() 
File "/home/dell/stable-baselines3/stable_baselines3/td3/",
 line 95, in _setup_model super(TD3, self)._setup_model() 
File "/home/dell/stable-baselines3/stable_baselines3/common/", 
line 729, in _setup_model self.set_random_seed(self.seed)
 File "/home/dell/stable-baselines3/stable_baselines3/common/", 
line 461, in set_random_seed self.env.seed(seed) File "/home/dell/stable-baselines3/stable_baselines3/common/vec_env/",
 line 112, in seed return [remote.recv() for remote in self.remotes] 
File "/home/dell/stable-baselines3/stable_baselines3/common/vec_env/", 
line 112, in <listcomp> return [remote.recv() for remote in self.remotes] File "/home/dell/anaconda3/lib/python3.8/multiprocessing/", 
line 250, in recv buf = self._recv_bytes() 
File "/home/dell/anaconda3/lib/python3.8/multiprocessing/", 
line 414, in _recv_bytes buf = self._recv(4) 
File "/home/dell/anaconda3/lib/python3.8/multiprocessing/", 
line 383, in _recv 
**raise EOFError 

System Info

  • Stable Baselines3 was installed by pip
  • Ubuntu 18.04
  • Python 3.8.3
  • PyTorch 1.5.0
  • Gym 0.17.2
  • Pybullet 2.8.1
  • 2* Nvidia RTX 2080TI CUDA 10.2

I appreciate your help. Thank you in advance.

Issue Analytics

  • State:closed
  • Created 3 years ago
  • Comments:17 (11 by maintainers)

github_iconTop GitHub Comments

araffincommented, Jun 10, 2020

I recently upgraded both SB3 and SB3-zoo

Please do pip install git+ (cf doc) or enable pre-release install. The Stable-Baselines version should be 0.7.0a1

araffincommented, Jun 3, 2020


Could you reformat your traceback using markdown codeblock? (cf issue template)

Read more comments on GitHub >

github_iconTop Results From Across the Web

How to spot and act on agent training opportunities - NICE
Training agents to be digitally fluent is a widespread opportunity. To get you started, download The Ultimate Guide to CX Agents: Hiring, ...
Read more >
5 Tips for Training Customer Service Agents - Vocalcom
Agents are a key source of knowledge for best practices, so their experiences should count heavily in agent training.Use call scripts for greater...
Read more >
'ValueError: All of the Tensors in `experience` must have two ...
Hi all, I've been putting together a tf-agents environment with the goal of training agents to play an app I've made with Kivy....
Read more >
How to TRAIN further a previously trained agent? - MathWorks
My agent was programmed to stop after reaching an average reward of X. How do I load and extend the training further? I...
Read more >
How Can Call Center Agents Learn the Art of Asking the Right ...
Clarifying questions help agents gain a clear picture of what's going on, letting them understand the customer's thought process. It also pulls ...
Read more >

github_iconTop Related Medium Post

No results found

github_iconTop Related StackOverflow Question

No results found

github_iconTroubleshoot Live Code

Lightrun enables developers to add logs, metrics and snapshots to live code - no restarts or redeploys required.
Start Free

github_iconTop Related Reddit Thread

No results found

github_iconTop Related Hackernoon Post

No results found

github_iconTop Related Tweet

No results found

github_iconTop Related Post

No results found

github_iconTop Related Hashnode Post

No results found