Comments (3)
Hi @Panshark , apologies for the delayed response. Unfortunately, pygame objects cannot be pickled. Any replacement for pygame (to render/display to screen) will also likely use objects that cannot be pickled.
Could you explain your use case and use of multiprocessing
? There is likely other ways to achieve the parallelization/multiprocessing you are looking for.
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Hi @praveen-palanisamy ,
In the beginning, I tried to train a meta reinforcement learning network for Carla, so I need to use multiprocessing
to due with the inner sampling of meta-rl. However, since I am questioning whether meta could work in such a complex task as autonomous driving or not, I did not continue to experiment on the Meta network. If you have any information about this idea, please tell me, really thank you.
Now I am trying to design some continuous changing environment in Carla, do you have any example of how do we define the weather changing using cloudy, precipitation, precipitation deposits, and wind intensity? Like, give it a changing function to simulate the weather change in our true world. Also, I will be really grateful if you can share any information about this question.
Best Regards
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Hi @Panshark ,
Thank you for explaining your use case.
You can randomize the weather in each of the training episode by customizing the "weather_distribution"
config in the scenario definition for example, you could change this line:
macad-gym/src/macad_gym/carla/scenarios.py
Line 113 in 38884ac
to include multiple weather conditions like this:
"weather_distribution": [0, 1, 2, 3, 4],
Where the weather integer enum values are described as below:
macad-gym/src/macad_gym/carla/scenarios.py
Lines 8 to 23 in 38884ac
If you want to change the weather dynamically within each of the episodes (not recommended), you can use the CARLA API directly. Sample script to dynamically change weather is provided here: Dynamic Weather
Converting this question to a GitHub discussion. Mark as answered if you got answer to your question.
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