How many GPU memory does the neural network need?

[xiboli]

Hello Luca,

I try to run the program in my own computer, which is with GTX 2060 Super GPU. However it seems my 8GB memory is not enough because I always face OOM when allocating tensor with shape[64,464,3,12]. How much memory of GPU is needed?

Best regards Xibo

[Luca96]

Hi, I don't know exactly how much GPU mem is needed but, unfortunately, is plenty.

What you can try is to edit main.py. In particular you could set timesteps=256 and/or batch_size=32 in the learning.stage_sX(...) function calls. You can also reduce the input size, here, or even the #parameters of the agent's neural-net: see here and here too.

Hope it helps

[xiboli]

Thank you so much. I would try that. With Nvidia-smi I have saw that carla will use 4GB and the network should use more than 4 GB

[nguyenvantruong1905]

@xiboli hi

My Carla can use 4GB. I try

os.environ["CUDA_DEVICE_ORDER"] = "PCI_BUS_ID"
os.environ["CUDA_VISIBLE_DEVICES"] = "0"

but network not using GPU. pls help me

[Luca96]

@nguyenvantruong1905, check the following:

• Do you set the environment variables before loading tensorflow, i.e. before import tensorflow as tf?
• Do you have a CUDA capable GPU? If so, have you correctly installed CUDA, Cudnn, etc? Check the console for error messages.
• The issue happens only with CARLA, or even with tensorflow alone (to check the latter run a script with only tensorflow and make sure the GPU allocates a tensor)?
• Have you tried forcing GPU execution? You can do that by wrapping the code about the model with a with tf.device('gpu'): scope.