I’m trying to train an agent using training_navigation.py from baselines repo.
I installed pytorch with CUDA support as described here: https://pytorch.org/get-started/locally/
I use lines 22-23 in dueling_double_dqn.py of baselines repo to switch between running on CPU and GPU.
Running on GPU speeds up the training about 1.5 times only comparing to running on CPU.
GPU seems to be in use (checked with nvidia-smi) but the load is very low (3-4%).
I’m new to pytorch and RL but I’ve trained some CNN using tensorflow.
In case of CNN GPU used to give me 10-50x increase in training speed.
Is it normal, that in case of the flatland training example the diference is so low, or am I missing something?