Closed Natibus closed 5 years ago
Not sure, I didn't run on K80. I typically run on a V100 which if I understand correctly is roughly the same speed as a RTX2080 TI. It takes roughly 20 hours for full training on such a GPU.
Note that for the purpose of quick experimentation you don't really have to train that long, even after 1/4th of the training has elapsed the network starts to make good predictions.
Hello, I'm trying to run your project on google colab. I ran your example line after the setup :
CUDA_VISIBLE_DEVICES=0 python mixmatch.py --filters=32 --dataset=cifar10.3@250-5000 --w_match=75 --beta=0.75
I can see on stdout that there are 1024 epochs, each taking about 5 minutes for a speed of about 180 images / sec. That leads to a total experiment time of 85 hours. Is it normal for the experiment to be that long on a Colab (K80) GPU ?