cifar10-fast
Demonstration of training a small ResNet on CIFAR10 to 94% test accuracy in 79 seconds.
Instructions to reproduce on an AWS p3.2xlarge
instance:
- setup an instance with AMI:
Deep Learning AMI (Ubuntu) Version 11.0
(ami-c47c28bc
inus-west-2
) - ssh into the instance:
ssh -i $KEY_PAIR ubuntu@$PUBLIC_IP_ADDRESS -L 8901:localhost:8901
- on the remote machine
source activate pytorch_p36
pip install pydot
(optional for network visualisation)git clone https://github.com/davidcpage/cifar10-fast.git
jupyter notebook --no-browser --port=8901
- open the jupyter notebook url in a browser, open
demo.ipynb
and run all the cells
In my test, 35 out of 50 runs reached 94% test set accuracy with a median of 94.08%. Runtime for 24 epochs is roughly 79s.
A second notebook experiments.ipynb
contains code to reproduce the main results from the posts.
NB: demo.ipynb
also works on the latest Deep Learning AMI (Ubuntu) Version 16.0
, but some examples in experiments.ipynb
trigger a core dump when using TensorCores in versions after 11.0
.