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(
- ssh into the instance:
ssh -i $KEY_PAIR [email protected]$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.ipynband 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.
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