IMPORTANT: Turns out pytorch doesn’t work well with CUDA9. Maybe you need to compile it differently, maybe there is something else that I am missing. It works okay with CUDA8 - I updated the script to use CUDA8. This means we don’t have p3 support but for using pytorch this is the way to go.
In the new installation script I no longer download the dogsvscats dataset nor do I pull a version of fastai from my forked repo. You should be doing
git clone https://github.com/fastai/fastai.git instead.
EDIT: I share one way of spinning up an instance and sshing into it in this post. These instructions are equivalent to step #1 and step #2 mentioned below.
Install script with blank Ubuntu Server 16.04 LTS (ami-785db401) instance
- Spin up a p2.xlarge or p3.2xlarge
- SSH into your instance and run:
- Press enter / y when prompted.
- Enter a password for jupter notebook when prompted and hit enter.
- To run jupyter notebook, execute
- To connect to your jupyter notebook, either configure a public IP for your instance or follow the instructions provided here for tunneling [recommended].
Install script with AWS Spot instances with persistent storage
- this gives you p2 instances for ~0.25$ per h -
- Follow the instructions here up to step #6.
- In step #6, replace the command with the following:
- uncomment lines 69 - 71
- Perform the remaining steps.
AWS AMI with the above installed
AMI for p2.xlarge: ami-19a00360 (new AMI with CUDA8)
Accessible only from region: eu-west-1