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1) Learn the basics of pyTorch in order to build sample submission that exercises the GPU.

2) Update form with edits from Ulli and Carolyn. 

Built pyTorch model that trains and uses a GPU

2) Built Miccai 2020 staging VM to create exact replica of our real challenge to deploy docker submission to3) Started working on CodaLab V2 and got Miccai 2020 challenge loaded into it. There are still some issues as during a submission it never registers a pass.

Planned for next month

1) Implement Docker image submission with real inference implemented on GPU remote machine.

2) Make edits to PR website as needed.

Hook up real data to GPU VM for docker submissions

23) Try to get issue with V2 sorted out.

Comments

Things that went well:

  • pyTorch is approachable and I'm getting the hang of it. Just trained my very first model. Essentially running this on the path\rad data is all we needmodel works and I created a docker image housing it and the steps to make the csv submission for the challenge.
  • Met with Eric Carmichael from CKCollab (https://www.linkedin.com/in/ericatckcollab/). He is the author of CodaLab V1 and V2 and runs a 6 person company at https://ckcollab.com/.

Things that could be improved:

  • My current understanding of pyTorch
  • Identifying proper Azure OSes that have GPU enabled software and identify which GPUs run on them.

...