The root folder contains the necessary meta-files and references to submit a model to the challenge.
run.sh
first runs the setup.py
script, which installs the
SubmittableResNet
. This is a simple wrapper around
a BaseModel
and provides a function that returns a foolbox model, representing the model itself.
If one wants to submit a newly implemented model (call it MyModel
), the steps are as follows:
- Train
MyModel
and create a checkpoint with the flagsave_directory
. Note theCHECKPOINT_PATH
where the checkpoint can be found. The checkpoint needs to be added to the repository. - Change
SubmittableResNet
to useMyModel
as its base class. - If necessary, adjust
submit.py
(e.g. change the placeholder tensor if needed). In most cases however, this step should not be necessary. - Move the requirements of all dependencies into a new file called
requirements.txt
placed in the root folder. - Update
run.sh
and set theCHECKPOINT_PATH
as theglobal_checkpoint
argument - Optional: make sure everything works using a VM (with
nvidia-docker
installed) usingavc-test-model .
. This will test the accuracy of your model. - Head over to crowdai's GitLab and create a new repository. Add the new repository as a new remote of this repository, commit and push everything.
- Run
avc-submit .
to run the evaluation and submit the model.