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Alternative workers

Uses cool Azure features (ACI) to run compute worker docker container in serverless environment:

Adds support for nvidia GPUs

Adds support for real time detailed results

Running

If you want to run everything in one line:

Note: this will make a /tmp/codalab directory

mkdir -p /tmp/codalab && docker run \
    -v /var/run/docker.sock:/var/run/docker.sock \
    -v /tmp/codalab:/tmp/codalab \
    -d \
    --name compute_worker \
    --env BROKER_URL=<queue broker url> \
    --restart unless-stopped \
    --log-opt max-size=50m \
    --log-opt max-file=3 \
    codalab/competitions-v1-compute-worker:latest

If you want to run using .env configuration:

Edit .env_sample and save it as .env

Make sure the temp directory you select is created and pass it in this command

docker run \
    -v /var/run/docker.sock:/var/run/docker.sock \
    -v /tmp/codalab:/tmp/codalab \
    -d \
    --name compute_worker \
    --env-file .env \
    --restart unless-stopped \
    --log-opt max-size=50m \
    --log-opt max-file=3 \
    codalab/competitions-v1-compute-worker:latest

If you want to run with GPU:

Make sure that you have nvidia-container-toolkit set up -- this also involves updating to Docker 19.03 and installing NVIDIA drivers.

Edit .env_sample and save it as .env. Make sure to uncomment USE_GPU=True.

Then make sure the temp directory you select is created and pass it in this command

docker run \
    -v /var/run/docker.sock:/var/run/docker.sock \
    -v /tmp/codalab:/tmp/codalab \
    -d \
    --name compute_worker \
    --env-file .env \
    --restart unless-stopped \
    --log-opt max-size=50m \
    --log-opt max-file=3 \
    --gpus all \
    codalab/competitions-v1-compute-worker:latest

To get output of the worker

$ docker logs -f compute_worker

To stop the worker

$ docker kill compute_worker

Development

To re-build the image:

docker build -t competitions-v1-compute-worker .

Updating the image

docker build -t codalab/competitions-v1-compute-worker:latest .
docker push codalab/competitions-v1-compute-worker

Special env flags

USE_GPU

Default False, does not pass --gpus all flag

Note: Also requires Docker v19.03 or greater, nvidia-container-toolkit, and NVIDIA drivers.

SUBMISSION_TEMP_DIR

Default /tmp/codalab

SUBMISSION_CACHE_DIR

Default /tmp/cache

CODALAB_HOSTNAME

Default socket.gethostname()

DONT_FINALIZE_SUBMISSION

Default False

Sometimes it may be useful to pause the compute worker and return instead of finishing a submission. This leaves the submission in a state where it hasn't been cleaned up yet and you can attempt to re-run it manually.

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  • Python 95.2%
  • Dockerfile 4.2%
  • Shell 0.6%