Provides access to computation resources on a single machine through a REST API
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Provides access to computation resources on a single machine.

Development Guide


  1. Install dependencies with pip install -r requirements.txt
  2. Make sure you have Docker installed and that your user has permissions to use it
  3. If you intend to run computations on a GPU, install also nvidia-docker2

Running Tests

The test suite can be run with python test.

Launching the Shepherd

First, you need to have a Docker registry and a Minio server running. The easiest way to achieve this is to use the Docker Compose example:

docker-compose -f examples/docker/docker-compose-sandbox.yml up -d

Second, you need a configuration file. Again, examples found in the examples/configs/ folder are a great starting point. Feel free to pick one of those and edit it to your needs.

Finally, you need to run the following command to start the shepherd:

shepherd -c examples/configs/shepherd-docker-cpu.yml

Be sure to adjust the command line parameters according to your needs (-h is your host address, -p is the port number where the shepherd API server listens and -c is the path to the configuration file).

After launching the shepherd, there will be an HTTP API available on the configured port that can be used to control the shepherd.

Processing a Request Directly

To process a request for debugging purposes, you need to:

  • choose a request id
  • create a bucket on your Minio server with a name same as your request id
  • put the payload (input for the model) in <yourbucket>/inputs/input.json
  • invoke the /start-job API endpoint with your chosen request id
  • after the job is processed, the result should be stored in Minio, in <yourbucket>/outputs.json