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https://github.com/iterait/shepherd

Provides access to computation resources on a single machine through a REST API
https://github.com/iterait/shepherd

gpu queue worker

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

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# Shepherd

[![CircleCI](https://circleci.com/gh/iterait/shepherd.png?style=shield&circle-token=1045f8994f4f35d81130331600a0683e16bbb4f9)](https://circleci.com/gh/iterait/shepherd/tree/master)

Provides access to computation resources on a single machine.

## Development Guide

### Prerequisites

1. Install dependencies with `pip install .`
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`

### 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 `/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
`/outputs.json`

### Running Tests

First, install the test requirements `pip install '.[tests]'`.
The test suite can be run with `python setup.py test`.

### Running Stress Tests

First, install the test requirements `pip install '.[tests]'`.

To launch stress test, run:
```
docker-compose -f examples/docker/docker-compose-sandbox.yml up -d
shepherd -c tests/stress/shepherd-bare.yml
molotov tests/stress/loadtest.py -p 2 -w 10 -d 60 -xv
```
You can modify stress test arguments: `-p` (number of processes), `-w` (number of workers) and
`-d` (number of seconds to run the test).

You can also run stress test with time measurements:
```
molotov --use-extension tests/stress/measure_time.py --max-runs 10 tests/stress/loadtest.py
```