custom_components.md

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Custom Components

This is a guide on how to build a simple app and custom component spec and launch it via two different schedulers.

See the Quickstart Guide for installation and basic usage.

Builtins

Before writing a custom component, check if any of the builtin components satisfy your needs. TorchX provides a number of builtin components with premade images. You can discover them via:

torchx builtins

You can use these either from the CLI, from a pipeline or programmatically like you would any other component.

torchx run utils.echo --msg "Hello :)"

Hello World

Lets start off with writing a simple "Hello World" python app. This is just a normal python program and can contain anything you'd like.

Note

This example uses Jupyter Notebook `%%writefile` to create local files for example purposes. Under normal usage you would have these as standalone files.

%%writefile my_app.py

import sys
import argparse

def main(user: str) -> None:
    print(f"Hello, {user}!")

if __name__ == "__main__":
    parser = argparse.ArgumentParser(
        description="Hello world app"
    )
    parser.add_argument(
        "--user",
        type=str,
        help="the person to greet",
        required=True,
    )
    args = parser.parse_args(sys.argv[1:])

    main(args.user)

Now that we have an app we can write the component file for it. This function allows us to reuse and share our app in a user friendly way.

We can use this component from the torchx cli or programmatically as part of a pipeline.

%%writefile my_component.py

import torchx.specs as specs

def greet(user: str, image: str = "my_app:latest") -> specs.AppDef:
    return specs.AppDef(
        name="hello_world",
        roles=[
            specs.Role(
                name="greeter",
                image=image,
                entrypoint="python",
                args=[
                    "-m", "my_app",
                    "--user", user,
                ],
            )
        ],
    )

We can execute our component via torchx run. The local_cwd scheduler executes the component relative to the current directory.

torchx run --scheduler local_cwd my_component.py:greet --user "your name"

If we want to run in other environments, we can build a Docker container so we can run our component in Docker enabled environments such as Kubernetes or via the local Docker scheduler.

Note

This requires Docker installed and won't work in environments such as Google Colab. If you have not done so already follow the install instructions on: [https://docs.docker.com/get-docker/](https://docs.docker.com/get-docker/)

%%writefile Dockerfile.custom

FROM ghcr.io/pytorch/torchx:0.1.0rc1

ADD my_app.py .

Once we have the Dockerfile created we can create our docker image.

docker build -t my_app:latest -f Dockerfile.custom .

We can then launch it on the local scheduler.

torchx run --scheduler local_docker my_component.py:greet --image "my_app:latest" --user "your name"

If you have a Kubernetes cluster you can use the Kubernetes scheduler to launch this on the cluster instead.

$ docker push my_app:latest
$ torchx run --scheduler kubernetes my_component.py:greet --image "my_app:latest" --user "your name"