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.

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.


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


import sys
import argparse

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

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


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.


import torchx.specs as specs

def greet(user: str, image: str = "my_app:latest") -> specs.AppDef:
    return specs.AppDef(
                    "-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 --user "your name"
torchx 2022-06-16 01:14:53 INFO     Log directory not set in scheduler cfg. Creating a temporary log dir that will be deleted on exit. To preserve log directory set the `log_dir` cfg option
torchx 2022-06-16 01:14:53 INFO     Log directory is: /tmp/torchx_nzcc2z92
torchx 2022-06-16 01:14:53 INFO     Waiting for the app to finish...
greeter/0 Hello, your name!
torchx 2022-06-16 01:14:54 INFO     Job finished: SUCCEEDED

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.


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:

%%writefile Dockerfile.custom


Writing Dockerfile.custom

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

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

Step 1/2 : FROM
0.1.0rc1: Pulling from pytorch/torchx
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889a7173dcfe: Verifying Checksum
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f119a6d0a466: Verifying Checksum
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4bbfd2c87b75: Pull complete
f18d016c4ccc: Verifying Checksum
f18d016c4ccc: Download complete
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143f80195431: Download complete
d2e110be24e1: Pull complete
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Digest: sha256:a738949601d82e7f100fa1efeb8dde0c35ce44c66726cf38596f96d78dcd7ad3
Status: Downloaded newer image for
 ---> 3dbec59e8049
Step 2/2 : ADD .
 ---> 11b996417979
Successfully built 11b996417979
Successfully tagged my_app:latest

We can then launch it on the local scheduler.

torchx run --scheduler local_docker --image "my_app:latest" --user "your name"
torchx 2022-06-16 01:17:02 INFO     Checking for changes in workspace `file:///home/runner/work/torchx/torchx/docs/source`...
torchx 2022-06-16 01:17:02 INFO     To disable workspaces pass: --workspace="" from CLI or workspace=None programmatically.
torchx 2022-06-16 01:17:03 WARNING  failed to pull image my_app:latest, falling back to local: 404 Client Error for http+docker://localhost/v1.41/images/create?tag=latest&fromImage=my_app: Not Found ("pull access denied for my_app, repository does not exist or may require 'docker login': denied: requested access to the resource is denied")
torchx 2022-06-16 01:17:10 INFO     Built new image `sha256:2eeaddea522b1922d57f1d34bfdf4c7ca9ae308b4e1278fa9e2df69bc7ee57c4` based on original image `my_app:latest` and changes in workspace `file:///home/runner/work/torchx/torchx/docs/source` for role[0]=greeter.
torchx 2022-06-16 01:17:11 INFO     Waiting for the app to finish...
greeter/0 Hello, your name!
torchx 2022-06-16 01:17:12 INFO     Job finished: SUCCEEDED

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 --image "my_app:latest" --user "your name"


TorchX also provides a number of builtin components with premade images. You can discover them via:

torchx builtins
Found 10 builtin components:
  1. serve.torchserve
  2. utils.binary
  3. utils.booth
  4. utils.copy
  5. utils.echo
  6. utils.python
  8. utils.touch
  9. dist.ddp
 10. metrics.tensorboard

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 :)"
torchx 2022-06-16 01:17:16 INFO     Checking for changes in workspace `file:///home/runner/work/torchx/torchx/docs/source`...
torchx 2022-06-16 01:17:16 INFO     To disable workspaces pass: --workspace="" from CLI or workspace=None programmatically.
torchx 2022-06-16 01:19:00 INFO     Built new image `sha256:46368bb0078abdedd3364c831b8461609cd55cae44f26d00296569ab0e88b6e1` based on original image `` and changes in workspace `file:///home/runner/work/torchx/torchx/docs/source` for role[0]=echo.
torchx 2022-06-16 01:19:01 INFO     Waiting for the app to finish...
echo/0 Hello :)
torchx 2022-06-16 01:19:02 INFO     Job finished: SUCCEEDED


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