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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:

[1]:
%%sh
torchx builtins
Found 11 builtin components:
  1. dist.ddp
  2. dist.spmd
  3. metrics.tensorboard
  4. serve.torchserve
  5. utils.binary
  6. utils.booth
  7. utils.copy
  8. utils.echo
  9. utils.python
 10. utils.sh
 11. utils.touch

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

[2]:
%%sh
torchx run utils.echo --msg "Hello :)"
torchx 2025-05-22 20:09:06 INFO     Tracker configurations: {}
torchx 2025-05-22 20:09:06 INFO     Checking for changes in workspace `file:///home/runner/work/torchx/torchx/docs/source`...
torchx 2025-05-22 20:09:06 INFO     To disable workspaces pass: --workspace="" from CLI or workspace=None programmatically.
torchx 2025-05-22 20:09:06 INFO     Workspace `file:///home/runner/work/torchx/torchx/docs/source` resolved to filesystem path `/home/runner/work/torchx/torchx/docs/source`
torchx 2025-05-22 20:11:36 INFO     Building workspace docker image (this may take a while)...
torchx 2025-05-22 20:11:36 INFO     Step 1/4 : ARG IMAGE
torchx 2025-05-22 20:11:36 INFO     Step 2/4 : FROM $IMAGE
torchx 2025-05-22 20:11:36 INFO      ---> c29b4bc733fb
torchx 2025-05-22 20:11:36 INFO     Step 3/4 : COPY . .
torchx 2025-05-22 20:11:44 INFO      ---> 9e6801d32fe0
torchx 2025-05-22 20:11:44 INFO     Step 4/4 : LABEL torchx.pytorch.org/version=0.8.0dev0
torchx 2025-05-22 20:11:44 INFO      ---> Running in 93e9096d07ad
torchx 2025-05-22 20:11:51 INFO      ---> Removed intermediate container 93e9096d07ad
torchx 2025-05-22 20:11:51 INFO      ---> 7c9e66c6dfbb
torchx 2025-05-22 20:11:51 INFO     [Warning] One or more build-args [WORKSPACE] were not consumed
torchx 2025-05-22 20:11:51 INFO     Successfully built 7c9e66c6dfbb
torchx 2025-05-22 20:11:51 INFO     Built new image `sha256:7c9e66c6dfbbdee0231d1c69a1186acbd45026ed75485b345a7bb8a0ba7ce57c` based on original image `ghcr.io/pytorch/torchx:0.8.0dev0` and changes in workspace `file:///home/runner/work/torchx/torchx/docs/source` for role[0]=echo.
torchx 2025-05-22 20:11:52 INFO     Waiting for the app to finish...
torchx 2025-05-22 20:11:52 INFO     Job finished: SUCCEEDED
echo/0 Hello :)
local_docker://torchx/echo-mh1j56hr0t1ml

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.

[3]:
%%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)
Writing my_app.py

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.

[4]:
%%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,
                ],
            )
        ],
    )
Writing my_component.py

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

[5]:
%%sh
torchx run --scheduler local_cwd my_component.py:greet --user "your name"
torchx 2025-05-22 20:11:52 INFO     Tracker configurations: {}
torchx 2025-05-22 20:11:52 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 2025-05-22 20:11:52 INFO     Log directory is: /tmp/torchx__qmcj97p
torchx 2025-05-22 20:11:52 INFO     Waiting for the app to finish...
greeter/0 Hello, your name!
torchx 2025-05-22 20:11:53 INFO     Job finished: SUCCEEDED
local_cwd://torchx/hello_world-qkmw761dst9lq

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/

[6]:
%%writefile Dockerfile.custom

FROM ghcr.io/pytorch/torchx:0.1.0rc1

ADD my_app.py .
Writing Dockerfile.custom

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

[7]:
%%sh
docker build -t my_app:latest -f Dockerfile.custom .
#0 building with "default" instance using docker driver

#1 [internal] load build definition from Dockerfile.custom
#1 transferring dockerfile: 99B done
#1 DONE 0.0s

#2 [internal] load metadata for ghcr.io/pytorch/torchx:0.1.0rc1
#2 DONE 1.0s

#3 [internal] load .dockerignore
#3 transferring context: 2B done
#3 DONE 0.0s

#4 [internal] load build context
#4 transferring context: 425B done
#4 DONE 0.0s

#5 [1/2] FROM ghcr.io/pytorch/torchx:0.1.0rc1@sha256:a738949601d82e7f100fa1efeb8dde0c35ce44c66726cf38596f96d78dcd7ad3
#5 resolve ghcr.io/pytorch/torchx:0.1.0rc1@sha256:a738949601d82e7f100fa1efeb8dde0c35ce44c66726cf38596f96d78dcd7ad3 done
#5 sha256:889a7173dcfeb409f9d88054a97ab2445f5a799a823f719a5573365ee3662b6f 0B / 189B 0.1s
#5 sha256:4bbfd2c87b7524455f144a03bf387c88b6d4200e5e0df9139a9d5e79110f89ca 0B / 26.70MB 0.1s
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#5 extracting sha256:4bbfd2c87b7524455f144a03bf387c88b6d4200e5e0df9139a9d5e79110f89ca 1.0s done
#5 sha256:143f801954310499daa44a8499a49797d2f282b5d56be601557ebe6cbf796907 113.25MB / 2.00GB 1.5s
#5 extracting sha256:d2e110be24e168b42c1a2ddbc4a476a217b73cccdba69cdcb212b812a88f5726
#5 sha256:30587ba7fd6bcbd1c883125d84517055b2d7f2d35a13faedbc8b15f94b900cc2 352B / 352B 1.5s done
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#5 sha256:909695be1d5003de345714eec2ca3020a48dd8f407fe918cbd47a8db73d7a233 0B / 341.29MB 1.7s
#5 sha256:f18d016c4ccc1c57c9e34cb119e1e1966287b08aa9b4d52a38b30815a56574b6 93.32MB / 1.71GB 1.9s
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#5 sha256:909695be1d5003de345714eec2ca3020a48dd8f407fe918cbd47a8db73d7a233 62.91MB / 341.29MB 2.2s
#5 extracting sha256:889a7173dcfeb409f9d88054a97ab2445f5a799a823f719a5573365ee3662b6f
#5 extracting sha256:889a7173dcfeb409f9d88054a97ab2445f5a799a823f719a5573365ee3662b6f done
#5 sha256:143f801954310499daa44a8499a49797d2f282b5d56be601557ebe6cbf796907 218.10MB / 2.00GB 2.5s
#5 sha256:909695be1d5003de345714eec2ca3020a48dd8f407fe918cbd47a8db73d7a233 97.52MB / 341.29MB 2.5s
#5 extracting sha256:6009a622672af862e3a3979ffd58a348f95208a4bc3b6f6cea2efda4e8390203 0.1s
#5 sha256:909695be1d5003de345714eec2ca3020a48dd8f407fe918cbd47a8db73d7a233 117.44MB / 341.29MB 2.6s
#5 sha256:f18d016c4ccc1c57c9e34cb119e1e1966287b08aa9b4d52a38b30815a56574b6 197.13MB / 1.71GB 2.8s
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#5 extracting sha256:6009a622672af862e3a3979ffd58a348f95208a4bc3b6f6cea2efda4e8390203 0.8s done
#5 sha256:f18d016c4ccc1c57c9e34cb119e1e1966287b08aa9b4d52a38b30815a56574b6 307.23MB / 1.71GB 3.6s
#5 sha256:909695be1d5003de345714eec2ca3020a48dd8f407fe918cbd47a8db73d7a233 255.85MB / 341.29MB 3.6s
#5 sha256:143f801954310499daa44a8499a49797d2f282b5d56be601557ebe6cbf796907 434.11MB / 2.00GB 4.0s
#5 sha256:909695be1d5003de345714eec2ca3020a48dd8f407fe918cbd47a8db73d7a233 281.02MB / 341.29MB 4.0s
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#5 sha256:f18d016c4ccc1c57c9e34cb119e1e1966287b08aa9b4d52a38b30815a56574b6 404.75MB / 1.71GB 4.3s
#5 sha256:909695be1d5003de345714eec2ca3020a48dd8f407fe918cbd47a8db73d7a233 341.29MB / 341.29MB 4.5s
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#5 sha256:f18d016c4ccc1c57c9e34cb119e1e1966287b08aa9b4d52a38b30815a56574b6 494.93MB / 1.71GB 5.0s
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#5 sha256:143f801954310499daa44a8499a49797d2f282b5d56be601557ebe6cbf796907 671.09MB / 2.00GB 5.7s
#5 sha256:f18d016c4ccc1c57c9e34cb119e1e1966287b08aa9b4d52a38b30815a56574b6 592.45MB / 1.71GB 5.7s
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#5 sha256:143f801954310499daa44a8499a49797d2f282b5d56be601557ebe6cbf796907 780.14MB / 2.00GB 6.4s
#5 sha256:f18d016c4ccc1c57c9e34cb119e1e1966287b08aa9b4d52a38b30815a56574b6 688.91MB / 1.71GB 6.4s
#5 sha256:143f801954310499daa44a8499a49797d2f282b5d56be601557ebe6cbf796907 901.78MB / 2.00GB 7.2s
#5 sha256:f18d016c4ccc1c57c9e34cb119e1e1966287b08aa9b4d52a38b30815a56574b6 793.77MB / 1.71GB 7.2s
#5 sha256:f18d016c4ccc1c57c9e34cb119e1e1966287b08aa9b4d52a38b30815a56574b6 881.85MB / 1.71GB 7.8s
#5 sha256:143f801954310499daa44a8499a49797d2f282b5d56be601557ebe6cbf796907 1.01GB / 2.00GB 7.9s
#5 sha256:f18d016c4ccc1c57c9e34cb119e1e1966287b08aa9b4d52a38b30815a56574b6 969.93MB / 1.71GB 8.4s
#5 sha256:143f801954310499daa44a8499a49797d2f282b5d56be601557ebe6cbf796907 1.11GB / 2.00GB 8.6s
#5 sha256:f18d016c4ccc1c57c9e34cb119e1e1966287b08aa9b4d52a38b30815a56574b6 1.07GB / 1.71GB 9.1s
#5 sha256:143f801954310499daa44a8499a49797d2f282b5d56be601557ebe6cbf796907 1.22GB / 2.00GB 9.3s
#5 sha256:f18d016c4ccc1c57c9e34cb119e1e1966287b08aa9b4d52a38b30815a56574b6 1.15GB / 1.71GB 9.7s
#5 sha256:143f801954310499daa44a8499a49797d2f282b5d56be601557ebe6cbf796907 1.34GB / 2.00GB 10.1s
#5 sha256:f18d016c4ccc1c57c9e34cb119e1e1966287b08aa9b4d52a38b30815a56574b6 1.24GB / 1.71GB 10.3s
#5 sha256:143f801954310499daa44a8499a49797d2f282b5d56be601557ebe6cbf796907 1.45GB / 2.00GB 10.8s
#5 sha256:f18d016c4ccc1c57c9e34cb119e1e1966287b08aa9b4d52a38b30815a56574b6 1.35GB / 1.71GB 11.0s
#5 sha256:143f801954310499daa44a8499a49797d2f282b5d56be601557ebe6cbf796907 1.56GB / 2.00GB 11.5s
#5 sha256:f18d016c4ccc1c57c9e34cb119e1e1966287b08aa9b4d52a38b30815a56574b6 1.44GB / 1.71GB 11.6s
#5 sha256:f18d016c4ccc1c57c9e34cb119e1e1966287b08aa9b4d52a38b30815a56574b6 1.53GB / 1.71GB 12.2s
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#5 extracting sha256:f18d016c4ccc1c57c9e34cb119e1e1966287b08aa9b4d52a38b30815a56574b6 5.0s
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#5 extracting sha256:909695be1d5003de345714eec2ca3020a48dd8f407fe918cbd47a8db73d7a233 10.2s
#5 extracting sha256:909695be1d5003de345714eec2ca3020a48dd8f407fe918cbd47a8db73d7a233 14.0s done
#5 extracting sha256:f119a6d0a466a041afbcb08344ff624b5c5ac5f68b93d33af4827529ea1a6800
#5 extracting sha256:f119a6d0a466a041afbcb08344ff624b5c5ac5f68b93d33af4827529ea1a6800 0.1s done
#5 extracting sha256:88d87059c913e67971846680d4032b75f96f599f8a67062f668fed6471fc2968
#5 extracting sha256:88d87059c913e67971846680d4032b75f96f599f8a67062f668fed6471fc2968 0.0s done
#5 DONE 82.4s

#6 [2/2] ADD my_app.py .
#6 DONE 0.0s

#7 exporting to image
#7 exporting layers
#7 exporting layers 4.3s done
#7 writing image sha256:f4494d87b7ff5144e422b30d8d55e9d2ee96f99cdc08f2f910e295ffcf509287 done
#7 naming to docker.io/library/my_app:latest done
#7 DONE 4.3s

We can then launch it on the local scheduler.

[8]:
%%sh
torchx run --scheduler local_docker my_component.py:greet --image "my_app:latest" --user "your name"
torchx 2025-05-22 20:13:25 INFO     Tracker configurations: {}
torchx 2025-05-22 20:13:25 INFO     Checking for changes in workspace `file:///home/runner/work/torchx/torchx/docs/source`...
torchx 2025-05-22 20:13:25 INFO     To disable workspaces pass: --workspace="" from CLI or workspace=None programmatically.
torchx 2025-05-22 20:13:25 INFO     Workspace `file:///home/runner/work/torchx/torchx/docs/source` resolved to filesystem path `/home/runner/work/torchx/torchx/docs/source`
torchx 2025-05-22 20:13:25 WARNING  failed to pull image my_app:latest, falling back to local: 404 Client Error for http+docker://localhost/v1.48/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 2025-05-22 20:13:25 INFO     Building workspace docker image (this may take a while)...
torchx 2025-05-22 20:13:25 INFO     Step 1/4 : ARG IMAGE
torchx 2025-05-22 20:13:25 INFO     Step 2/4 : FROM $IMAGE
torchx 2025-05-22 20:13:25 INFO      ---> f4494d87b7ff
torchx 2025-05-22 20:13:25 INFO     Step 3/4 : COPY . .
torchx 2025-05-22 20:13:30 INFO      ---> b6cc18616308
torchx 2025-05-22 20:13:30 INFO     Step 4/4 : LABEL torchx.pytorch.org/version=0.8.0dev0
torchx 2025-05-22 20:13:30 INFO      ---> Running in 716fbd24cef3
torchx 2025-05-22 20:13:34 INFO      ---> Removed intermediate container 716fbd24cef3
torchx 2025-05-22 20:13:34 INFO      ---> 25a8f24e036c
torchx 2025-05-22 20:13:34 INFO     [Warning] One or more build-args [WORKSPACE] were not consumed
torchx 2025-05-22 20:13:34 INFO     Successfully built 25a8f24e036c
torchx 2025-05-22 20:13:34 INFO     Built new image `sha256:25a8f24e036cd1253e642717bf490071b79ac555af11393489316932cedc0666` based on original image `my_app:latest` and changes in workspace `file:///home/runner/work/torchx/torchx/docs/source` for role[0]=greeter.
torchx 2025-05-22 20:13:34 INFO     Waiting for the app to finish...
greeter/0 Hello, your name!
torchx 2025-05-22 20:13:35 INFO     Job finished: SUCCEEDED
local_docker://torchx/hello_world-g3sxtbj9xv2x6c

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"

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