Polyaxon integrates with Tensorboard to visualize and debug deep learning models.
Polyaxon provides several ways for using Tensorboard, you can check the component on Polyaxon for more details.
Note: The default version
latesttargets a single run, and it has the same component’s content as
polyaxon run --hub tensorboard -P uuid=UUID
UUID is the uuid of the experiment to start a tensorboard for.
To provide a specific tag:
polyaxon run --hub tensorboard:multi-run -P uuids=UUID1,UUID2
To start the session on a different project
polyaxon run --hub tensorboard -p project-name
Go to the UI under the
polyaxon ops dashboard [-uid] [-p]
Or to get to the service directly:
polyaxon ops service [-uid] [-p]
Or to get the service in full-screen mode:
polyaxon ops service --external [-uid] [-p]
- Single-run tensorboard
- Multi-run tensorboard
You can provide more information before scheduling the service, like the queue, presets, …
polyaxon run --hub tensorboard -q agent-name/queue-name --presets preset-name1,preset-name2
polyaxon run --hub tensorboard -f path/to/preset.yaml
You can also provide a full operation manifest to customize the environment section, node selector, connections, initializers, resources requirements, …
version: 1.1 kind: operation hubRef: tensorboard runPatch: connections: [...] environment: ... container: resources: requests: memory: 300Mi
If you need to expose the
tensorboard component with your predefined configuration without requiring end-users to create operations,
we suggest that you clone the component and customize it.
On Polyaxon CE, you will need to create a new
.yaml file where you will host the content of the component, and users can either start new sessions using:
polyaxon run -f my-custom-tensorboard.yaml
polyaxon run --url https://path/to/my-custom-tensorboard.yaml
On Polyaxon Cloud or Polyaxon EE, you just need to add a new component hub.
The end users will need to run with
org-name/tensorboard instead of
polyaxon run --hub acme/tensorboard
Note: In order to use
:tagyou need to name the version
tensorboard versions can be found on the component hub
polyaxon hub ls -c tensorboard