pipelines/kfp: update component_from_app to respect resource allocations #15
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
This makes the kfp adapter handle resources correctly. For GPUs we use the standard KFP settings which is nvidia specific. https://github.com/kubeflow/pipelines/blob/master/sdk/python/kfp/dsl/_container_op.py#L357
If for some reason you need to set something other than
nvidia.com/gpuresource limit you'd have to manually update the resource spec as par of the pipeline.Test plan: