Using compute target name as a PipelineParameter
Nobody has claimed this yet.
Assessment
- Difficulty
- 5/5
- Estimated time
- Over a week
- Newbie friendliness
- 20/100
- Issue type
- Feature
- Clarity
- Needs clarification
- Activity status
- Stale
- Tech stack
- azure, python
- Domain
- cloud, machine-learning
Research direction
Start with the shown Workspace, PipelineParameter, and ComputeTarget usage in the orchestrating notebook, then trace Azure ML pipeline publication and parameter-passing entry points. Done means establishing whether a published pipeline supports a dynamic compute target name and recording the supported behavior or limitation.
Written by the indexing model from the issue text.
Description
I have a query regarding the behavior of the azureml.pipeline.core.graph.PipelineParameter class. As its name suggests, the PipelineParameter is employed to dynamically pass values to our pipeline after its publication. My objective is to convey dynamic values to the orchestrating notebook. For instance, I intend to provide the compute target name dynamically once the pipeline is published. What I am implying is that users can specify the compute name afterwards, eliminating the need for hardcoding the same.
The code i tried:
ws = Workspace.from_config()
compute_para = PipelineParameter(name="compute_parameter", default_value="vm1-ig-04-aml-in-cappa-d")
compute_target = ComputeTarget(workspace=ws, name=compute_para.default_value)
As I have assigned the default value of the compute name to the compute target, it is currently utilizing only the default value. My inquiry pertains to the existence of any available functionality within Azure that allows for the dynamic transmission of values to the orchestrating notebook.
Let me know if you need more info.
- Dominant language
- Jupyter Notebook
- Stars
- 4.4k
- Forks
- 2.6k
- PR merge metrics
- No merged PRs in 30d
Contributor guide
No contributing guide indexed for this repository
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
More from Azure/MachineLearningNotebooks
-
Difficulty 2/5 1-3 hours Newbie friendliness 72/100
Azure/MachineLearningNotebooks#1975 · 1 comment ·
-
duplicates Open
Difficulty 1/5 Under an hour Newbie friendliness 68/100
Azure/MachineLearningNotebooks#1960 ·
-
machine Open
Difficulty 5/5 Over a week Newbie friendliness 10/100
Azure/MachineLearningNotebooks#1987 ·
-
Difficulty 5/5 Over a week Newbie friendliness 25/100
Azure/MachineLearningNotebooks#1985 · 1 comment ·
-
Difficulty 3/5 1-2 days Newbie friendliness 35/100
Azure/MachineLearningNotebooks#1981 · 1 reaction ·
All issues in Azure/MachineLearningNotebooks
Similar issues
-
enhancement
Difficulty 2/5 1-3 hours Newbie friendliness 75/100
palladius/rails8-app-on-gcp#141 · 1 comment ·
-
Difficulty 1/5 Under an hour Newbie friendliness 75/100
-
Difficulty 1/5 Under an hour Newbie friendliness 85/100
-
documentation improve or update documentation priority/low triage
Difficulty 2/5 Half a day Newbie friendliness 86/100
warpdotdev/docs#782 · 1 comment ·
-
customer-reported question
Difficulty 1/5 Under an hour Newbie friendliness 80/100
Azure/awesome-azd#1017 ·