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[FR] Raise an exception if mlflow.get_artifact_uri() used outside of an active run #12576

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mohammedsalah-ai opened this issue Jul 4, 2024 · 1 comment
Open
3 of 22 tasks

[FR] Raise an exception if mlflow.get_artifact_uri() used outside of an active run #12576

mohammedsalah-ai opened this issue Jul 4, 2024 · 1 comment
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area/artifacts Artifact stores and artifact logging area/model-registry Model registry, model registry APIs, and the fluent client calls for model registry area/models MLmodel format, model serialization/deserialization, flavors enhancement New feature or request good first issue Good for newcomers help wanted We would like help from the community to add this support

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@mohammedsalah-ai
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Willingness to contribute

No. I cannot contribute this feature at this time.

Proposal Summary

It's just to avoid new users having the problem that I went through which is detailed in issue #12564

Motivation

What is the use case for this feature?

just to avoid confusion

Why is this use case valuable to support for MLflow users in general?

ensuring control over mlflow so it won't create runs unexpectedly

Details

again all details to understand the issue it outlined here issue #12564

What component(s) does this bug affect?

  • area/artifacts: Artifact stores and artifact logging
  • area/build: Build and test infrastructure for MLflow
  • area/deployments: MLflow Deployments client APIs, server, and third-party Deployments integrations
  • area/docs: MLflow documentation pages
  • area/examples: Example code
  • area/model-registry: Model Registry service, APIs, and the fluent client calls for Model Registry
  • area/models: MLmodel format, model serialization/deserialization, flavors
  • area/recipes: Recipes, Recipe APIs, Recipe configs, Recipe Templates
  • area/projects: MLproject format, project running backends
  • area/scoring: MLflow Model server, model deployment tools, Spark UDFs
  • area/server-infra: MLflow Tracking server backend
  • area/tracking: Tracking Service, tracking client APIs, autologging

What interface(s) does this bug affect?

  • area/uiux: Front-end, user experience, plotting, JavaScript, JavaScript dev server
  • area/docker: Docker use across MLflow's components, such as MLflow Projects and MLflow Models
  • area/sqlalchemy: Use of SQLAlchemy in the Tracking Service or Model Registry
  • area/windows: Windows support

What language(s) does this bug affect?

  • language/r: R APIs and clients
  • language/java: Java APIs and clients
  • language/new: Proposals for new client languages

What integration(s) does this bug affect?

  • integrations/azure: Azure and Azure ML integrations
  • integrations/sagemaker: SageMaker integrations
  • integrations/databricks: Databricks integrations
@mohammedsalah-ai mohammedsalah-ai added the enhancement New feature or request label Jul 4, 2024
@github-actions github-actions bot added area/artifacts Artifact stores and artifact logging area/model-registry Model registry, model registry APIs, and the fluent client calls for model registry area/models MLmodel format, model serialization/deserialization, flavors labels Jul 4, 2024
@WeichenXu123 WeichenXu123 added good first issue Good for newcomers help wanted We would like help from the community to add this support labels Jul 4, 2024
@karoel2
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karoel2 commented Jul 6, 2024

Hi,
I'm here because of the "good first issue" tag. After reviewing the code for a while, I believe the proposed solution of raising an exception will not work.

When using mlflow.get_artifact_uri with artifact_path as argument (which is the case in mentioned issue #12564 ) , the intended behavior of this function is to create a new run if there is no active run:

If no run is active, this method will create a new active run.
Reference: mlflow/tracking/fluent.py#L1794-L1847

To solve this bug, either the intended behavior of this function needs to be changed, or it needs to be debugged to determine why it is not working when creating a new run.

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area/artifacts Artifact stores and artifact logging area/model-registry Model registry, model registry APIs, and the fluent client calls for model registry area/models MLmodel format, model serialization/deserialization, flavors enhancement New feature or request good first issue Good for newcomers help wanted We would like help from the community to add this support
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@WeichenXu123 @karoel2 @mohammedsalah-ai