Add note to docstring for fluent API set_experiment #10795
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Signed-off-by: Ben Wilson <benjamin.wilson@databricks.com>
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Signed-off-by: mlflow-automation <mlflow-automation@users.noreply.github.com>
B-Step62
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Jan 9, 2024
mlflow/tracking/fluent.py
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| @@ -91,6 +91,9 @@ def set_experiment( | |||
| name via `experiment_name` or by ID via `experiment_id`. The experiment name and ID cannot | |||
| both be specified. | |||
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| .. note:: If the experiment being set by name does not exist, a new experiment will be created with the | |||
| given name. After the experiment has been created, it will be set as the active experiment. | |||
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| :param experiment_name: Case sensitive name of the experiment to be activated. If an experiment | |||
| with this name does not exist, a new experiment wth this name is | |||
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nit: Can we remove the same description from param instead?
BenWilson2
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Jan 9, 2024
Signed-off-by: Ben Wilson <39283302+BenWilson2@users.noreply.github.com>
Good idea! :D |
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Related Issues/PRs
#xxxWhat changes are proposed in this pull request?
Adds a clear note about the behavior of set_experiment in the fluent API due to reported confusion about the behavior.
How is this PR tested?
Does this PR require documentation update?
Release Notes
Is this a user-facing change?
What component(s), interfaces, languages, and integrations does this PR affect?
Components
area/artifacts: Artifact stores and artifact loggingarea/build: Build and test infrastructure for MLflowarea/deployments: MLflow Deployments client APIs, server, and third-party Deployments integrationsarea/docs: MLflow documentation pagesarea/examples: Example codearea/model-registry: Model Registry service, APIs, and the fluent client calls for Model Registryarea/models: MLmodel format, model serialization/deserialization, flavorsarea/recipes: Recipes, Recipe APIs, Recipe configs, Recipe Templatesarea/projects: MLproject format, project running backendsarea/scoring: MLflow Model server, model deployment tools, Spark UDFsarea/server-infra: MLflow Tracking server backendarea/tracking: Tracking Service, tracking client APIs, autologgingInterface
area/uiux: Front-end, user experience, plotting, JavaScript, JavaScript dev serverarea/docker: Docker use across MLflow's components, such as MLflow Projects and MLflow Modelsarea/sqlalchemy: Use of SQLAlchemy in the Tracking Service or Model Registryarea/windows: Windows supportLanguage
language/r: R APIs and clientslanguage/java: Java APIs and clientslanguage/new: Proposals for new client languagesIntegrations
integrations/azure: Azure and Azure ML integrationsintegrations/sagemaker: SageMaker integrationsintegrations/databricks: Databricks integrationsHow should the PR be classified in the release notes? Choose one:
rn/none- No description will be included. The PR will be mentioned only by the PR number in the "Small Bugfixes and Documentation Updates" sectionrn/breaking-change- The PR will be mentioned in the "Breaking Changes" sectionrn/feature- A new user-facing feature worth mentioning in the release notesrn/bug-fix- A user-facing bug fix worth mentioning in the release notesrn/documentation- A user-facing documentation change worth mentioning in the release notes