Introduce get_parent_run fluent API #8493
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Signed-off-by: Ann Zhang <ann.zhang@databricks.com>
Signed-off-by: Ann Zhang <ann.zhang@databricks.com>
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This looks great @annzhang-db . Can we also extend this to the mlflow client APIs (see mlflow/tracking/client.py)? Similar to the way we call MlflowClient().get_run(run_id), it would be helpful to call MlflowClient().get_parent_run(run_id).
sunishsheth2009
approved these changes
May 23, 2023
mlflow/tracking/fluent.py
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| @@ -518,6 +518,43 @@ def get_run(run_id: str) -> Run: | |||
| return MlflowClient().get_run(run_id) | |||
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| def get_parent_run(run_id: str) -> Optional[Run]: | |||
| """ | |||
| Gets the parent run for the given run id. | |||
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Gets the parent run for the given run id if one exists
harupy
reviewed
May 23, 2023
mlflow/tracking/fluent.py
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| child_run = MlflowClient().get_run(run_id) | ||
| parent_run_id = child_run.data.tags.get(MLFLOW_PARENT_RUN_ID) | ||
| if parent_run_id is None: | ||
| return None | ||
| return MlflowClient().get_run(parent_run_id) |
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Suggested change
| child_run = MlflowClient().get_run(run_id) | |
| parent_run_id = child_run.data.tags.get(MLFLOW_PARENT_RUN_ID) | |
| if parent_run_id is None: | |
| return None | |
| return MlflowClient().get_run(parent_run_id) | |
| client = MlflowClient() | |
| child_run = client.get_run(run_id) | |
| parent_run_id = child_run.data.tags.get(MLFLOW_PARENT_RUN_ID) | |
| if parent_run_id is None: | |
| return None | |
| return client.get_run(parent_run_id) |
Can we reuse the client?
harupy
reviewed
May 23, 2023
tests/tracking/fluent/test_fluent.py
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| def test_get_parent_run(): | ||
| parent_run_id = mlflow.start_run().info.run_id | ||
| mlflow.log_param("a", 1) | ||
| mlflow.log_metric("b", 2.0) | ||
| child_run_id = mlflow.start_run(nested=True).info.run_id | ||
| mlflow.end_run() | ||
| mlflow.end_run() | ||
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| parent_run = mlflow.get_parent_run(child_run_id) | ||
| assert parent_run.info.run_id == parent_run_id | ||
| assert parent_run.data.metrics == {"b": 2.0} | ||
| assert parent_run.data.params == {"a": "1"} |
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Can we also add a test that ensures get_parent_run returns None if the parent run doesn't exist?
harupy
approved these changes
May 23, 2023
harupy
reviewed
May 23, 2023
tests/tracking/fluent/test_fluent.py
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| parent_run_id = mlflow.start_run().info.run_id | ||
| mlflow.log_param("a", 1) | ||
| mlflow.log_metric("b", 2.0) | ||
| child_run_id = mlflow.start_run(nested=True).info.run_id | ||
| mlflow.end_run() | ||
| mlflow.end_run() |
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Suggested change
| parent_run_id = mlflow.start_run().info.run_id | |
| mlflow.log_param("a", 1) | |
| mlflow.log_metric("b", 2.0) | |
| child_run_id = mlflow.start_run(nested=True).info.run_id | |
| mlflow.end_run() | |
| mlflow.end_run() | |
| with mlflow.start_run() as parent: | |
| mlflow.log_param("a", 1) | |
| mlflow.log_metric("b", 2.0) | |
| with mlflow.start_run(nested=True) as child: |
Can we use with mlflow.start_run()?
WeichenXu123
approved these changes
May 23, 2023
Signed-off-by: Ann Zhang <ann.zhang@databricks.com>
Signed-off-by: Ann Zhang <ann.zhang@databricks.com>
prithvikannan
approved these changes
May 23, 2023
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Awesome work @annzhang-db ! Just one small nit comment and a test
mlflow/tracking/client.py
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| with mlflow.start_run(nested=True) as child_run: | ||
| child_run_id = child_run.info.run_id | ||
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| parent_run = mlflow.get_parent_run(child_run_id) |
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can we update this to demonstrate the MlflowClient approach? something like
parent_run = MlflowClient().get_parent_run
| child_run_id: 7d175204675e40328e46d9a6a5a7ee6a | ||
| parent_run_id: 8979459433a24a52ab3be87a229a9cdf | ||
| """ | ||
| return MlflowClient().get_parent_run(run_id) |
Signed-off-by: Ann Zhang <ann.zhang@databricks.com>
Signed-off-by: Ann Zhang <ann.zhang@databricks.com>
Signed-off-by: Ann Zhang <ann.zhang@databricks.com>
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Related Issues/PRs
#xxxWhat changes are proposed in this pull request?
How is this patch tested?
Does this PR change the documentation?
Release Notes
Is this a user-facing change?
Introduce
mlflow.get_parent_run()fluent APIWhat 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/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/breaking-change- The PR will be mentioned in the "Breaking Changes" sectionrn/none- No description will be included. The PR will be mentioned only by the PR number in the "Small Bugfixes and Documentation Updates" 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