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Add mlflow_version to Java model spec to fix serving behavior #5576
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Signed-off-by: dbczumar <corey.zumar@databricks.com>
Signed-off-by: dbczumar <corey.zumar@databricks.com>
Signed-off-by: dbczumar <corey.zumar@databricks.com>
Signed-off-by: dbczumar <corey.zumar@databricks.com>
@@ -51,7 +51,7 @@ public Predictor load(String modelRootPath) throws PredictorLoadingException { | |||
} catch (IOException e) { | |||
throw new PredictorLoadingException( | |||
"Failed to load the model configuration at the specified path. Please ensure that" | |||
+ " this is the path to the root directory of a valid MLflow model"); | |||
+ " this is the path to the root directory of a valid MLflow model", e); |
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Extended PredictorLoadingException
to include the root cause exception for easier debugging next time
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LGTM!
* @param message The user-readable error message associated with this exception | ||
* @param ex The causal exception to include in the PredictorLoadingException | ||
*/ | ||
public PredictorLoadingException(String message, Exception ex) { |
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excellent! :)
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On behalf of our future selves, thank you for adding in stack trace surfacing.
LGTM!
…#5576) * Add mlflow version to java model Signed-off-by: dbczumar <corey.zumar@databricks.com> * Add exception content Signed-off-by: dbczumar <corey.zumar@databricks.com> * Indentation Signed-off-by: dbczumar <corey.zumar@databricks.com> * Add exc info elsewhere Signed-off-by: dbczumar <corey.zumar@databricks.com> * Indent Signed-off-by: dbczumar <corey.zumar@databricks.com>
What changes are proposed in this pull request?
Add mlflow_version to Java model spec to fix serving behavior
How is this patch tested?
Existing coverage + new coverage to make sure models are loaded properly even if they lack
mlflow_version
Does this PR change the documentation?
ci/circleci: build_doc
check. If it's successful, proceed to thenext step, otherwise fix it.
Details
on the right to open the job page of CircleCI.Artifacts
tab.docs/build/html/index.html
.Release Notes
Add
mlflow_version
field to Java model specIs this a user-facing change?
(Details in 1-2 sentences. You can just refer to another PR with a description if this PR is part of a larger 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/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/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