Cherry-pick the tensor-info bug fix into branch 1.14#4151
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harupy merged 1 commit intomlflow:branch-1.14from Mar 1, 2021
Merged
Cherry-pick the tensor-info bug fix into branch 1.14#4151harupy merged 1 commit intomlflow:branch-1.14from
harupy merged 1 commit intomlflow:branch-1.14from
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…#4147) * Improve Signed-off-by: Arjun DCunha <arjun.dcunha@databricks.com> * Comments Signed-off-by: Arjun DCunha <arjun.dcunha@databricks.com> * LINT Signed-off-by: Arjun DCunha <arjun.dcunha@databricks.com> * indent Signed-off-by: Arjun DCunha <arjun.dcunha@databricks.com> * Small improve Signed-off-by: Arjun DCunha <arjun.dcunha@databricks.com> * Tomas comments Signed-off-by: Arjun DCunha <arjun.dcunha@databricks.com> * retrigger tets Signed-off-by: Arjun DCunha <arjun.dcunha@databricks.com> * PLease Signed-off-by: Arjun DCunha <arjun.dcunha@databricks.com> Signed-off-by: harupy <17039389+harupy@users.noreply.github.com>
smurching
approved these changes
Mar 1, 2021
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What changes are proposed in this pull request?
Cherry-picks #4147 into
branch-1.14How is this patch tested?
(Details)
Release Notes
Is 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: Local serving, model deployment tools, spark UDFsarea/server-infra: MLflow server, JavaScript dev serverarea/tracking: Tracking Service, tracking client APIs, autologgingInterface
area/uiux: Front-end, user experience, JavaScript, plottingarea/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