Bug Fix Issue #4603 Access problem#4604
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Is there any updates on this PR? is it blocked by anything? |
Signed-off-by: osobky <omar_sobky@hotmail.com>
Signed-off-by: harupy <hkawamura0130@gmail.com>
Signed-off-by: harupy <hkawamura0130@gmail.com>
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@OSobky Sorry for the late reply. Thanks for fixing this issue! I've pushed a commit to use a more conservative implementation. Does it look good to you? |
WeichenXu123
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Dec 6, 2021
| ) | ||
| finally: | ||
| shutil.rmtree(directory) | ||
| shutil.rmtree(directory, onerror=handle_readonly) |
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could you add a unit test to verify the handle_readonly works ?
Signed-off-by: harupy <hkawamura0130@gmail.com>
Signed-off-by: harupy <hkawamura0130@gmail.com>
Signed-off-by: harupy <hkawamura0130@gmail.com>
This was referenced Dec 7, 2021
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@harupy Sorry for the super late reply! however, the commit looks good |
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What changes are proposed in this pull request?
(Please fill in changes proposed in this fix)
as discussed in #4603 there is permission error whenever docker or kubernetes are used.
I added the
onerrorfunction. Whichshutil.rmtreewill use whenever there is permission error to give it access to removing the temp directory.How is this patch tested?
Successfully used MLflow projects with Docker and Kubernetes
(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