[BUG] PermissionError: [WinError 5] Access is denied with Docker or Kubernetes #4603
Closed
4 of 23 tasks
Labels
area/docker
Docker use anywhere, such as MLprojects and MLmodels
area/projects
MLproject format, project running backends
area/windows
Issue is unique to windows.
bug
Something isn't working
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Willingness to contribute
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System information
mlflow --version
): 1.18.0mlflow run examples/docker -P alpha=0.5
ormlflow run examples/docker -P alpha=0.5 --backend kubernetes --backend-config kubernetes_config.json
Describe the problem
Describe the problem clearly here. Include descriptions of the expected behavior and the actual behavior.
I work on my company laptop which may be the reason this bug happened. I have been trying to use MLflow projects in Docker environment or with Kubernetes as backend. However when I try to run it, it produces
PermissionError
. The error is produced whenever MLflow tries to remove the temp directory it created in_create_docker_build_ctx
function. this is the exact line that produces the errormlflow/mlflow/projects/docker.py
Line 117 in 221fedc
Code to reproduce issue
Provide a reproducible test case that is the bare minimum necessary to generate the problem.
Clone MLflow repository and try to run the docker container with the following commands:
mlflow run examples/docker -P alpha=0.5
mlflow run examples/docker -P alpha=0.5 --backend kubernetes --backend-config kubernetes_config.json
Other info / logs
Include any logs or source code that would be helpful to diagnose the problem. If including tracebacks, please include the full traceback. Large logs and files should be attached.
What component(s), interfaces, languages, and integrations does this bug 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 integrationsThe text was updated successfully, but these errors were encountered: