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[BUG] R API: mlflow_create_model_version() has bug in source #4908

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dwh1142 opened this issue Oct 18, 2021 · 1 comment · Fixed by #5185
Closed
4 of 23 tasks

[BUG] R API: mlflow_create_model_version() has bug in source #4908

dwh1142 opened this issue Oct 18, 2021 · 1 comment · Fixed by #5185
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area/model-registry Model registry, model registry APIs, and the fluent client calls for model registry bug Something isn't working language/r R APIs and clients

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@dwh1142
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dwh1142 commented Oct 18, 2021

Thank you for submitting an issue. Please refer to our issue policy for additional information about bug reports. For help with debugging your code, please refer to Stack Overflow.

Please fill in this bug report template to ensure a timely and thorough response.

Willingness to contribute

The MLflow Community encourages bug fix contributions. Would you or another member of your organization be willing to contribute a fix for this bug to the MLflow code base?

  • Yes. I can contribute a fix for this bug independently.
  • Yes. I would be willing to contribute a fix for this bug with guidance from the MLflow community.
  • No. I cannot contribute a bug fix at this time.

System information

  • Have I written custom code (as opposed to using a stock example script provided in MLflow):
  • OS Platform and Distribution (e.g., Linux Ubuntu 16.04):
  • MLflow installed from (source or binary):
  • MLflow version (run mlflow --version):
  • Python version:
  • npm version, if running the dev UI:
  • Exact command to reproduce:

Describe the problem

This is trivial, but the function definition in the source code below appears wrong. It should be source = source instead of source = name.

File: model-registry.R

mlflow_create_model_version <- function(name, source, run_id = NULL,
                                        tags = NULL, run_link = NULL,
                                        description = NULL, client = NULL) {
  client <- resolve_client(client)

  response <- mlflow_rest(
    "model-versions",
    "create",
    client = client,
    verb = "POST",
    version = "2.0",
    data = list(
      name = name,
      source = name,
      run_id = run_id,
      run_link = run_link,
      description = description
    )
  )

  return(response$model_version)
}

Code to reproduce issue

mlflow_create_model_version(name="model", source="dbfs:/databricks/mlflow-tracking/2466938677462882/11ff1812a0384f118825a7838e82ba2d/artifacts")

Error : API request to endpoint 'model-versions/create' failed with error code 400. Reponse body: 'INVALID_PARAMETER_VALUE; Got an invalid source 'model'. Only DBFS locations are currently supported.'
Some(<code style = 'font-size:10p'> Error: API request to endpoint 'model-versions/create' failed with error code 400. Reponse body: 'INVALID_PARAMETER_VALUE; Got an invalid source 'model'. Only DBFS locations are currently supported.' </code>)
Error: API request to endpoint 'model-versions/create' failed with error code 400. Reponse body: 'INVALID_PARAMETER_VALUE; Got an invalid source 'model'. Only DBFS locations are currently supported.'

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 logging
  • area/build: Build and test infrastructure for MLflow
  • area/docs: MLflow documentation pages
  • area/examples: Example code
  • area/model-registry: Model Registry service, APIs, and the fluent client calls for Model Registry
  • area/models: MLmodel format, model serialization/deserialization, flavors
  • area/projects: MLproject format, project running backends
  • area/scoring: MLflow Model server, model deployment tools, Spark UDFs
  • area/server-infra: MLflow Tracking server backend
  • area/tracking: Tracking Service, tracking client APIs, autologging

Interface

  • area/uiux: Front-end, user experience, plotting, JavaScript, JavaScript dev server
  • area/docker: Docker use across MLflow's components, such as MLflow Projects and MLflow Models
  • area/sqlalchemy: Use of SQLAlchemy in the Tracking Service or Model Registry
  • area/windows: Windows support

Language

  • language/r: R APIs and clients
  • language/java: Java APIs and clients
  • language/new: Proposals for new client languages

Integrations

  • integrations/azure: Azure and Azure ML integrations
  • integrations/sagemaker: SageMaker integrations
  • integrations/databricks: Databricks integrations
@dwh1142 dwh1142 added the bug Something isn't working label Oct 18, 2021
@github-actions github-actions bot added area/model-registry Model registry, model registry APIs, and the fluent client calls for model registry integrations/databricks Databricks integrations language/r R APIs and clients labels Oct 18, 2021
@AveshCSingh AveshCSingh removed the integrations/databricks Databricks integrations label Oct 22, 2021
@bramrodenburg
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Fix proposed here: #5185

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