"_prepare_to_copy" none intuitive step with sdk (no documentation)

[FlorianPydde]

[Enter feedback here] Why do we need to use "_prepare_to_copy" with the SDK. Could you expand on a it a bit ? What happens if don't use an MFLow model but sklearn or onnx ?

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Document Details

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• ID: c51f8710-600c-f87e-d5d1-134ac70efecf
• Version Independent ID: 3131da88-f396-ad16-e08e-b44681f852d8
• Content: Share models, components, and environments across workspaces with registries (preview) - Azure Machine Learning
• Content Source: articles/machine-learning/how-to-share-models-pipelines-across-workspaces-with-registries.md
• Service: machine-learning
• Sub-service: mlops
• GitHub Login: @ManojBableshwar
• Microsoft Alias: mabables

[RamanathanChinnappan-MSFT]

@spottedmahn

Thanks for your feedback! We will investigate and update as appropriate.

[RamanathanChinnappan-MSFT]

@FlorianPydde

I've delegated this to content author @ManojBableshwar to review and share his valuable insights.

[FlorianPydde]

Any update ?

[fkriti]

@FlorianPydde "_prepare_to_copy" was to share an Azure Mahine Learning asset (ex: model) from a Azure Machine Learning workspace to Azure Machine Learning registry. However, this syntax no longer exists and instead share() can be used.

# share the model from registry to workspace ml_client.models.share(name="nyc-taxi-model", version=1, registry_name=<registry_name>, share_with_name=<new-name>, share_with_version=<new-version>)

Check out this article to learn more