Sets a version in the model.

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Last Updated: Feb. 25, 2023

Access Instructions

Install the Google provider package into your Airflow environment.

Import the module into your DAG file and instantiate it with your desired params.


model_nameRequiredThe name of the Google Cloud ML Engine model that the version belongs to. (templated)
version_nameRequiredA name to use for the version being operated upon. (templated)
project_idThe Google Cloud project name to which MLEngine model belongs. If set to None or missing, the default project_id from the Google Cloud connection is used. (templated)
gcp_conn_idThe connection ID to use when fetching connection info.
delegate_toThe account to impersonate using domain-wide delegation of authority, if any. For this to work, the service account making the request must have domain-wide delegation enabled.
impersonation_chainOptional service account to impersonate using short-term credentials, or chained list of accounts required to get the access_token of the last account in the list, which will be impersonated in the request. If set as a string, the account must grant the originating account the Service Account Token Creator IAM role. If set as a sequence, the identities from the list must grant Service Account Token Creator IAM role to the directly preceding identity, with first account from the list granting this role to the originating account (templated).


Sets a version in the model.

See also

For more information on how to use this operator, take a look at the guide: Managing model versions

The model should be specified by model_name to be the default. The name of the version should be specified in the version_name parameter.

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