Create or update trained model aliases API
editCreate or update trained model aliases API
editCreates or updates a trained model alias.
A trained model alias is a logical name used to reference a single trained model.
Request
editPUT _ml/trained_models/<model_id>/model_aliases/<model_alias>
Prerequisites
editRequires the manage_ml
cluster privilege. This privilege is included in the
machine_learning_admin
built-in role.
Description
editYou can use aliases instead of trained model identifiers to make it easier to reference your models. For example, you can use aliases in inference aggregations and processors.
An alias must be unique and refer to only a single trained model. However, you can have multiple aliases for each trained model.
API Restrictions:
- You are not allowed to update an alias such that it references a different trained model ID and the model uses a different type of data frame analytics. For example, this situation occurs if you have a trained model for regression analysis and a trained model for classification analysis; you cannot reassign an alias from one type of trained model to another.
-
You cannot update an alias from a
pytorch
model and a data frame analytics model. -
You cannot update the alias from a deployed
pytorch
model to one not currently deployed.
If you use this API to update an alias and there are very few input fields in common between the old and new trained models for the model alias, the API returns a warning.
Path parameters
edit-
model_alias
- (Required, string) The alias to create or update. This value cannot end in numbers.
-
model_id
- (Required, string) The identifier for the trained model that the alias refers to.
Query parameters
edit-
reassign
-
(Optional, boolean)
Specifies whether the alias gets reassigned to the specified trained model if it
is already assigned to a different model. If the alias is already assigned and
this parameter is
false
, the API returns an error. Defaults tofalse
.
Examples
editCreate a trained model alias
editThe following example shows how to create an alias (flight_delay_model
) for a
trained model (flight-delay-prediction-1574775339910
):
resp = client.ml.put_trained_model_alias( model_id="flight-delay-prediction-1574775339910", model_alias="flight_delay_model", ) print(resp)
response = client.ml.put_trained_model_alias( model_id: 'flight-delay-prediction-1574775339910', model_alias: 'flight_delay_model' ) puts response
const response = await client.ml.putTrainedModelAlias({ model_id: "flight-delay-prediction-1574775339910", model_alias: "flight_delay_model", }); console.log(response);
PUT _ml/trained_models/flight-delay-prediction-1574775339910/model_aliases/flight_delay_model
Update a trained model alias
editThe following example shows how to reassign an alias (flight_delay_model
) to a
different trained model (flight-delay-prediction-1580004349800
):
resp = client.ml.put_trained_model_alias( model_id="flight-delay-prediction-1580004349800", model_alias="flight_delay_model", reassign=True, ) print(resp)
response = client.ml.put_trained_model_alias( model_id: 'flight-delay-prediction-1580004349800', model_alias: 'flight_delay_model', reassign: true ) puts response
const response = await client.ml.putTrainedModelAlias({ model_id: "flight-delay-prediction-1580004349800", model_alias: "flight_delay_model", reassign: "true", }); console.log(response);
PUT _ml/trained_models/flight-delay-prediction-1580004349800/model_aliases/flight_delay_model?reassign=true