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Elastic Docs ›Elasticsearch Guide [8.15] ›REST APIs ›Machine learning trained model APIs

Update trained model deployment API

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Update trained model deployment API

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Updates certain properties of a trained model deployment.

Request

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POST _ml/trained_models/<deployment_id>/deployment/_update

Prerequisites

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Requires the manage_ml cluster privilege. This privilege is included in the machine_learning_admin built-in role.

Description

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You can update a trained model deployment whose assignment_state is started. You can either increase or decrease the number of allocations of such a deployment.

Path parameters

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<deployment_id>
(Required, string) A unique identifier for the deployment of the model.

Request body

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number_of_allocations
(Optional, integer) The total number of allocations this model is assigned across machine learning nodes. Increasing this value generally increases the throughput.

Examples

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The following example updates the deployment for a elastic__distilbert-base-uncased-finetuned-conll03-english trained model to have 4 allocations:

resp = client.ml.update_trained_model_deployment(
    model_id="elastic__distilbert-base-uncased-finetuned-conll03-english",
    number_of_allocations=4,
)
print(resp)
response = client.ml.update_trained_model_deployment(
  model_id: 'elastic__distilbert-base-uncased-finetuned-conll03-english',
  body: {
    number_of_allocations: 4
  }
)
puts response
const response = await client.ml.updateTrainedModelDeployment({
  model_id: "elastic__distilbert-base-uncased-finetuned-conll03-english",
  number_of_allocations: 4,
});
console.log(response);
POST _ml/trained_models/elastic__distilbert-base-uncased-finetuned-conll03-english/deployment/_update
{
  "number_of_allocations": 4
}

The API returns the following results:

{
    "assignment": {
        "task_parameters": {
            "model_id": "elastic__distilbert-base-uncased-finetuned-conll03-english",
            "model_bytes": 265632637,
            "threads_per_allocation" : 1,
            "number_of_allocations" : 4,
            "queue_capacity" : 1024
        },
        "routing_table": {
            "uckeG3R8TLe2MMNBQ6AGrw": {
                "current_allocations": 1,
                "target_allocations": 4,
                "routing_state": "started",
                "reason": ""
            }
        },
        "assignment_state": "started",
        "start_time": "2022-11-02T11:50:34.766591Z"
    }
}
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