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Josh Mock
2024-11-19 11:04:35 -06:00
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[[reference-ml-start_trained_model_deployment]]
////////
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|| ██╔══██╗██╔════╝██╔══██╗██╔══██╗████╗ ████║██╔════╝ ||
|| ██████╔╝█████╗ ███████║██║ ██║██╔████╔██║█████╗ ||
|| ██╔══██╗██╔══╝ ██╔══██║██║ ██║██║╚██╔╝██║██╔══╝ ||
|| ██║ ██║███████╗██║ ██║██████╔╝██║ ╚═╝ ██║███████╗ ||
|| ╚═╝ ╚═╝╚══════╝╚═╝ ╚═╝╚═════╝ ╚═╝ ╚═╝╚══════╝ ||
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|| This file is autogenerated, DO NOT send pull requests that changes this file directly. ||
|| You should update the script that does the generation, which can be found in: ||
|| https://github.com/elastic/elastic-client-generator-js ||
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|| You can run the script with the following command: ||
|| npm run elasticsearch -- --version <version> ||
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===========================================================================================================================
////////
[discrete]
=== client.ml.startTrainedModelDeployment
Start a trained model deployment. It allocates the model to every machine learning node.
{ref}/start-trained-model-deployment.html[{es} documentation]
[discrete]
==== Function signature
[source,ts]
----
(MlStartTrainedModelDeploymentRequest, options?): Promise<MlStartTrainedModelDeploymentResponse>
----
[discrete]
===== `MlStartTrainedModelDeploymentRequest`
[source,ts]
----
interface MlStartTrainedModelDeploymentRequest extends <<shared-type-request-base, RequestBase>> {
model_id: <<shared-type-id, Id>>
cache_size?: <<shared-type-byte-size, ByteSize>>
deployment_id?: string
number_of_allocations?: <<shared-type-integer, integer>>
priority?: MlTrainingPriority
queue_capacity?: <<shared-type-integer, integer>>
threads_per_allocation?: <<shared-type-integer, integer>>
timeout?: <<shared-type-duration, Duration>>
wait_for?: MlDeploymentAllocationState
}
----
[discrete]
===== `MlStartTrainedModelDeploymentResponse`
[source,ts]
----
interface MlStartTrainedModelDeploymentResponse {
assignment: MlTrainedModelAssignment
}
----