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