2019-12-18 03:10:12 -05:00
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[role="xpack"]
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[testenv="basic"]
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[[delete-inference]]
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2020-07-20 16:06:29 -04:00
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= Delete {infer} trained model API
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2019-12-18 03:10:12 -05:00
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[subs="attributes"]
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++++
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<titleabbrev>Delete {infer} trained model</titleabbrev>
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++++
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Deletes an existing trained {infer} model that is currently not referenced by an
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ingest pipeline.
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experimental[]
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[[ml-delete-inference-request]]
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== {api-request-title}
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`DELETE _ml/inference/<model_id>`
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[[ml-delete-inference-prereq]]
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== {api-prereq-title}
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2020-01-09 04:44:07 -05:00
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If the {es} {security-features} are enabled, you must have the following built-in roles or equivalent privileges:
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* `machine_learning_admin`
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2020-07-23 19:43:10 -04:00
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For more information, see <<built-in-roles>> and {ml-docs-setup-privileges}.
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[[ml-delete-inference-path-params]]
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2020-07-20 16:06:29 -04:00
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== {api-path-parms-title}
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`<model_id>`::
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(Optional, string)
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include::{es-repo-dir}/ml/ml-shared.asciidoc[tag=model-id]
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2019-12-18 03:10:12 -05:00
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[[ml-delete-inference-response-codes]]
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2020-07-20 16:06:29 -04:00
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== {api-response-codes-title}
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`409`::
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The code indicates that the trained {infer} model is referenced by an ingest
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pipeline and cannot be deleted.
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[[ml-delete-inference-example]]
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2020-07-20 16:06:29 -04:00
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== {api-examples-title}
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2019-12-18 03:10:12 -05:00
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The following example deletes the `regression-job-one-1574775307356` trained
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model:
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[source,console]
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--------------------------------------------------
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DELETE _ml/inference/regression-job-one-1574775307356
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--------------------------------------------------
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// TEST[skip:TBD]
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The API returns the following result:
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[source,console-result]
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----
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{
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"acknowledged" : true
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}
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----
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