[ML] adding new PUT trained model vocabulary endpoint #77387
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benwtrent
added
>enhancement
:ml
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Pinging @elastic/clients-team (Team:Clients) |
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Pinging @elastic/ml-core (Team:ML) |
lcawl
reviewed
Sep 7, 2021
docs/reference/ml/df-analytics/apis/put-trained-model-vocabulary.asciidoc
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…ry.asciidoc Co-authored-by: Lisa Cawley <lcawley@elastic.co>
davidkyle
approved these changes
Sep 8, 2021
| "parts":{ | ||
| "model_id":{ | ||
| "type":"string", | ||
| "description":"The ID of the trained model for this definition part" |
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| "description":"The ID of the trained model for this definition part" | |
| "description":"The ID of the trained model for this vocabulary" |
| if ((inferenceConfig instanceof NlpConfig) == false) { | ||
| listener.onFailure( | ||
| new ElasticsearchStatusException( | ||
| "cannot put vocabulary for model [{}] as it is not an nlp model", |
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nlp or NLP?
It's NLP in the docs but there is not a precedent in code
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error messages are simply docs for failures :). So, I can switch it to be NLP.
| parser.declareObject( | ||
| ConstructingObjectParser.optionalConstructorArg(), | ||
| (p, c) -> { | ||
| if (ignoreUnknownFields == false) { |
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++ the caller can't set this but the code creates the config so it is visible
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This commit removes the ability to set the vocabulary location in the model config.
This opts instead for sane defaults to be set and used. Wrapping this up in an
API.
The index is now always the internally managed
.ml-inference-nativeindexand the document ID is always
<model_id>_vocabularyThis API only works for pytorch/nlp type models.