[ML] ML Model Inference Ingest Processor #49052
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This adds a couple of things: - A model loader service that is accessible via transport calls. This service will load in models and cache them. They will stay loaded until a processor no longer references them - A Model class and its first sub-class LocalModel. Used to cache model information and run inference. - Transport action and handler for requests to infer against a local model
* [ML][Inference] Adjust inference configuration option API * fixing method reference * fixing tests
* [ML][Inference] adds logistic_regression output aggregator * Addressing PR comments
* [ML][Inference] Adding read/del trained models * addressing PR comments and fixing tests * adding error tests to ml_security blacklist * fixing tests
* [ML][Inference] Adding ingest processor * optionally including tag in model metadata injection in processor * fixing test * addressing PR comments * adding comment
* [ML][Inference] Adding model memory estimations * addressing PR comments
* [ML][Inference] adding more options to inference processor, fixing minor bug * addressing PR comments
…8584) * [ML][Inference] handle string values better in feature extraction * adding tests for InferenceHelpers
[ML][Inference] Adding _stats endpoint for inference. Initially only contains ingest stats and pipeline counts.
…47869) * [ML][Inference] add inference processors and trained models to usage * renaming usage fields
#48718) * [ML][Inference] add new flag for optionally including model definition * adjusting after definition and config split * revert unnecessary changes to AbstractTransportGetResourcesAction * fixing TrainedModelDefinitionTests * fixing yaml tests from previous code changes * fixing integration test * making tests an assertBusy for verification
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benwtrent
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* [ML][Inference] adding license checks * Apply suggestions from code review Co-Authored-By: Przemysław Witek <przemyslaw.witek@elastic.co>
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@elasticmachine retest this please |
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@elasticmachine update branch |
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* [ML][Inference] adds lazy model loader and inference (elastic#47410) This adds a couple of things: - A model loader service that is accessible via transport calls. This service will load in models and cache them. They will stay loaded until a processor no longer references them - A Model class and its first sub-class LocalModel. Used to cache model information and run inference. - Transport action and handler for requests to infer against a local model Related Feature PRs: * [ML][Inference] Adjust inference configuration option API (elastic#47812) * [ML][Inference] adds logistic_regression output aggregator (elastic#48075) * [ML][Inference] Adding read/del trained models (elastic#47882) * [ML][Inference] Adding inference ingest processor (elastic#47859) * [ML][Inference] fixing classification inference for ensemble (elastic#48463) * [ML][Inference] Adding model memory estimations (elastic#48323) * [ML][Inference] adding more options to inference processor (elastic#48545) * [ML][Inference] handle string values better in feature extraction (elastic#48584) * [ML][Inference] Adding _stats endpoint for inference (elastic#48492) * [ML][Inference] add inference processors and trained models to usage (elastic#47869) * [ML][Inference] add new flag for optionally including model definition (elastic#48718) * [ML][Inference] adding license checks (elastic#49056) * [ML][Inference] Adding memory and compute estimates to inference (elastic#48955)
benwtrent
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* [ML] ML Model Inference Ingest Processor (#49052) * [ML][Inference] adds lazy model loader and inference (#47410) This adds a couple of things: - A model loader service that is accessible via transport calls. This service will load in models and cache them. They will stay loaded until a processor no longer references them - A Model class and its first sub-class LocalModel. Used to cache model information and run inference. - Transport action and handler for requests to infer against a local model Related Feature PRs: * [ML][Inference] Adjust inference configuration option API (#47812) * [ML][Inference] adds logistic_regression output aggregator (#48075) * [ML][Inference] Adding read/del trained models (#47882) * [ML][Inference] Adding inference ingest processor (#47859) * [ML][Inference] fixing classification inference for ensemble (#48463) * [ML][Inference] Adding model memory estimations (#48323) * [ML][Inference] adding more options to inference processor (#48545) * [ML][Inference] handle string values better in feature extraction (#48584) * [ML][Inference] Adding _stats endpoint for inference (#48492) * [ML][Inference] add inference processors and trained models to usage (#47869) * [ML][Inference] add new flag for optionally including model definition (#48718) * [ML][Inference] adding license checks (#49056) * [ML][Inference] Adding memory and compute estimates to inference (#48955) * fixing version of indexed docs for model inference
This was referenced Feb 3, 2020
russcam
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Relates: #4341, elastic/elasticsearch#49052 This commit adds the ingest inference processor.
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This contains the groundwork for allowing machine model inference in an ingest processor.
The new ingest processor is called
inference:field_mappings: The mapping of ingest doc field names to the fields expected by the modelmodel_id: The model with which to inferinference_config: The type of inference (regression or classification) and their related optionstarget_field: The field name to put the results of the inferenceThe steps for building a model and then utilizing it for inference are as follows:
_ml/inferenceAPIThe machine learning data frame analytics jobs automatically store models for inference when it completes a classification or regression analysis.
Additionally, some basic management APIs and quality of life features are included.