java.lang.Object
org.elasticsearch.xpack.core.ml.MachineLearningField
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Field Summary
FieldsModifier and TypeFieldDescriptionstatic final Setting<ByteSizeValue> static final MlConfigVersionstatic final LicensedFeature.Momentarystatic final StringWhen set tofalse, the pytorch_inference process skips TorchScript model graph validation (the operation allowlist/forbidden list check).When set, overrides automatic ML node platform detection for built-in model variant selection (e.g.static final TimeValueThis boolean value indicates if `max_machine_memory_percent` should be ignored and an automatic calculation is used instead. -
Method Summary
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Field Details
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AUTODETECT_PROCESS
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MAX_MODEL_MEMORY_LIMIT
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MAX_LAZY_ML_NODES
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USE_AUTO_MACHINE_MEMORY_PERCENT
This boolean value indicates if `max_machine_memory_percent` should be ignored and an automatic calculation is used instead. This calculation takes into account total node size and the size of the JVM on that node. If the calculation fails, we fall back to `max_machine_memory_percent`. -
MODEL_PLATFORM_ARCHITECTURES
When set, overrides automatic ML node platform detection for built-in model variant selection (e.g. ELSER, E5). The configured list of architectures is used in place of querying ML node OS info. When empty (default), architectures are auto-detected from running ML nodes. Example values:["linux-x86_64"],["linux-aarch64"]. -
MODEL_GRAPH_VALIDATION_ENABLED
When set tofalse, the pytorch_inference process skips TorchScript model graph validation (the operation allowlist/forbidden list check). This is an emergency escape hatch — disabling validation removes the security check that blocks models with dangerous operations. -
STATE_PERSIST_RESTORE_TIMEOUT
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ML_FEATURE_FAMILY
- See Also:
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ML_API_FEATURE
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MIN_SUPPORTED_SNAPSHOT_VERSION
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Method Details
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valuesToId
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