stack es ml update-trained-model-deployment cli command

elastic stack es ml update-trained-model-deployment \
  --model-id <model-id> \
  [options]
		

Update a trained model deployment.

Behaviour flags:

--dry-run — validate all inputs and exit without performing any action

--model-id string required

The unique identifier of the trained model. Currently, only PyTorch models are supported.

--number-of-allocations number

The number of model allocations on each node where the model is deployed. All allocations on a node share the same copy of the model in memory but use a separate set of threads to evaluate the model. Increasing this value generally increases the throughput. If this setting is greater than the number of hardware threads it will automatically be changed to a value less than the number of hardware threads. If adaptive_allocations is enabled, do not set this value, because it’s automatically set.

--adaptive-allocations string

Adaptive allocations configuration. When enabled, the number of allocations is set based on the current load. If adaptive_allocations is enabled, do not set the number of allocations manually.

--error-trace

When set to true Elasticsearch will include the full stack trace of errors when they occur.

--filter-path string

Comma-separated list of filters in dot notation which reduce the response returned by Elasticsearch.

Repeatable: pass --filter-path multiple times to supply more than one value

--human

When set to true will return statistics in a format suitable for humans. For example "exists_time": "1h" for humans and "exists_time_in_millis": 3600000 for computers. When disabled the human readable values will be omitted. This makes sense for responses being consumed only by machines.

--pretty

If set to true the returned JSON will be "pretty-formatted". Only use this option for debugging only.

--input-file string

path to a JSON file to use as command input

--dry-run

validate all inputs and exit without performing any action (preview changes without applying them)

--json

output as JSON