[API] Updates machine_learning APIs

- machine_learning.put_trained_model adds `wait_for_completion`
(Boolean) parameter: Whether to wait for all child operations(e.g.
model download) to complete, before returning or not. Default to
false.
- machine_learning.start_trained_model_deployment adds `deployment_id`
(String) The Id of the new deployment. Defaults to the model_id if not
set.

Author: picandocodigo

elasticsearch-api/lib/elasticsearch/api/actions/machine_learning/put_trained_model.rb

@@ -26,6 +26,7 @@ module Actions
         #
         # @option arguments [String] :model_id The ID of the trained models to store
         # @option arguments [Boolean] :defer_definition_decompression If set to `true` and a `compressed_definition` is provided, the request defers definition decompression and skips relevant validations.
+        # @option arguments [Boolean] :wait_for_completion Whether to wait for all child operations(e.g. model download) to complete, before returning or not. Default to false
         # @option arguments [Hash] :headers Custom HTTP headers
         # @option arguments [Hash] :body The trained model configuration (*Required*)
         #

elasticsearch-api/lib/elasticsearch/api/actions/machine_learning/start_trained_model_deployment.rb

@@ -26,6 +26,7 @@ module Actions
         #
         # @option arguments [String] :model_id The unique identifier of the trained model. (*Required*)
         # @option arguments [String] :cache_size A byte-size value for configuring the inference cache size. For example, 20mb.
+        # @option arguments [String] :deployment_id The Id of the new deployment. Defaults to the model_id if not set.
         # @option arguments [Integer] :number_of_allocations The total number of allocations this model is assigned across machine learning nodes.
         # @option arguments [Integer] :threads_per_allocation The number of threads used by each model allocation during inference.
         # @option arguments [String] :priority The deployment priority.