Class: Google::Apis::AiplatformV1::GoogleCloudAiplatformV1SuggestTrialsRequest

Inherits:
Object
  • Object
show all
Includes:
Core::Hashable, Core::JsonObjectSupport
Defined in:
lib/google/apis/aiplatform_v1/classes.rb,
lib/google/apis/aiplatform_v1/representations.rb,
lib/google/apis/aiplatform_v1/representations.rb

Overview

Request message for VizierService.SuggestTrials.

Instance Attribute Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize(**args) ⇒ GoogleCloudAiplatformV1SuggestTrialsRequest

Returns a new instance of GoogleCloudAiplatformV1SuggestTrialsRequest.



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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 29253

def initialize(**args)
   update!(**args)
end

Instance Attribute Details

#client_idString

Required. The identifier of the client that is requesting the suggestion. If multiple SuggestTrialsRequests have the same client_id, the service will return the identical suggested Trial if the Trial is pending, and provide a new Trial if the last suggested Trial was completed. Corresponds to the JSON property clientId

Returns:

  • (String)


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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 29216

def client_id
  @client_id
end

#contextsArray<Google::Apis::AiplatformV1::GoogleCloudAiplatformV1TrialContext>

Optional. This allows you to specify the "context" for a Trial; a context is a slice (a subspace) of the search space. Typical uses for contexts: 1) You are using Vizier to tune a server for best performance, but there's a strong weekly cycle. The context specifies the day-of-week. This allows Tuesday to generalize from Wednesday without assuming that everything is identical. 2) Imagine you're optimizing some medical treatment for people. As they walk in the door, you know certain facts about them (e.g. sex, weight, height, blood- pressure). Put that information in the context, and Vizier will adapt its suggestions to the patient. 3) You want to do a fair A/B test efficiently. Specify the "A" and "B" conditions as contexts, and Vizier will generalize between "A" and "B" conditions. If they are similar, this will allow Vizier to converge to the optimum faster than if "A" and "B" were separate Studies. NOTE: You can also enter contexts as REQUESTED Trials, e.g. via the CreateTrial() RPC; that's the asynchronous option where you don't need a close association between contexts and suggestions. NOTE: All the Parameters you set in a context MUST be defined in the Study. NOTE: You must supply 0 or $ suggestion_count contexts. If you don't supply any contexts, Vizier will make suggestions from the full search space specified in the StudySpec; if you supply a full set of context, each suggestion will match the corresponding context. NOTE: A Context with no features set matches anything, and allows suggestions from the full search space. NOTE: Contexts MUST lie within the search space specified in the StudySpec. It's an error if they don't. NOTE: Contexts preferentially match ACTIVE then REQUESTED trials before new suggestions are generated. NOTE: Generation of suggestions involves a match between a Context and (optionally) a REQUESTED trial; if that match is not fully specified, a suggestion will be geneated in the merged subspace. Corresponds to the JSON property contexts



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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 29246

def contexts
  @contexts
end

#suggestion_countFixnum

Required. The number of suggestions requested. It must be positive. Corresponds to the JSON property suggestionCount

Returns:

  • (Fixnum)


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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 29251

def suggestion_count
  @suggestion_count
end

Instance Method Details

#update!(**args) ⇒ Object

Update properties of this object



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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 29258

def update!(**args)
  @client_id = args[:client_id] if args.key?(:client_id)
  @contexts = args[:contexts] if args.key?(:contexts)
  @suggestion_count = args[:suggestion_count] if args.key?(:suggestion_count)
end