Interface SuggestTrialsRequestOrBuilder

All Superinterfaces:
com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder
All Known Implementing Classes:
SuggestTrialsRequest, SuggestTrialsRequest.Builder

@Generated public interface SuggestTrialsRequestOrBuilder extends com.google.protobuf.MessageOrBuilder
  • Method Details

    • getParent

      String getParent()
       Required. The project and location that the Study belongs to.
       Format: `projects/{project}/locations/{location}/studies/{study}`
       
      string parent = 1 [(.google.api.field_behavior) = REQUIRED, (.google.api.resource_reference) = { ... }
      Returns:
      The parent.
    • getParentBytes

      com.google.protobuf.ByteString getParentBytes()
       Required. The project and location that the Study belongs to.
       Format: `projects/{project}/locations/{location}/studies/{study}`
       
      string parent = 1 [(.google.api.field_behavior) = REQUIRED, (.google.api.resource_reference) = { ... }
      Returns:
      The bytes for parent.
    • getSuggestionCount

      int getSuggestionCount()
       Required. The number of suggestions requested. It must be positive.
       
      int32 suggestion_count = 2 [(.google.api.field_behavior) = REQUIRED];
      Returns:
      The suggestionCount.
    • getClientId

      String getClientId()
       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.
       
      string client_id = 3 [(.google.api.field_behavior) = REQUIRED];
      Returns:
      The clientId.
    • getClientIdBytes

      com.google.protobuf.ByteString getClientIdBytes()
       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.
       
      string client_id = 3 [(.google.api.field_behavior) = REQUIRED];
      Returns:
      The bytes for clientId.
    • getContextsList

      List<TrialContext> getContextsList()
       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.
       
      repeated .google.cloud.aiplatform.v1.TrialContext contexts = 4 [(.google.api.field_behavior) = OPTIONAL];
    • getContexts

      TrialContext getContexts(int index)
       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.
       
      repeated .google.cloud.aiplatform.v1.TrialContext contexts = 4 [(.google.api.field_behavior) = OPTIONAL];
    • getContextsCount

      int getContextsCount()
       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.
       
      repeated .google.cloud.aiplatform.v1.TrialContext contexts = 4 [(.google.api.field_behavior) = OPTIONAL];
    • getContextsOrBuilderList

      List<? extends TrialContextOrBuilder> getContextsOrBuilderList()
       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.
       
      repeated .google.cloud.aiplatform.v1.TrialContext contexts = 4 [(.google.api.field_behavior) = OPTIONAL];
    • getContextsOrBuilder

      TrialContextOrBuilder getContextsOrBuilder(int index)
       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.
       
      repeated .google.cloud.aiplatform.v1.TrialContext contexts = 4 [(.google.api.field_behavior) = OPTIONAL];