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public interface SuggestTrialsRequestOrBuilder extends MessageOrBuilder
Implements
MessageOrBuilderMethods
getClientId()
public abstract 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 | |
---|---|
Type | Description |
String | The clientId. |
getClientIdBytes()
public abstract 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 | |
---|---|
Type | Description |
ByteString | The bytes for clientId. |
getContexts(int index)
public abstract 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];
Parameter | |
---|---|
Name | Description |
index | int |
Returns | |
---|---|
Type | Description |
TrialContext |
getContextsCount()
public abstract 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];
Returns | |
---|---|
Type | Description |
int |
getContextsList()
public abstract 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];
Returns | |
---|---|
Type | Description |
List<TrialContext> |
getContextsOrBuilder(int index)
public abstract 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];
Parameter | |
---|---|
Name | Description |
index | int |
Returns | |
---|---|
Type | Description |
TrialContextOrBuilder |
getContextsOrBuilderList()
public abstract 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];
Returns | |
---|---|
Type | Description |
List<? extends com.google.cloud.aiplatform.v1.TrialContextOrBuilder> |
getParent()
public abstract 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 | |
---|---|
Type | Description |
String | The parent. |
getParentBytes()
public abstract 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 | |
---|---|
Type | Description |
ByteString | The bytes for parent. |
getSuggestionCount()
public abstract int getSuggestionCount()
Required. The number of suggestions requested. It must be positive.
int32 suggestion_count = 2 [(.google.api.field_behavior) = REQUIRED];
Returns | |
---|---|
Type | Description |
int | The suggestionCount. |