public final class SuggestTrialsRequest extends GeneratedMessageV3 implements SuggestTrialsRequestOrBuilder
Request message for
VizierService.SuggestTrials.
Protobuf type google.cloud.aiplatform.v1.SuggestTrialsRequest
Inherited Members
com.google.protobuf.GeneratedMessageV3.<ListT>makeMutableCopy(ListT)
com.google.protobuf.GeneratedMessageV3.<ListT>makeMutableCopy(ListT,int)
com.google.protobuf.GeneratedMessageV3.<T>emptyList(java.lang.Class<T>)
Static Fields
public static final int CLIENT_ID_FIELD_NUMBER
| Field Value |
|---|
| Type | Description |
int | |
CONTEXTS_FIELD_NUMBER
public static final int CONTEXTS_FIELD_NUMBER
| Field Value |
|---|
| Type | Description |
int | |
public static final int PARENT_FIELD_NUMBER
| Field Value |
|---|
| Type | Description |
int | |
public static final int SUGGESTION_COUNT_FIELD_NUMBER
| Field Value |
|---|
| Type | Description |
int | |
Static Methods
public static SuggestTrialsRequest getDefaultInstance()
public static final Descriptors.Descriptor getDescriptor()
public static SuggestTrialsRequest.Builder newBuilder()
public static SuggestTrialsRequest.Builder newBuilder(SuggestTrialsRequest prototype)
public static SuggestTrialsRequest parseDelimitedFrom(InputStream input)
public static SuggestTrialsRequest parseDelimitedFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
public static SuggestTrialsRequest parseFrom(byte[] data)
| Parameter |
|---|
| Name | Description |
data | byte[]
|
public static SuggestTrialsRequest parseFrom(byte[] data, ExtensionRegistryLite extensionRegistry)
public static SuggestTrialsRequest parseFrom(ByteString data)
public static SuggestTrialsRequest parseFrom(ByteString data, ExtensionRegistryLite extensionRegistry)
public static SuggestTrialsRequest parseFrom(CodedInputStream input)
public static SuggestTrialsRequest parseFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
public static SuggestTrialsRequest parseFrom(InputStream input)
public static SuggestTrialsRequest parseFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
public static SuggestTrialsRequest parseFrom(ByteBuffer data)
public static SuggestTrialsRequest parseFrom(ByteBuffer data, ExtensionRegistryLite extensionRegistry)
public static Parser<SuggestTrialsRequest> parser()
Methods
public boolean equals(Object obj)
| Parameter |
|---|
| Name | Description |
obj | Object
|
Overrides
public 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.
|
public 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 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
|
getContextsCount()
public 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 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];
getContextsOrBuilder(int index)
public 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
|
getContextsOrBuilderList()
public 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> | |
public SuggestTrialsRequest getDefaultInstanceForType()
public 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.
|
public 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.
|
public Parser<SuggestTrialsRequest> getParserForType()
Overrides
public int getSerializedSize()
| Returns |
|---|
| Type | Description |
int | |
Overrides
public 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.
|
| Returns |
|---|
| Type | Description |
int | |
Overrides
protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Overrides
public final boolean isInitialized()
Overrides
public SuggestTrialsRequest.Builder newBuilderForType()
protected SuggestTrialsRequest.Builder newBuilderForType(GeneratedMessageV3.BuilderParent parent)
Overrides
protected Object newInstance(GeneratedMessageV3.UnusedPrivateParameter unused)
Overrides
public SuggestTrialsRequest.Builder toBuilder()
public void writeTo(CodedOutputStream output)
Overrides
