public interface ExplainRequestOrBuilder
extends com.google.protobuf.MessageOrBuilder
| Modifier and Type | Method and Description |
|---|---|
boolean |
containsConcurrentExplanationSpecOverride(String key)
Optional.
|
Map<String,ExplanationSpecOverride> |
getConcurrentExplanationSpecOverride()
Deprecated.
|
int |
getConcurrentExplanationSpecOverrideCount()
Optional.
|
Map<String,ExplanationSpecOverride> |
getConcurrentExplanationSpecOverrideMap()
Optional.
|
ExplanationSpecOverride |
getConcurrentExplanationSpecOverrideOrDefault(String key,
ExplanationSpecOverride defaultValue)
Optional.
|
ExplanationSpecOverride |
getConcurrentExplanationSpecOverrideOrThrow(String key)
Optional.
|
String |
getDeployedModelId()
If specified, this ExplainRequest will be served by the chosen
DeployedModel, overriding
[Endpoint.traffic_split][google.cloud.aiplatform.v1beta1.Endpoint.traffic_split].
|
com.google.protobuf.ByteString |
getDeployedModelIdBytes()
If specified, this ExplainRequest will be served by the chosen
DeployedModel, overriding
[Endpoint.traffic_split][google.cloud.aiplatform.v1beta1.Endpoint.traffic_split].
|
String |
getEndpoint()
Required.
|
com.google.protobuf.ByteString |
getEndpointBytes()
Required.
|
ExplanationSpecOverride |
getExplanationSpecOverride()
If specified, overrides the
[explanation_spec][google.cloud.aiplatform.v1beta1.DeployedModel.explanation_spec]
of the DeployedModel.
|
ExplanationSpecOverrideOrBuilder |
getExplanationSpecOverrideOrBuilder()
If specified, overrides the
[explanation_spec][google.cloud.aiplatform.v1beta1.DeployedModel.explanation_spec]
of the DeployedModel.
|
com.google.protobuf.Value |
getInstances(int index)
Required.
|
int |
getInstancesCount()
Required.
|
List<com.google.protobuf.Value> |
getInstancesList()
Required.
|
com.google.protobuf.ValueOrBuilder |
getInstancesOrBuilder(int index)
Required.
|
List<? extends com.google.protobuf.ValueOrBuilder> |
getInstancesOrBuilderList()
Required.
|
com.google.protobuf.Value |
getParameters()
The parameters that govern the prediction.
|
com.google.protobuf.ValueOrBuilder |
getParametersOrBuilder()
The parameters that govern the prediction.
|
boolean |
hasExplanationSpecOverride()
If specified, overrides the
[explanation_spec][google.cloud.aiplatform.v1beta1.DeployedModel.explanation_spec]
of the DeployedModel.
|
boolean |
hasParameters()
The parameters that govern the prediction.
|
findInitializationErrors, getAllFields, getDefaultInstanceForType, getDescriptorForType, getField, getInitializationErrorString, getOneofFieldDescriptor, getRepeatedField, getRepeatedFieldCount, getUnknownFields, hasField, hasOneofString getEndpoint()
Required. The name of the Endpoint requested to serve the explanation.
Format:
`projects/{project}/locations/{location}/endpoints/{endpoint}`
string endpoint = 1 [(.google.api.field_behavior) = REQUIRED, (.google.api.resource_reference) = { ... }
com.google.protobuf.ByteString getEndpointBytes()
Required. The name of the Endpoint requested to serve the explanation.
Format:
`projects/{project}/locations/{location}/endpoints/{endpoint}`
string endpoint = 1 [(.google.api.field_behavior) = REQUIRED, (.google.api.resource_reference) = { ... }
List<com.google.protobuf.Value> getInstancesList()
Required. The instances that are the input to the explanation call. A DeployedModel may have an upper limit on the number of instances it supports per request, and when it is exceeded the explanation call errors in case of AutoML Models, or, in case of customer created Models, the behaviour is as documented by that Model. The schema of any single instance may be specified via Endpoint's DeployedModels' [Model's][google.cloud.aiplatform.v1beta1.DeployedModel.model] [PredictSchemata's][google.cloud.aiplatform.v1beta1.Model.predict_schemata] [instance_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.instance_schema_uri].
repeated .google.protobuf.Value instances = 2 [(.google.api.field_behavior) = REQUIRED];
com.google.protobuf.Value getInstances(int index)
Required. The instances that are the input to the explanation call. A DeployedModel may have an upper limit on the number of instances it supports per request, and when it is exceeded the explanation call errors in case of AutoML Models, or, in case of customer created Models, the behaviour is as documented by that Model. The schema of any single instance may be specified via Endpoint's DeployedModels' [Model's][google.cloud.aiplatform.v1beta1.DeployedModel.model] [PredictSchemata's][google.cloud.aiplatform.v1beta1.Model.predict_schemata] [instance_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.instance_schema_uri].
repeated .google.protobuf.Value instances = 2 [(.google.api.field_behavior) = REQUIRED];
int getInstancesCount()
Required. The instances that are the input to the explanation call. A DeployedModel may have an upper limit on the number of instances it supports per request, and when it is exceeded the explanation call errors in case of AutoML Models, or, in case of customer created Models, the behaviour is as documented by that Model. The schema of any single instance may be specified via Endpoint's DeployedModels' [Model's][google.cloud.aiplatform.v1beta1.DeployedModel.model] [PredictSchemata's][google.cloud.aiplatform.v1beta1.Model.predict_schemata] [instance_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.instance_schema_uri].
repeated .google.protobuf.Value instances = 2 [(.google.api.field_behavior) = REQUIRED];
List<? extends com.google.protobuf.ValueOrBuilder> getInstancesOrBuilderList()
Required. The instances that are the input to the explanation call. A DeployedModel may have an upper limit on the number of instances it supports per request, and when it is exceeded the explanation call errors in case of AutoML Models, or, in case of customer created Models, the behaviour is as documented by that Model. The schema of any single instance may be specified via Endpoint's DeployedModels' [Model's][google.cloud.aiplatform.v1beta1.DeployedModel.model] [PredictSchemata's][google.cloud.aiplatform.v1beta1.Model.predict_schemata] [instance_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.instance_schema_uri].
repeated .google.protobuf.Value instances = 2 [(.google.api.field_behavior) = REQUIRED];
com.google.protobuf.ValueOrBuilder getInstancesOrBuilder(int index)
Required. The instances that are the input to the explanation call. A DeployedModel may have an upper limit on the number of instances it supports per request, and when it is exceeded the explanation call errors in case of AutoML Models, or, in case of customer created Models, the behaviour is as documented by that Model. The schema of any single instance may be specified via Endpoint's DeployedModels' [Model's][google.cloud.aiplatform.v1beta1.DeployedModel.model] [PredictSchemata's][google.cloud.aiplatform.v1beta1.Model.predict_schemata] [instance_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.instance_schema_uri].
repeated .google.protobuf.Value instances = 2 [(.google.api.field_behavior) = REQUIRED];
boolean hasParameters()
The parameters that govern the prediction. The schema of the parameters may be specified via Endpoint's DeployedModels' [Model's ][google.cloud.aiplatform.v1beta1.DeployedModel.model] [PredictSchemata's][google.cloud.aiplatform.v1beta1.Model.predict_schemata] [parameters_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.parameters_schema_uri].
.google.protobuf.Value parameters = 4;com.google.protobuf.Value getParameters()
The parameters that govern the prediction. The schema of the parameters may be specified via Endpoint's DeployedModels' [Model's ][google.cloud.aiplatform.v1beta1.DeployedModel.model] [PredictSchemata's][google.cloud.aiplatform.v1beta1.Model.predict_schemata] [parameters_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.parameters_schema_uri].
.google.protobuf.Value parameters = 4;com.google.protobuf.ValueOrBuilder getParametersOrBuilder()
The parameters that govern the prediction. The schema of the parameters may be specified via Endpoint's DeployedModels' [Model's ][google.cloud.aiplatform.v1beta1.DeployedModel.model] [PredictSchemata's][google.cloud.aiplatform.v1beta1.Model.predict_schemata] [parameters_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.parameters_schema_uri].
.google.protobuf.Value parameters = 4;boolean hasExplanationSpecOverride()
If specified, overrides the
[explanation_spec][google.cloud.aiplatform.v1beta1.DeployedModel.explanation_spec]
of the DeployedModel. Can be used for explaining prediction results with
different configurations, such as:
- Explaining top-5 predictions results as opposed to top-1;
- Increasing path count or step count of the attribution methods to reduce
approximate errors;
- Using different baselines for explaining the prediction results.
.google.cloud.aiplatform.v1beta1.ExplanationSpecOverride explanation_spec_override = 5;
ExplanationSpecOverride getExplanationSpecOverride()
If specified, overrides the
[explanation_spec][google.cloud.aiplatform.v1beta1.DeployedModel.explanation_spec]
of the DeployedModel. Can be used for explaining prediction results with
different configurations, such as:
- Explaining top-5 predictions results as opposed to top-1;
- Increasing path count or step count of the attribution methods to reduce
approximate errors;
- Using different baselines for explaining the prediction results.
.google.cloud.aiplatform.v1beta1.ExplanationSpecOverride explanation_spec_override = 5;
ExplanationSpecOverrideOrBuilder getExplanationSpecOverrideOrBuilder()
If specified, overrides the
[explanation_spec][google.cloud.aiplatform.v1beta1.DeployedModel.explanation_spec]
of the DeployedModel. Can be used for explaining prediction results with
different configurations, such as:
- Explaining top-5 predictions results as opposed to top-1;
- Increasing path count or step count of the attribution methods to reduce
approximate errors;
- Using different baselines for explaining the prediction results.
.google.cloud.aiplatform.v1beta1.ExplanationSpecOverride explanation_spec_override = 5;
int getConcurrentExplanationSpecOverrideCount()
Optional. This field is the same as the one above, but supports multiple explanations to occur in parallel. The key can be any string. Each override will be run against the model, then its explanations will be grouped together. Note - these explanations are run **In Addition** to the default Explanation in the deployed model.
map<string, .google.cloud.aiplatform.v1beta1.ExplanationSpecOverride> concurrent_explanation_spec_override = 6 [(.google.api.field_behavior) = OPTIONAL];
boolean containsConcurrentExplanationSpecOverride(String key)
Optional. This field is the same as the one above, but supports multiple explanations to occur in parallel. The key can be any string. Each override will be run against the model, then its explanations will be grouped together. Note - these explanations are run **In Addition** to the default Explanation in the deployed model.
map<string, .google.cloud.aiplatform.v1beta1.ExplanationSpecOverride> concurrent_explanation_spec_override = 6 [(.google.api.field_behavior) = OPTIONAL];
@Deprecated Map<String,ExplanationSpecOverride> getConcurrentExplanationSpecOverride()
getConcurrentExplanationSpecOverrideMap() instead.Map<String,ExplanationSpecOverride> getConcurrentExplanationSpecOverrideMap()
Optional. This field is the same as the one above, but supports multiple explanations to occur in parallel. The key can be any string. Each override will be run against the model, then its explanations will be grouped together. Note - these explanations are run **In Addition** to the default Explanation in the deployed model.
map<string, .google.cloud.aiplatform.v1beta1.ExplanationSpecOverride> concurrent_explanation_spec_override = 6 [(.google.api.field_behavior) = OPTIONAL];
ExplanationSpecOverride getConcurrentExplanationSpecOverrideOrDefault(String key, ExplanationSpecOverride defaultValue)
Optional. This field is the same as the one above, but supports multiple explanations to occur in parallel. The key can be any string. Each override will be run against the model, then its explanations will be grouped together. Note - these explanations are run **In Addition** to the default Explanation in the deployed model.
map<string, .google.cloud.aiplatform.v1beta1.ExplanationSpecOverride> concurrent_explanation_spec_override = 6 [(.google.api.field_behavior) = OPTIONAL];
ExplanationSpecOverride getConcurrentExplanationSpecOverrideOrThrow(String key)
Optional. This field is the same as the one above, but supports multiple explanations to occur in parallel. The key can be any string. Each override will be run against the model, then its explanations will be grouped together. Note - these explanations are run **In Addition** to the default Explanation in the deployed model.
map<string, .google.cloud.aiplatform.v1beta1.ExplanationSpecOverride> concurrent_explanation_spec_override = 6 [(.google.api.field_behavior) = OPTIONAL];
String getDeployedModelId()
If specified, this ExplainRequest will be served by the chosen DeployedModel, overriding [Endpoint.traffic_split][google.cloud.aiplatform.v1beta1.Endpoint.traffic_split].
string deployed_model_id = 3;com.google.protobuf.ByteString getDeployedModelIdBytes()
If specified, this ExplainRequest will be served by the chosen DeployedModel, overriding [Endpoint.traffic_split][google.cloud.aiplatform.v1beta1.Endpoint.traffic_split].
string deployed_model_id = 3;Copyright © 2024 Google LLC. All rights reserved.