Package com.google.cloud.aiplatform.v1beta1

Class ModelMonitor.Builder

java.lang.Object
com.google.protobuf.AbstractMessageLite.Builder
com.google.protobuf.AbstractMessage.Builder<BuilderT>
com.google.protobuf.GeneratedMessage.Builder<ModelMonitor.Builder>
com.google.cloud.aiplatform.v1beta1.ModelMonitor.Builder
All Implemented Interfaces:
ModelMonitorOrBuilder, com.google.protobuf.Message.Builder, com.google.protobuf.MessageLite.Builder, com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder, Cloneable
Enclosing class:
ModelMonitor
public static final class ModelMonitor.Builder extends com.google.protobuf.GeneratedMessage.Builder<ModelMonitor.Builder> implements ModelMonitorOrBuilder
 Vertex AI Model Monitoring Service serves as a central hub for the analysis
 and visualization of data quality and performance related to models.
 ModelMonitor stands as a top level resource for overseeing your model
 monitoring tasks.
Protobuf type google.cloud.aiplatform.v1beta1.ModelMonitor

  • Method Details

    • getDescriptor

      public static final com.google.protobuf.Descriptors.Descriptor getDescriptor()

    • internalGetFieldAccessorTable

      protected com.google.protobuf.GeneratedMessage.FieldAccessorTable internalGetFieldAccessorTable()
      Specified by:
      internalGetFieldAccessorTable in class com.google.protobuf.GeneratedMessage.Builder<ModelMonitor.Builder>

    • clear

      public ModelMonitor.Builder clear()
      Specified by:
      clear in interface com.google.protobuf.Message.Builder
      Specified by:
      clear in interface com.google.protobuf.MessageLite.Builder
      Overrides:
      clear in class com.google.protobuf.GeneratedMessage.Builder<ModelMonitor.Builder>

    • getDescriptorForType

      public com.google.protobuf.Descriptors.Descriptor getDescriptorForType()
      Specified by:
      getDescriptorForType in interface com.google.protobuf.Message.Builder
      Specified by:
      getDescriptorForType in interface com.google.protobuf.MessageOrBuilder
      Overrides:
      getDescriptorForType in class com.google.protobuf.GeneratedMessage.Builder<ModelMonitor.Builder>

    • getDefaultInstanceForType

      public ModelMonitor getDefaultInstanceForType()
      Specified by:
      getDefaultInstanceForType in interface com.google.protobuf.MessageLiteOrBuilder
      Specified by:
      getDefaultInstanceForType in interface com.google.protobuf.MessageOrBuilder

    • build

      public ModelMonitor build()
      Specified by:
      build in interface com.google.protobuf.Message.Builder
      Specified by:
      build in interface com.google.protobuf.MessageLite.Builder

    • buildPartial

      public ModelMonitor buildPartial()
      Specified by:
      buildPartial in interface com.google.protobuf.Message.Builder
      Specified by:
      buildPartial in interface com.google.protobuf.MessageLite.Builder

    • mergeFrom

      public ModelMonitor.Builder mergeFrom(com.google.protobuf.Message other)
      Specified by:
      mergeFrom in interface com.google.protobuf.Message.Builder
      Overrides:
      mergeFrom in class com.google.protobuf.AbstractMessage.Builder<ModelMonitor.Builder>

    • mergeFrom

      public ModelMonitor.Builder mergeFrom(ModelMonitor other)

    • isInitialized

      public final boolean isInitialized()
      Specified by:
      isInitialized in interface com.google.protobuf.MessageLiteOrBuilder
      Overrides:
      isInitialized in class com.google.protobuf.GeneratedMessage.Builder<ModelMonitor.Builder>

    • mergeFrom

      public ModelMonitor.Builder mergeFrom(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws IOException
      Specified by:
      mergeFrom in interface com.google.protobuf.Message.Builder
      Specified by:
      mergeFrom in interface com.google.protobuf.MessageLite.Builder
      Overrides:
      mergeFrom in class com.google.protobuf.AbstractMessage.Builder<ModelMonitor.Builder>
      Throws:
      IOException

    • getDefaultObjectiveCase

      public ModelMonitor.DefaultObjectiveCase getDefaultObjectiveCase()
      Specified by:
      getDefaultObjectiveCase in interface ModelMonitorOrBuilder

    • clearDefaultObjective

      public ModelMonitor.Builder clearDefaultObjective()

    • hasTabularObjective

      public boolean hasTabularObjective()
       Optional default tabular model monitoring objective.
      .google.cloud.aiplatform.v1beta1.ModelMonitoringObjectiveSpec.TabularObjective tabular_objective = 11;
      Specified by:
      hasTabularObjective in interface ModelMonitorOrBuilder
      Returns:
      Whether the tabularObjective field is set.

    • getTabularObjective

      public ModelMonitoringObjectiveSpec.TabularObjective getTabularObjective()
       Optional default tabular model monitoring objective.
      .google.cloud.aiplatform.v1beta1.ModelMonitoringObjectiveSpec.TabularObjective tabular_objective = 11;
      Specified by:
      getTabularObjective in interface ModelMonitorOrBuilder
      Returns:
      The tabularObjective.

    • setTabularObjective

      public ModelMonitor.Builder setTabularObjective(ModelMonitoringObjectiveSpec.TabularObjective value)
       Optional default tabular model monitoring objective.
      .google.cloud.aiplatform.v1beta1.ModelMonitoringObjectiveSpec.TabularObjective tabular_objective = 11;

    • setTabularObjective

      public ModelMonitor.Builder setTabularObjective(ModelMonitoringObjectiveSpec.TabularObjective.Builder builderForValue)
       Optional default tabular model monitoring objective.
      .google.cloud.aiplatform.v1beta1.ModelMonitoringObjectiveSpec.TabularObjective tabular_objective = 11;

    • mergeTabularObjective

      public ModelMonitor.Builder mergeTabularObjective(ModelMonitoringObjectiveSpec.TabularObjective value)
       Optional default tabular model monitoring objective.
      .google.cloud.aiplatform.v1beta1.ModelMonitoringObjectiveSpec.TabularObjective tabular_objective = 11;

    • clearTabularObjective

      public ModelMonitor.Builder clearTabularObjective()
       Optional default tabular model monitoring objective.
      .google.cloud.aiplatform.v1beta1.ModelMonitoringObjectiveSpec.TabularObjective tabular_objective = 11;

    • getTabularObjectiveBuilder

      public ModelMonitoringObjectiveSpec.TabularObjective.Builder getTabularObjectiveBuilder()
       Optional default tabular model monitoring objective.
      .google.cloud.aiplatform.v1beta1.ModelMonitoringObjectiveSpec.TabularObjective tabular_objective = 11;

    • getTabularObjectiveOrBuilder

      public ModelMonitoringObjectiveSpec.TabularObjectiveOrBuilder getTabularObjectiveOrBuilder()
       Optional default tabular model monitoring objective.
      .google.cloud.aiplatform.v1beta1.ModelMonitoringObjectiveSpec.TabularObjective tabular_objective = 11;
      Specified by:
      getTabularObjectiveOrBuilder in interface ModelMonitorOrBuilder

    • getName

      public String getName()
       Immutable. Resource name of the ModelMonitor. Format:
 `projects/{project}/locations/{location}/modelMonitors/{model_monitor}`.
      string name = 1 [(.google.api.field_behavior) = IMMUTABLE];
      Specified by:
      getName in interface ModelMonitorOrBuilder
      Returns:
      The name.

    • getNameBytes

      public com.google.protobuf.ByteString getNameBytes()
       Immutable. Resource name of the ModelMonitor. Format:
 `projects/{project}/locations/{location}/modelMonitors/{model_monitor}`.
      string name = 1 [(.google.api.field_behavior) = IMMUTABLE];
      Specified by:
      getNameBytes in interface ModelMonitorOrBuilder
      Returns:
      The bytes for name.

    • setName

      public ModelMonitor.Builder setName(String value)
       Immutable. Resource name of the ModelMonitor. Format:
 `projects/{project}/locations/{location}/modelMonitors/{model_monitor}`.
      string name = 1 [(.google.api.field_behavior) = IMMUTABLE];
      Parameters:
      value - The name to set.
      Returns:
      This builder for chaining.

    • clearName

      public ModelMonitor.Builder clearName()
       Immutable. Resource name of the ModelMonitor. Format:
 `projects/{project}/locations/{location}/modelMonitors/{model_monitor}`.
      string name = 1 [(.google.api.field_behavior) = IMMUTABLE];
      Returns:
      This builder for chaining.

    • setNameBytes

      public ModelMonitor.Builder setNameBytes(com.google.protobuf.ByteString value)
       Immutable. Resource name of the ModelMonitor. Format:
 `projects/{project}/locations/{location}/modelMonitors/{model_monitor}`.
      string name = 1 [(.google.api.field_behavior) = IMMUTABLE];
      Parameters:
      value - The bytes for name to set.
      Returns:
      This builder for chaining.

    • getDisplayName

      public String getDisplayName()
       The display name of the ModelMonitor.
 The name can be up to 128 characters long and can consist of any UTF-8.
      string display_name = 2;
      Specified by:
      getDisplayName in interface ModelMonitorOrBuilder
      Returns:
      The displayName.

    • getDisplayNameBytes

      public com.google.protobuf.ByteString getDisplayNameBytes()
       The display name of the ModelMonitor.
 The name can be up to 128 characters long and can consist of any UTF-8.
      string display_name = 2;
      Specified by:
      getDisplayNameBytes in interface ModelMonitorOrBuilder
      Returns:
      The bytes for displayName.

    • setDisplayName

      public ModelMonitor.Builder setDisplayName(String value)
       The display name of the ModelMonitor.
 The name can be up to 128 characters long and can consist of any UTF-8.
      string display_name = 2;
      Parameters:
      value - The displayName to set.
      Returns:
      This builder for chaining.

    • clearDisplayName

      public ModelMonitor.Builder clearDisplayName()
       The display name of the ModelMonitor.
 The name can be up to 128 characters long and can consist of any UTF-8.
      string display_name = 2;
      Returns:
      This builder for chaining.

    • setDisplayNameBytes

      public ModelMonitor.Builder setDisplayNameBytes(com.google.protobuf.ByteString value)
       The display name of the ModelMonitor.
 The name can be up to 128 characters long and can consist of any UTF-8.
      string display_name = 2;
      Parameters:
      value - The bytes for displayName to set.
      Returns:
      This builder for chaining.

    • hasModelMonitoringTarget

      public boolean hasModelMonitoringTarget()
       The entity that is subject to analysis.
 Currently only models in Vertex AI Model Registry are supported. If you
 want to analyze the model which is outside the Vertex AI, you could
 register a model in Vertex AI Model Registry using just a display name.
      .google.cloud.aiplatform.v1beta1.ModelMonitor.ModelMonitoringTarget model_monitoring_target = 3;
      Specified by:
      hasModelMonitoringTarget in interface ModelMonitorOrBuilder
      Returns:
      Whether the modelMonitoringTarget field is set.

    • getModelMonitoringTarget

      public ModelMonitor.ModelMonitoringTarget getModelMonitoringTarget()
       The entity that is subject to analysis.
 Currently only models in Vertex AI Model Registry are supported. If you
 want to analyze the model which is outside the Vertex AI, you could
 register a model in Vertex AI Model Registry using just a display name.
      .google.cloud.aiplatform.v1beta1.ModelMonitor.ModelMonitoringTarget model_monitoring_target = 3;
      Specified by:
      getModelMonitoringTarget in interface ModelMonitorOrBuilder
      Returns:
      The modelMonitoringTarget.

    • setModelMonitoringTarget

      public ModelMonitor.Builder setModelMonitoringTarget(ModelMonitor.ModelMonitoringTarget value)
       The entity that is subject to analysis.
 Currently only models in Vertex AI Model Registry are supported. If you
 want to analyze the model which is outside the Vertex AI, you could
 register a model in Vertex AI Model Registry using just a display name.
      .google.cloud.aiplatform.v1beta1.ModelMonitor.ModelMonitoringTarget model_monitoring_target = 3;

    • setModelMonitoringTarget

      public ModelMonitor.Builder setModelMonitoringTarget(ModelMonitor.ModelMonitoringTarget.Builder builderForValue)
       The entity that is subject to analysis.
 Currently only models in Vertex AI Model Registry are supported. If you
 want to analyze the model which is outside the Vertex AI, you could
 register a model in Vertex AI Model Registry using just a display name.
      .google.cloud.aiplatform.v1beta1.ModelMonitor.ModelMonitoringTarget model_monitoring_target = 3;

    • mergeModelMonitoringTarget

      public ModelMonitor.Builder mergeModelMonitoringTarget(ModelMonitor.ModelMonitoringTarget value)
       The entity that is subject to analysis.
 Currently only models in Vertex AI Model Registry are supported. If you
 want to analyze the model which is outside the Vertex AI, you could
 register a model in Vertex AI Model Registry using just a display name.
      .google.cloud.aiplatform.v1beta1.ModelMonitor.ModelMonitoringTarget model_monitoring_target = 3;

    • clearModelMonitoringTarget

      public ModelMonitor.Builder clearModelMonitoringTarget()
       The entity that is subject to analysis.
 Currently only models in Vertex AI Model Registry are supported. If you
 want to analyze the model which is outside the Vertex AI, you could
 register a model in Vertex AI Model Registry using just a display name.
      .google.cloud.aiplatform.v1beta1.ModelMonitor.ModelMonitoringTarget model_monitoring_target = 3;

    • getModelMonitoringTargetBuilder

      public ModelMonitor.ModelMonitoringTarget.Builder getModelMonitoringTargetBuilder()
       The entity that is subject to analysis.
 Currently only models in Vertex AI Model Registry are supported. If you
 want to analyze the model which is outside the Vertex AI, you could
 register a model in Vertex AI Model Registry using just a display name.
      .google.cloud.aiplatform.v1beta1.ModelMonitor.ModelMonitoringTarget model_monitoring_target = 3;

    • getModelMonitoringTargetOrBuilder

      public ModelMonitor.ModelMonitoringTargetOrBuilder getModelMonitoringTargetOrBuilder()
       The entity that is subject to analysis.
 Currently only models in Vertex AI Model Registry are supported. If you
 want to analyze the model which is outside the Vertex AI, you could
 register a model in Vertex AI Model Registry using just a display name.
      .google.cloud.aiplatform.v1beta1.ModelMonitor.ModelMonitoringTarget model_monitoring_target = 3;
      Specified by:
      getModelMonitoringTargetOrBuilder in interface ModelMonitorOrBuilder

    • hasTrainingDataset

      public boolean hasTrainingDataset()
       Optional training dataset used to train the model.
 It can serve as a reference dataset to identify changes in production.
      .google.cloud.aiplatform.v1beta1.ModelMonitoringInput training_dataset = 10;
      Specified by:
      hasTrainingDataset in interface ModelMonitorOrBuilder
      Returns:
      Whether the trainingDataset field is set.

    • getTrainingDataset

      public ModelMonitoringInput getTrainingDataset()
       Optional training dataset used to train the model.
 It can serve as a reference dataset to identify changes in production.
      .google.cloud.aiplatform.v1beta1.ModelMonitoringInput training_dataset = 10;
      Specified by:
      getTrainingDataset in interface ModelMonitorOrBuilder
      Returns:
      The trainingDataset.

    • setTrainingDataset

      public ModelMonitor.Builder setTrainingDataset(ModelMonitoringInput value)
       Optional training dataset used to train the model.
 It can serve as a reference dataset to identify changes in production.
      .google.cloud.aiplatform.v1beta1.ModelMonitoringInput training_dataset = 10;

    • setTrainingDataset

      public ModelMonitor.Builder setTrainingDataset(ModelMonitoringInput.Builder builderForValue)
       Optional training dataset used to train the model.
 It can serve as a reference dataset to identify changes in production.
      .google.cloud.aiplatform.v1beta1.ModelMonitoringInput training_dataset = 10;

    • mergeTrainingDataset

      public ModelMonitor.Builder mergeTrainingDataset(ModelMonitoringInput value)
       Optional training dataset used to train the model.
 It can serve as a reference dataset to identify changes in production.
      .google.cloud.aiplatform.v1beta1.ModelMonitoringInput training_dataset = 10;

    • clearTrainingDataset

      public ModelMonitor.Builder clearTrainingDataset()
       Optional training dataset used to train the model.
 It can serve as a reference dataset to identify changes in production.
      .google.cloud.aiplatform.v1beta1.ModelMonitoringInput training_dataset = 10;

    • getTrainingDatasetBuilder

      public ModelMonitoringInput.Builder getTrainingDatasetBuilder()
       Optional training dataset used to train the model.
 It can serve as a reference dataset to identify changes in production.
      .google.cloud.aiplatform.v1beta1.ModelMonitoringInput training_dataset = 10;

    • getTrainingDatasetOrBuilder

      public ModelMonitoringInputOrBuilder getTrainingDatasetOrBuilder()
       Optional training dataset used to train the model.
 It can serve as a reference dataset to identify changes in production.
      .google.cloud.aiplatform.v1beta1.ModelMonitoringInput training_dataset = 10;
      Specified by:
      getTrainingDatasetOrBuilder in interface ModelMonitorOrBuilder

    • hasNotificationSpec

      public boolean hasNotificationSpec()
       Optional default notification spec, it can be overridden in the
 ModelMonitoringJob notification spec.
      .google.cloud.aiplatform.v1beta1.ModelMonitoringNotificationSpec notification_spec = 12;
      Specified by:
      hasNotificationSpec in interface ModelMonitorOrBuilder
      Returns:
      Whether the notificationSpec field is set.

    • getNotificationSpec

      public ModelMonitoringNotificationSpec getNotificationSpec()
       Optional default notification spec, it can be overridden in the
 ModelMonitoringJob notification spec.
      .google.cloud.aiplatform.v1beta1.ModelMonitoringNotificationSpec notification_spec = 12;
      Specified by:
      getNotificationSpec in interface ModelMonitorOrBuilder
      Returns:
      The notificationSpec.

    • setNotificationSpec

      public ModelMonitor.Builder setNotificationSpec(ModelMonitoringNotificationSpec value)
       Optional default notification spec, it can be overridden in the
 ModelMonitoringJob notification spec.
      .google.cloud.aiplatform.v1beta1.ModelMonitoringNotificationSpec notification_spec = 12;

    • setNotificationSpec

      public ModelMonitor.Builder setNotificationSpec(ModelMonitoringNotificationSpec.Builder builderForValue)
       Optional default notification spec, it can be overridden in the
 ModelMonitoringJob notification spec.
      .google.cloud.aiplatform.v1beta1.ModelMonitoringNotificationSpec notification_spec = 12;

    • mergeNotificationSpec

      public ModelMonitor.Builder mergeNotificationSpec(ModelMonitoringNotificationSpec value)
       Optional default notification spec, it can be overridden in the
 ModelMonitoringJob notification spec.
      .google.cloud.aiplatform.v1beta1.ModelMonitoringNotificationSpec notification_spec = 12;

    • clearNotificationSpec

      public ModelMonitor.Builder clearNotificationSpec()
       Optional default notification spec, it can be overridden in the
 ModelMonitoringJob notification spec.
      .google.cloud.aiplatform.v1beta1.ModelMonitoringNotificationSpec notification_spec = 12;

    • getNotificationSpecBuilder

      public ModelMonitoringNotificationSpec.Builder getNotificationSpecBuilder()
       Optional default notification spec, it can be overridden in the
 ModelMonitoringJob notification spec.
      .google.cloud.aiplatform.v1beta1.ModelMonitoringNotificationSpec notification_spec = 12;

    • getNotificationSpecOrBuilder

      public ModelMonitoringNotificationSpecOrBuilder getNotificationSpecOrBuilder()
       Optional default notification spec, it can be overridden in the
 ModelMonitoringJob notification spec.
      .google.cloud.aiplatform.v1beta1.ModelMonitoringNotificationSpec notification_spec = 12;
      Specified by:
      getNotificationSpecOrBuilder in interface ModelMonitorOrBuilder

    • hasOutputSpec

      public boolean hasOutputSpec()
       Optional default monitoring metrics/logs export spec, it can be overridden
 in the ModelMonitoringJob output spec.
 If not specified, a default Google Cloud Storage bucket will be created
 under your project.
      .google.cloud.aiplatform.v1beta1.ModelMonitoringOutputSpec output_spec = 13;
      Specified by:
      hasOutputSpec in interface ModelMonitorOrBuilder
      Returns:
      Whether the outputSpec field is set.

    • getOutputSpec

      public ModelMonitoringOutputSpec getOutputSpec()
       Optional default monitoring metrics/logs export spec, it can be overridden
 in the ModelMonitoringJob output spec.
 If not specified, a default Google Cloud Storage bucket will be created
 under your project.
      .google.cloud.aiplatform.v1beta1.ModelMonitoringOutputSpec output_spec = 13;
      Specified by:
      getOutputSpec in interface ModelMonitorOrBuilder
      Returns:
      The outputSpec.

    • setOutputSpec

      public ModelMonitor.Builder setOutputSpec(ModelMonitoringOutputSpec value)
       Optional default monitoring metrics/logs export spec, it can be overridden
 in the ModelMonitoringJob output spec.
 If not specified, a default Google Cloud Storage bucket will be created
 under your project.
      .google.cloud.aiplatform.v1beta1.ModelMonitoringOutputSpec output_spec = 13;

    • setOutputSpec

      public ModelMonitor.Builder setOutputSpec(ModelMonitoringOutputSpec.Builder builderForValue)
       Optional default monitoring metrics/logs export spec, it can be overridden
 in the ModelMonitoringJob output spec.
 If not specified, a default Google Cloud Storage bucket will be created
 under your project.
      .google.cloud.aiplatform.v1beta1.ModelMonitoringOutputSpec output_spec = 13;

    • mergeOutputSpec

      public ModelMonitor.Builder mergeOutputSpec(ModelMonitoringOutputSpec value)
       Optional default monitoring metrics/logs export spec, it can be overridden
 in the ModelMonitoringJob output spec.
 If not specified, a default Google Cloud Storage bucket will be created
 under your project.
      .google.cloud.aiplatform.v1beta1.ModelMonitoringOutputSpec output_spec = 13;

    • clearOutputSpec

      public ModelMonitor.Builder clearOutputSpec()
       Optional default monitoring metrics/logs export spec, it can be overridden
 in the ModelMonitoringJob output spec.
 If not specified, a default Google Cloud Storage bucket will be created
 under your project.
      .google.cloud.aiplatform.v1beta1.ModelMonitoringOutputSpec output_spec = 13;

    • getOutputSpecBuilder

      public ModelMonitoringOutputSpec.Builder getOutputSpecBuilder()
       Optional default monitoring metrics/logs export spec, it can be overridden
 in the ModelMonitoringJob output spec.
 If not specified, a default Google Cloud Storage bucket will be created
 under your project.
      .google.cloud.aiplatform.v1beta1.ModelMonitoringOutputSpec output_spec = 13;

    • getOutputSpecOrBuilder

      public ModelMonitoringOutputSpecOrBuilder getOutputSpecOrBuilder()
       Optional default monitoring metrics/logs export spec, it can be overridden
 in the ModelMonitoringJob output spec.
 If not specified, a default Google Cloud Storage bucket will be created
 under your project.
      .google.cloud.aiplatform.v1beta1.ModelMonitoringOutputSpec output_spec = 13;
      Specified by:
      getOutputSpecOrBuilder in interface ModelMonitorOrBuilder

    • hasExplanationSpec

      public boolean hasExplanationSpec()
       Optional model explanation spec. It is used for feature attribution
 monitoring.
      .google.cloud.aiplatform.v1beta1.ExplanationSpec explanation_spec = 16;
      Specified by:
      hasExplanationSpec in interface ModelMonitorOrBuilder
      Returns:
      Whether the explanationSpec field is set.

    • getExplanationSpec

      public ExplanationSpec getExplanationSpec()
       Optional model explanation spec. It is used for feature attribution
 monitoring.
      .google.cloud.aiplatform.v1beta1.ExplanationSpec explanation_spec = 16;
      Specified by:
      getExplanationSpec in interface ModelMonitorOrBuilder
      Returns:
      The explanationSpec.

    • setExplanationSpec

      public ModelMonitor.Builder setExplanationSpec(ExplanationSpec value)
       Optional model explanation spec. It is used for feature attribution
 monitoring.
      .google.cloud.aiplatform.v1beta1.ExplanationSpec explanation_spec = 16;

    • setExplanationSpec

      public ModelMonitor.Builder setExplanationSpec(ExplanationSpec.Builder builderForValue)
       Optional model explanation spec. It is used for feature attribution
 monitoring.
      .google.cloud.aiplatform.v1beta1.ExplanationSpec explanation_spec = 16;

    • mergeExplanationSpec

      public ModelMonitor.Builder mergeExplanationSpec(ExplanationSpec value)
       Optional model explanation spec. It is used for feature attribution
 monitoring.
      .google.cloud.aiplatform.v1beta1.ExplanationSpec explanation_spec = 16;

    • clearExplanationSpec

      public ModelMonitor.Builder clearExplanationSpec()
       Optional model explanation spec. It is used for feature attribution
 monitoring.
      .google.cloud.aiplatform.v1beta1.ExplanationSpec explanation_spec = 16;

    • getExplanationSpecBuilder

      public ExplanationSpec.Builder getExplanationSpecBuilder()
       Optional model explanation spec. It is used for feature attribution
 monitoring.
      .google.cloud.aiplatform.v1beta1.ExplanationSpec explanation_spec = 16;

    • getExplanationSpecOrBuilder

      public ExplanationSpecOrBuilder getExplanationSpecOrBuilder()
       Optional model explanation spec. It is used for feature attribution
 monitoring.
      .google.cloud.aiplatform.v1beta1.ExplanationSpec explanation_spec = 16;
      Specified by:
      getExplanationSpecOrBuilder in interface ModelMonitorOrBuilder

    • hasModelMonitoringSchema

      public boolean hasModelMonitoringSchema()
       Monitoring Schema is to specify the model's features, prediction outputs
 and ground truth properties. It is used to extract pertinent data from the
 dataset and to process features based on their properties.
 Make sure that the schema aligns with your dataset, if it does not, we will
 be unable to extract data from the dataset.
 It is required for most models, but optional for Vertex AI AutoML Tables
 unless the schem information is not available.
      .google.cloud.aiplatform.v1beta1.ModelMonitoringSchema model_monitoring_schema = 9;
      Specified by:
      hasModelMonitoringSchema in interface ModelMonitorOrBuilder
      Returns:
      Whether the modelMonitoringSchema field is set.

    • getModelMonitoringSchema

      public ModelMonitoringSchema getModelMonitoringSchema()
       Monitoring Schema is to specify the model's features, prediction outputs
 and ground truth properties. It is used to extract pertinent data from the
 dataset and to process features based on their properties.
 Make sure that the schema aligns with your dataset, if it does not, we will
 be unable to extract data from the dataset.
 It is required for most models, but optional for Vertex AI AutoML Tables
 unless the schem information is not available.
      .google.cloud.aiplatform.v1beta1.ModelMonitoringSchema model_monitoring_schema = 9;
      Specified by:
      getModelMonitoringSchema in interface ModelMonitorOrBuilder
      Returns:
      The modelMonitoringSchema.

    • setModelMonitoringSchema

      public ModelMonitor.Builder setModelMonitoringSchema(ModelMonitoringSchema value)
       Monitoring Schema is to specify the model's features, prediction outputs
 and ground truth properties. It is used to extract pertinent data from the
 dataset and to process features based on their properties.
 Make sure that the schema aligns with your dataset, if it does not, we will
 be unable to extract data from the dataset.
 It is required for most models, but optional for Vertex AI AutoML Tables
 unless the schem information is not available.
      .google.cloud.aiplatform.v1beta1.ModelMonitoringSchema model_monitoring_schema = 9;

    • setModelMonitoringSchema

      public ModelMonitor.Builder setModelMonitoringSchema(ModelMonitoringSchema.Builder builderForValue)
       Monitoring Schema is to specify the model's features, prediction outputs
 and ground truth properties. It is used to extract pertinent data from the
 dataset and to process features based on their properties.
 Make sure that the schema aligns with your dataset, if it does not, we will
 be unable to extract data from the dataset.
 It is required for most models, but optional for Vertex AI AutoML Tables
 unless the schem information is not available.
      .google.cloud.aiplatform.v1beta1.ModelMonitoringSchema model_monitoring_schema = 9;

    • mergeModelMonitoringSchema

      public ModelMonitor.Builder mergeModelMonitoringSchema(ModelMonitoringSchema value)
       Monitoring Schema is to specify the model's features, prediction outputs
 and ground truth properties. It is used to extract pertinent data from the
 dataset and to process features based on their properties.
 Make sure that the schema aligns with your dataset, if it does not, we will
 be unable to extract data from the dataset.
 It is required for most models, but optional for Vertex AI AutoML Tables
 unless the schem information is not available.
      .google.cloud.aiplatform.v1beta1.ModelMonitoringSchema model_monitoring_schema = 9;

    • clearModelMonitoringSchema

      public ModelMonitor.Builder clearModelMonitoringSchema()
       Monitoring Schema is to specify the model's features, prediction outputs
 and ground truth properties. It is used to extract pertinent data from the
 dataset and to process features based on their properties.
 Make sure that the schema aligns with your dataset, if it does not, we will
 be unable to extract data from the dataset.
 It is required for most models, but optional for Vertex AI AutoML Tables
 unless the schem information is not available.
      .google.cloud.aiplatform.v1beta1.ModelMonitoringSchema model_monitoring_schema = 9;

    • getModelMonitoringSchemaBuilder

      public ModelMonitoringSchema.Builder getModelMonitoringSchemaBuilder()
       Monitoring Schema is to specify the model's features, prediction outputs
 and ground truth properties. It is used to extract pertinent data from the
 dataset and to process features based on their properties.
 Make sure that the schema aligns with your dataset, if it does not, we will
 be unable to extract data from the dataset.
 It is required for most models, but optional for Vertex AI AutoML Tables
 unless the schem information is not available.
      .google.cloud.aiplatform.v1beta1.ModelMonitoringSchema model_monitoring_schema = 9;

    • getModelMonitoringSchemaOrBuilder

      public ModelMonitoringSchemaOrBuilder getModelMonitoringSchemaOrBuilder()
       Monitoring Schema is to specify the model's features, prediction outputs
 and ground truth properties. It is used to extract pertinent data from the
 dataset and to process features based on their properties.
 Make sure that the schema aligns with your dataset, if it does not, we will
 be unable to extract data from the dataset.
 It is required for most models, but optional for Vertex AI AutoML Tables
 unless the schem information is not available.
      .google.cloud.aiplatform.v1beta1.ModelMonitoringSchema model_monitoring_schema = 9;
      Specified by:
      getModelMonitoringSchemaOrBuilder in interface ModelMonitorOrBuilder

    • hasEncryptionSpec

      public boolean hasEncryptionSpec()
       Customer-managed encryption key spec for a ModelMonitor. If
 set, this ModelMonitor and all sub-resources of this
 ModelMonitor will be secured by this key.
      .google.cloud.aiplatform.v1beta1.EncryptionSpec encryption_spec = 5;
      Specified by:
      hasEncryptionSpec in interface ModelMonitorOrBuilder
      Returns:
      Whether the encryptionSpec field is set.

    • getEncryptionSpec

      public EncryptionSpec getEncryptionSpec()
       Customer-managed encryption key spec for a ModelMonitor. If
 set, this ModelMonitor and all sub-resources of this
 ModelMonitor will be secured by this key.
      .google.cloud.aiplatform.v1beta1.EncryptionSpec encryption_spec = 5;
      Specified by:
      getEncryptionSpec in interface ModelMonitorOrBuilder
      Returns:
      The encryptionSpec.

    • setEncryptionSpec

      public ModelMonitor.Builder setEncryptionSpec(EncryptionSpec value)
       Customer-managed encryption key spec for a ModelMonitor. If
 set, this ModelMonitor and all sub-resources of this
 ModelMonitor will be secured by this key.
      .google.cloud.aiplatform.v1beta1.EncryptionSpec encryption_spec = 5;

    • setEncryptionSpec

      public ModelMonitor.Builder setEncryptionSpec(EncryptionSpec.Builder builderForValue)
       Customer-managed encryption key spec for a ModelMonitor. If
 set, this ModelMonitor and all sub-resources of this
 ModelMonitor will be secured by this key.
      .google.cloud.aiplatform.v1beta1.EncryptionSpec encryption_spec = 5;

    • mergeEncryptionSpec

      public ModelMonitor.Builder mergeEncryptionSpec(EncryptionSpec value)
       Customer-managed encryption key spec for a ModelMonitor. If
 set, this ModelMonitor and all sub-resources of this
 ModelMonitor will be secured by this key.
      .google.cloud.aiplatform.v1beta1.EncryptionSpec encryption_spec = 5;

    • clearEncryptionSpec

      public ModelMonitor.Builder clearEncryptionSpec()
       Customer-managed encryption key spec for a ModelMonitor. If
 set, this ModelMonitor and all sub-resources of this
 ModelMonitor will be secured by this key.
      .google.cloud.aiplatform.v1beta1.EncryptionSpec encryption_spec = 5;

    • getEncryptionSpecBuilder

      public EncryptionSpec.Builder getEncryptionSpecBuilder()
       Customer-managed encryption key spec for a ModelMonitor. If
 set, this ModelMonitor and all sub-resources of this
 ModelMonitor will be secured by this key.
      .google.cloud.aiplatform.v1beta1.EncryptionSpec encryption_spec = 5;

    • getEncryptionSpecOrBuilder

      public EncryptionSpecOrBuilder getEncryptionSpecOrBuilder()
       Customer-managed encryption key spec for a ModelMonitor. If
 set, this ModelMonitor and all sub-resources of this
 ModelMonitor will be secured by this key.
      .google.cloud.aiplatform.v1beta1.EncryptionSpec encryption_spec = 5;
      Specified by:
      getEncryptionSpecOrBuilder in interface ModelMonitorOrBuilder

    • hasCreateTime

      public boolean hasCreateTime()
       Output only. Timestamp when this ModelMonitor was created.
      .google.protobuf.Timestamp create_time = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      hasCreateTime in interface ModelMonitorOrBuilder
      Returns:
      Whether the createTime field is set.

    • getCreateTime

      public com.google.protobuf.Timestamp getCreateTime()
       Output only. Timestamp when this ModelMonitor was created.
      .google.protobuf.Timestamp create_time = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getCreateTime in interface ModelMonitorOrBuilder
      Returns:
      The createTime.

    • setCreateTime

      public ModelMonitor.Builder setCreateTime(com.google.protobuf.Timestamp value)
       Output only. Timestamp when this ModelMonitor was created.
      .google.protobuf.Timestamp create_time = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];

    • setCreateTime

      public ModelMonitor.Builder setCreateTime(com.google.protobuf.Timestamp.Builder builderForValue)
       Output only. Timestamp when this ModelMonitor was created.
      .google.protobuf.Timestamp create_time = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];

    • mergeCreateTime

      public ModelMonitor.Builder mergeCreateTime(com.google.protobuf.Timestamp value)
       Output only. Timestamp when this ModelMonitor was created.
      .google.protobuf.Timestamp create_time = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];

    • clearCreateTime

      public ModelMonitor.Builder clearCreateTime()
       Output only. Timestamp when this ModelMonitor was created.
      .google.protobuf.Timestamp create_time = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];

    • getCreateTimeBuilder

      public com.google.protobuf.Timestamp.Builder getCreateTimeBuilder()
       Output only. Timestamp when this ModelMonitor was created.
      .google.protobuf.Timestamp create_time = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];

    • getCreateTimeOrBuilder

      public com.google.protobuf.TimestampOrBuilder getCreateTimeOrBuilder()
       Output only. Timestamp when this ModelMonitor was created.
      .google.protobuf.Timestamp create_time = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getCreateTimeOrBuilder in interface ModelMonitorOrBuilder

    • hasUpdateTime

      public boolean hasUpdateTime()
       Output only. Timestamp when this ModelMonitor was updated most recently.
      .google.protobuf.Timestamp update_time = 7 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      hasUpdateTime in interface ModelMonitorOrBuilder
      Returns:
      Whether the updateTime field is set.

    • getUpdateTime

      public com.google.protobuf.Timestamp getUpdateTime()
       Output only. Timestamp when this ModelMonitor was updated most recently.
      .google.protobuf.Timestamp update_time = 7 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getUpdateTime in interface ModelMonitorOrBuilder
      Returns:
      The updateTime.

    • setUpdateTime

      public ModelMonitor.Builder setUpdateTime(com.google.protobuf.Timestamp value)
       Output only. Timestamp when this ModelMonitor was updated most recently.
      .google.protobuf.Timestamp update_time = 7 [(.google.api.field_behavior) = OUTPUT_ONLY];

    • setUpdateTime

      public ModelMonitor.Builder setUpdateTime(com.google.protobuf.Timestamp.Builder builderForValue)
       Output only. Timestamp when this ModelMonitor was updated most recently.
      .google.protobuf.Timestamp update_time = 7 [(.google.api.field_behavior) = OUTPUT_ONLY];

    • mergeUpdateTime

      public ModelMonitor.Builder mergeUpdateTime(com.google.protobuf.Timestamp value)
       Output only. Timestamp when this ModelMonitor was updated most recently.
      .google.protobuf.Timestamp update_time = 7 [(.google.api.field_behavior) = OUTPUT_ONLY];

    • clearUpdateTime

      public ModelMonitor.Builder clearUpdateTime()
       Output only. Timestamp when this ModelMonitor was updated most recently.
      .google.protobuf.Timestamp update_time = 7 [(.google.api.field_behavior) = OUTPUT_ONLY];

    • getUpdateTimeBuilder

      public com.google.protobuf.Timestamp.Builder getUpdateTimeBuilder()
       Output only. Timestamp when this ModelMonitor was updated most recently.
      .google.protobuf.Timestamp update_time = 7 [(.google.api.field_behavior) = OUTPUT_ONLY];

    • getUpdateTimeOrBuilder

      public com.google.protobuf.TimestampOrBuilder getUpdateTimeOrBuilder()
       Output only. Timestamp when this ModelMonitor was updated most recently.
      .google.protobuf.Timestamp update_time = 7 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getUpdateTimeOrBuilder in interface ModelMonitorOrBuilder

    • getSatisfiesPzs

      public boolean getSatisfiesPzs()
       Output only. Reserved for future use.
      bool satisfies_pzs = 17 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getSatisfiesPzs in interface ModelMonitorOrBuilder
      Returns:
      The satisfiesPzs.

    • setSatisfiesPzs

      public ModelMonitor.Builder setSatisfiesPzs(boolean value)
       Output only. Reserved for future use.
      bool satisfies_pzs = 17 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Parameters:
      value - The satisfiesPzs to set.
      Returns:
      This builder for chaining.

    • clearSatisfiesPzs

      public ModelMonitor.Builder clearSatisfiesPzs()
       Output only. Reserved for future use.
      bool satisfies_pzs = 17 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Returns:
      This builder for chaining.

    • getSatisfiesPzi

      public boolean getSatisfiesPzi()
       Output only. Reserved for future use.
      bool satisfies_pzi = 18 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getSatisfiesPzi in interface ModelMonitorOrBuilder
      Returns:
      The satisfiesPzi.

    • setSatisfiesPzi

      public ModelMonitor.Builder setSatisfiesPzi(boolean value)
       Output only. Reserved for future use.
      bool satisfies_pzi = 18 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Parameters:
      value - The satisfiesPzi to set.
      Returns:
      This builder for chaining.

    • clearSatisfiesPzi

      public ModelMonitor.Builder clearSatisfiesPzi()
       Output only. Reserved for future use.
      bool satisfies_pzi = 18 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Returns:
      This builder for chaining.