Package com.google.cloud.aiplatform.v1beta1

Interface ModelMonitorOrBuilder

All Superinterfaces:
com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder
All Known Implementing Classes:
ModelMonitor, ModelMonitor.Builder
@Generated public interface ModelMonitorOrBuilder extends com.google.protobuf.MessageOrBuilder

  • Method Details

    • hasTabularObjective

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

    • getTabularObjective

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

    • getTabularObjectiveOrBuilder

      ModelMonitoringObjectiveSpec.TabularObjectiveOrBuilder getTabularObjectiveOrBuilder()
       Optional default tabular model monitoring objective.
      .google.cloud.aiplatform.v1beta1.ModelMonitoringObjectiveSpec.TabularObjective tabular_objective = 11;

    • getName

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

    • getNameBytes

      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];
      Returns:
      The bytes for name.

    • getDisplayName

      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;
      Returns:
      The displayName.

    • getDisplayNameBytes

      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;
      Returns:
      The bytes for displayName.

    • hasModelMonitoringTarget

      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;
      Returns:
      Whether the modelMonitoringTarget field is set.

    • getModelMonitoringTarget

      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;
      Returns:
      The modelMonitoringTarget.

    • getModelMonitoringTargetOrBuilder

      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;

    • hasTrainingDataset

      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;
      Returns:
      Whether the trainingDataset field is set.

    • getTrainingDataset

      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;
      Returns:
      The trainingDataset.

    • getTrainingDatasetOrBuilder

      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;

    • hasNotificationSpec

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

    • getNotificationSpec

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

    • getNotificationSpecOrBuilder

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

    • hasOutputSpec

      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;
      Returns:
      Whether the outputSpec field is set.

    • getOutputSpec

      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;
      Returns:
      The outputSpec.

    • getOutputSpecOrBuilder

      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;

    • hasExplanationSpec

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

    • getExplanationSpec

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

    • getExplanationSpecOrBuilder

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

    • hasModelMonitoringSchema

      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;
      Returns:
      Whether the modelMonitoringSchema field is set.

    • getModelMonitoringSchema

      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;
      Returns:
      The modelMonitoringSchema.

    • getModelMonitoringSchemaOrBuilder

      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;

    • hasEncryptionSpec

      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;
      Returns:
      Whether the encryptionSpec field is set.

    • getEncryptionSpec

      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;
      Returns:
      The encryptionSpec.

    • getEncryptionSpecOrBuilder

      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;

    • hasCreateTime

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

    • getCreateTime

      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];
      Returns:
      The createTime.

    • getCreateTimeOrBuilder

      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];

    • hasUpdateTime

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

    • getUpdateTime

      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];
      Returns:
      The updateTime.

    • getUpdateTimeOrBuilder

      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];

    • getSatisfiesPzs

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

    • getSatisfiesPzi

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

    • getDefaultObjectiveCase

      ModelMonitor.DefaultObjectiveCase getDefaultObjectiveCase()