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2F feat: add PredictRequestResponseLoggingConfig to Endpoint in aiplatfo… · googleapis/googleapis@e0f0642 · GitHub
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feat: add PredictRequestResponseLoggingConfig to Endpoint in aiplatform v1 endpoint.proto
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‎google/cloud/aiplatform/v1/annotation.proto

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package google.cloud.aiplatform.v1;
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import "google/api/annotations.proto";
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import "google/api/field_behavior.proto";
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import "google/api/resource.proto";
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import "google/cloud/aiplatform/v1/user_action_reference.proto";
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import "google/protobuf/struct.proto";
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import "google/protobuf/timestamp.proto";

‎google/cloud/aiplatform/v1/annotation_spec.proto

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package google.cloud.aiplatform.v1;
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import "google/api/annotations.proto";
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import "google/api/field_behavior.proto";
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import "google/api/resource.proto";
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import "google/protobuf/timestamp.proto";

‎google/cloud/aiplatform/v1/artifact.proto

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package google.cloud.aiplatform.v1;
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import "google/api/annotations.proto";
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import "google/api/field_behavior.proto";
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import "google/api/resource.proto";
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import "google/cloud/aiplatform/v1/value.proto";
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import "google/protobuf/struct.proto";
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import "google/protobuf/timestamp.proto";
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‎google/cloud/aiplatform/v1/batch_prediction_job.proto

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package google.cloud.aiplatform.v1;
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import "google/api/annotations.proto";
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import "google/api/field_behavior.proto";
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import "google/api/resource.proto";
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import "google/cloud/aiplatform/v1/completion_stats.proto";
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import "google/cloud/aiplatform/v1/job_state.proto";
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import "google/cloud/aiplatform/v1/machine_resources.proto";
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import "google/cloud/aiplatform/v1/manual_batch_tuning_parameters.proto";
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import "google/cloud/aiplatform/v1/model_monitoring.proto";
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import "google/cloud/aiplatform/v1/unmanaged_container_model.proto";
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import "google/protobuf/struct.proto";
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import "google/protobuf/timestamp.proto";

‎google/cloud/aiplatform/v1/completion_stats.proto

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package google.cloud.aiplatform.v1;
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import "google/api/annotations.proto";
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import "google/api/field_behavior.proto";
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import "google/rpc/status.proto";
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option csharp_namespace = "Google.Cloud.AIPlatform.V1";
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option go_package = "google.golang.org/genproto/googleapis/cloud/aiplatform/v1;aiplatform";

‎google/cloud/aiplatform/v1/context.proto

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package google.cloud.aiplatform.v1;
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import "google/api/annotations.proto";
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import "google/api/field_behavior.proto";
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import "google/api/resource.proto";
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import "google/cloud/aiplatform/v1/value.proto";
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import "google/protobuf/struct.proto";
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import "google/protobuf/timestamp.proto";
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‎google/cloud/aiplatform/v1/custom_job.proto

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package google.cloud.aiplatform.v1;
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import "google/api/annotations.proto";
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import "google/api/field_behavior.proto";
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import "google/api/resource.proto";
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import "google/cloud/aiplatform/v1/encryption_spec.proto";

‎google/cloud/aiplatform/v1/data_item.proto

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package google.cloud.aiplatform.v1;
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import "google/api/annotations.proto";
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import "google/api/field_behavior.proto";
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import "google/api/resource.proto";
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import "google/protobuf/struct.proto";
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import "google/protobuf/timestamp.proto";
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‎google/cloud/aiplatform/v1/data_labeling_job.proto

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package google.cloud.aiplatform.v1;
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import "google/api/annotations.proto";
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import "google/api/field_behavior.proto";
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import "google/api/resource.proto";
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import "google/cloud/aiplatform/v1/accelerator_type.proto";
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import "google/cloud/aiplatform/v1/encryption_spec.proto";
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import "google/cloud/aiplatform/v1/job_state.proto";
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import "google/cloud/aiplatform/v1/specialist_pool.proto";
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import "google/protobuf/struct.proto";
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import "google/protobuf/timestamp.proto";
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import "google/rpc/status.proto";

‎google/cloud/aiplatform/v1/dataset.proto

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package google.cloud.aiplatform.v1;
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import "google/api/annotations.proto";
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import "google/api/field_behavior.proto";
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import "google/api/resource.proto";
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import "google/cloud/aiplatform/v1/encryption_spec.proto";

‎google/cloud/aiplatform/v1/dataset_service.proto

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import "google/cloud/aiplatform/v1/data_item.proto";
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import "google/cloud/aiplatform/v1/dataset.proto";
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import "google/cloud/aiplatform/v1/operation.proto";
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import "google/cloud/aiplatform/v1/training_pipeline.proto";
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import "google/longrunning/operations.proto";
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import "google/protobuf/field_mask.proto";
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‎google/cloud/aiplatform/v1/deployed_index_ref.proto

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package google.cloud.aiplatform.v1;
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import "google/api/annotations.proto";
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import "google/api/field_behavior.proto";
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import "google/api/resource.proto";
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‎google/cloud/aiplatform/v1/deployed_model_ref.proto

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package google.cloud.aiplatform.v1;
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import "google/api/annotations.proto";
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import "google/api/field_behavior.proto";
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import "google/api/resource.proto";
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‎google/cloud/aiplatform/v1/encryption_spec.proto

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package google.cloud.aiplatform.v1;
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import "google/api/annotations.proto";
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option csharp_namespace = "Google.Cloud.AIPlatform.V1";

‎google/cloud/aiplatform/v1/endpoint.proto

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package google.cloud.aiplatform.v1;
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import "google/api/annotations.proto";
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import "google/api/field_behavior.proto";
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import "google/api/resource.proto";
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import "google/cloud/aiplatform/v1/encryption_spec.proto";
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import "google/cloud/aiplatform/v1/explanation.proto";
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import "google/cloud/aiplatform/v1/io.proto";
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import "google/cloud/aiplatform/v1/machine_resources.proto";
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import "google/cloud/aiplatform/v1/model_deployment_monitoring_job.proto";
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import "google/cloud/aiplatform/v1/model_monitoring.proto";
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option csharp_namespace = "Google.Cloud.AIPlatform.V1";
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// Only one of the fields, [network][google.cloud.aiplatform.v1.Endpoint.network] or
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// [enable_private_service_connect][google.cloud.aiplatform.v1.Endpoint.enable_private_service_connect],
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// can be set.
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bool enable_private_service_connect = 17;
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bool enable_private_service_connect = 17 [deprecated = true];
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// Output only. Resource name of the Model Monitoring job associated with this Endpoint
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// if monitoring is enabled by [CreateModelDeploymentMonitoringJob][].
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type: "aiplatform.googleapis.com/ModelDeploymentMonitoringJob"
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}
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];
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// Configures the request-response logging for online prediction.
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PredictRequestResponseLoggingConfig predict_request_response_logging_config = 18;
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}
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// connect is enabled.
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string service_attachment = 4 [(google.api.field_behavior) = OUTPUT_ONLY];
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}
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// Configuration for logging request-response to a BigQuery table.
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message PredictRequestResponseLoggingConfig {
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// If logging is enabled or not.
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bool enabled = 1;
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// Percentage of requests to be logged, expressed as a fraction in
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// range(0,1].
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double sampling_rate = 2;
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// BigQuery table for logging.
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// If only given project, a new dataset will be created with name
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// `logging_<endpoint-display-name>_<endpoint-id>` where
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// <endpoint-display-name> will be made BigQuery-dataset-name compatible (e.g.
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// most special characters will become underscores). If no table name is
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// given, a new table will be created with name `request_response_logging`
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BigQueryDestination bigquery_destination = 3;
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}

‎google/cloud/aiplatform/v1/entity_type.proto

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import "google/cloud/aiplatform/v1/feature.proto";
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‎google/cloud/aiplatform/v1/env_var.proto

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‎google/cloud/aiplatform/v1/event.proto

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‎google/cloud/aiplatform/v1/execution.proto

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‎google/cloud/aiplatform/v1/explanation.proto

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‎google/cloud/aiplatform/v1/explanation_metadata.proto

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‎google/cloud/aiplatform/v1/feature.proto

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‎google/cloud/aiplatform/v1/feature_monitoring_stats.proto

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‎google/cloud/aiplatform/v1/feature_selector.proto

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‎google/cloud/aiplatform/v1/featurestore.proto

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‎google/cloud/aiplatform/v1/featurestore_service.proto

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‎google/cloud/aiplatform/v1/hyperparameter_tuning_job.proto

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‎google/cloud/aiplatform/v1/index.proto

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‎google/cloud/aiplatform/v1/index_endpoint.proto

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‎google/cloud/aiplatform/v1/io.proto

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‎google/cloud/aiplatform/v1/job_state.proto

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‎google/cloud/aiplatform/v1/lineage_subgraph.proto

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‎google/cloud/aiplatform/v1/machine_resources.proto

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‎google/cloud/aiplatform/v1/manual_batch_tuning_parameters.proto

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‎google/cloud/aiplatform/v1/metadata_schema.proto

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‎google/cloud/aiplatform/v1/metadata_store.proto

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‎google/cloud/aiplatform/v1/migratable_resource.proto

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