feat: add enable_private_service_connect field to Endpoint (#238)

feat: add id field to DeployedModel
feat: add service_attachment field to PrivateEndpoints
feat: add endpoint_id to CreateEndpointRequest and method signature to CreateEndpoint
feat: add method signature to CreateFeatureStore, CreateEntityType, CreateFeature
feat: add network and enable_private_service_connect to IndexEndpoint
feat: add service_attachment to IndexPrivateEndpoints
feat: add stratified_split field to training_pipeline InputDataConfig
fix: remove invalid resource annotations in LineageSubgraph

- [ ] Regenerate this pull request now.

PiperOrigin-RevId: 413686247

Source-Link: googleapis/googleapis@244a89d

Source-Link: googleapis/googleapis-gen@c485e44
Copy-Tag: eyJwIjoiLmdpdGh1Yi8uT3dsQm90LnlhbWwiLCJoIjoiYzQ4NWU0NGExYjJmZWY1MTZlOWJjYTM2NTE0ZDUwY2ViZDVlYTUxZiJ9

packages/google-cloud-aiplatform/linkinator.config.json

@@ -3,13 +3,8 @@
   "skip": [
     "https://codecov.io/gh/googleapis/",
     "www.googleapis.com",
-    "img.shields.io",
-    "https://console.cloud.google.com/cloudshell"
+    "img.shields.io"
   ],
   "silent": true,
-  "concurrency": 5,
-  "retry": true,
-  "retryErrors": true,
-  "retryErrorsCount": 5,
-  "retryErrorsJitter": 3000
+  "concurrency": 5
 }

packages/google-cloud-aiplatform/protos/google/cloud/aiplatform/v1beta1/artifact.proto

@@ -43,7 +43,7 @@ message Artifact {
     // Unspecified state for the Artifact.
     STATE_UNSPECIFIED = 0;
 
-    // A state used by systems like Vertex Pipelines to indicate that the
+    // A state used by systems like Vertex AI Pipelines to indicate that the
     // underlying data item represented by this Artifact is being created.
     PENDING = 1;
 
@@ -84,7 +84,7 @@ message Artifact {
 
   // The state of this Artifact. This is a property of the Artifact, and does
   // not imply or capture any ongoing process. This property is managed by
-  // clients (such as Vertex Pipelines), and the system does not prescribe
+  // clients (such as Vertex AI Pipelines), and the system does not prescribe
   // or check the validity of state transitions.
   State state = 13;
 

packages/google-cloud-aiplatform/protos/google/cloud/aiplatform/v1beta1/batch_prediction_job.proto

@@ -26,6 +26,7 @@ import "google/cloud/aiplatform/v1beta1/job_state.proto";
 import "google/cloud/aiplatform/v1beta1/machine_resources.proto";
 import "google/cloud/aiplatform/v1beta1/manual_batch_tuning_parameters.proto";
 import "google/cloud/aiplatform/v1beta1/model_monitoring.proto";
+import "google/cloud/aiplatform/v1beta1/unmanaged_container_model.proto";
 import "google/protobuf/struct.proto";
 import "google/protobuf/timestamp.proto";
 import "google/rpc/status.proto";
@@ -155,16 +156,19 @@ message BatchPredictionJob {
   // Required. The user-defined name of this BatchPredictionJob.
   string display_name = 2 [(google.api.field_behavior) = REQUIRED];
 
-  // Required. The name of the Model that produces the predictions via this job,
+  // The name of the Model resoure that produces the predictions via this job,
   // must share the same ancestor Location.
   // Starting this job has no impact on any existing deployments of the Model
   // and their resources.
-  string model = 3 [
-    (google.api.field_behavior) = REQUIRED,
-    (google.api.resource_reference) = {
-      type: "aiplatform.googleapis.com/Model"
-    }
-  ];
+  // Exactly one of model and unmanaged_container_model must be set.
+  string model = 3 [(google.api.resource_reference) = {
+                      type: "aiplatform.googleapis.com/Model"
+                    }];
+
+  // Contains model information necessary to perform batch prediction without
+  // requiring uploading to model registry.
+  // Exactly one of model and unmanaged_container_model must be set.
+  UnmanagedContainerModel unmanaged_container_model = 28;
 
   // Required. Input configuration of the instances on which predictions are performed.
   // The schema of any single instance may be specified via

packages/google-cloud-aiplatform/protos/google/cloud/aiplatform/v1beta1/custom_job.proto

@@ -131,8 +131,11 @@ message CustomJobSpec {
   // Where {project} is a project number, as in `12345`, and {network} is a
   // network name.
   //
-  // Private services access must already be configured for the network. If left
-  // unspecified, the job is not peered with any network.
+  // To specify this field, you must have already [configured VPC Network
+  // Peering for Vertex
+  // AI](https://cloud.google.com/vertex-ai/docs/general/vpc-peering).
+  //
+  // If this field is left unspecified, the job is not peered with any network.
   string network = 5 [(google.api.resource_reference) = {
                         type: "compute.googleapis.com/Network"
                       }];

packages/google-cloud-aiplatform/protos/google/cloud/aiplatform/v1beta1/endpoint.proto

@@ -20,6 +20,7 @@ import "google/api/field_behavior.proto";
 import "google/api/resource.proto";
 import "google/cloud/aiplatform/v1beta1/encryption_spec.proto";
 import "google/cloud/aiplatform/v1beta1/explanation.proto";
+import "google/cloud/aiplatform/v1beta1/io.proto";
 import "google/cloud/aiplatform/v1beta1/machine_resources.proto";
 import "google/cloud/aiplatform/v1beta1/model_deployment_monitoring_job.proto";
 import "google/cloud/aiplatform/v1beta1/model_monitoring.proto";
@@ -93,20 +94,31 @@ message Endpoint {
   EncryptionSpec encryption_spec = 10;
 
   // The full name of the Google Compute Engine
-  // [network](/compute/docs/networks-and-firewalls#networks) to which the
-  // Endpoint should be peered.
+  // [network](https://cloud.google.com//compute/docs/networks-and-firewalls#networks)
+  // to which the Endpoint should be peered.
   //
   // Private services access must already be configured for the network. If left
   // unspecified, the Endpoint is not peered with any network.
   //
+  // Only one of the fields, [network][google.cloud.aiplatform.v1beta1.Endpoint.network] or
+  // [enable_private_service_connect][google.cloud.aiplatform.v1beta1.Endpoint.enable_private_service_connect],
+  // can be set.
+  //
   // [Format](https://cloud.google.com/compute/docs/reference/rest/v1/networks/insert):
-  // projects/{project}/global/networks/{network}.
-  // Where {project} is a project number, as in '12345', and {network} is
+  // `projects/{project}/global/networks/{network}`.
+  // Where `{project}` is a project number, as in `12345`, and `{network}` is
   // network name.
   string network = 13 [(google.api.resource_reference) = {
                          type: "compute.googleapis.com/Network"
                        }];
 
+  // If true, expose the Endpoint via private service connect.
+  //
+  // Only one of the fields, [network][google.cloud.aiplatform.v1beta1.Endpoint.network] or
+  // [enable_private_service_connect][google.cloud.aiplatform.v1beta1.Endpoint.enable_private_service_connect],
+  // can be set.
+  bool enable_private_service_connect = 17;
+
   // Output only. Resource name of the Model Monitoring job associated with this Endpoint
   // if monitoring is enabled by [CreateModelDeploymentMonitoringJob][].
   // Format:
@@ -136,8 +148,11 @@ message DeployedModel {
     AutomaticResources automatic_resources = 8;
   }
 
-  // Output only. The ID of the DeployedModel.
-  string id = 1 [(google.api.field_behavior) = OUTPUT_ONLY];
+  // Immutable. The ID of the DeployedModel. If not provided upon deployment, Vertex AI
+  // will generate a value for this ID.
+  //
+  // This value should be 1-10 characters, and valid characters are /[0-9]/.
+  string id = 1 [(google.api.field_behavior) = IMMUTABLE];
 
   // Required. The name of the Model that this is the deployment of. Note that the Model
   // may be in a different location than the DeployedModel's Endpoint.
@@ -195,8 +210,11 @@ message DeployedModel {
   PrivateEndpoints private_endpoints = 14 [(google.api.field_behavior) = OUTPUT_ONLY];
 }
 
-// PrivateEndpoints is used to provide paths for users to send
-// requests via private services access.
+// PrivateEndpoints proto is used to provide paths for users to send
+// requests privately.
+// To send request via private service access, use predict_http_uri,
+// explain_http_uri or health_http_uri. To send request via private service
+// connect, use service_attachment.
 message PrivateEndpoints {
   // Output only. Http(s) path to send prediction requests.
   string predict_http_uri = 1 [(google.api.field_behavior) = OUTPUT_ONLY];
@@ -206,4 +224,8 @@ message PrivateEndpoints {
 
   // Output only. Http(s) path to send health check requests.
   string health_http_uri = 3 [(google.api.field_behavior) = OUTPUT_ONLY];
+
+  // Output only. The name of the service attachment resource. Populated if private service
+  // connect is enabled.
+  string service_attachment = 4 [(google.api.field_behavior) = OUTPUT_ONLY];
 }

packages/google-cloud-aiplatform/protos/google/cloud/aiplatform/v1beta1/endpoint_service.proto

@@ -45,6 +45,7 @@ service EndpointService {
       body: "endpoint"
     };
     option (google.api.method_signature) = "parent,endpoint";
+    option (google.api.method_signature) = "parent,endpoint,endpoint_id";
     option (google.longrunning.operation_info) = {
       response_type: "Endpoint"
       metadata_type: "CreateEndpointOperationMetadata"
@@ -129,6 +130,16 @@ message CreateEndpointRequest {
 
   // Required. The Endpoint to create.
   Endpoint endpoint = 2 [(google.api.field_behavior) = REQUIRED];
+
+  // Immutable. The ID to use for endpoint, which will become the final
+  // component of the endpoint resource name.
+  // If not provided, Vertex AI will generate a value for this ID.
+  //
+  // This value should be 1-10 characters, and valid characters are /[0-9]/.
+  // When using HTTP/JSON, this field is populated based on a query string
+  // argument, such as `?endpoint_id=12345`. This is the fallback for fields
+  // that are not included in either the URI or the body.
+  string endpoint_id = 4 [(google.api.field_behavior) = IMMUTABLE];
 }
 
 // Runtime operation information for [EndpointService.CreateEndpoint][google.cloud.aiplatform.v1beta1.EndpointService.CreateEndpoint].

packages/google-cloud-aiplatform/protos/google/cloud/aiplatform/v1beta1/execution.proto

@@ -71,7 +71,7 @@ message Execution {
 
   // The state of this Execution. This is a property of the Execution, and does
   // not imply or capture any ongoing process. This property is managed by
-  // clients (such as Vertex Pipelines) and the system does not prescribe
+  // clients (such as Vertex AI Pipelines) and the system does not prescribe
   // or check the validity of state transitions.
   State state = 6;
 

packages/google-cloud-aiplatform/protos/google/cloud/aiplatform/v1beta1/explanation.proto

@@ -252,6 +252,14 @@ message IntegratedGradientsAttribution {
   // noise can help improve the computed gradients. Refer to this paper for more
   // details: https://arxiv.org/pdf/1706.03825.pdf
   SmoothGradConfig smooth_grad_config = 2;
+
+  // Config for IG with blur baseline.
+  //
+  // When enabled, a linear path from the maximally blurred image to the input
+  // image is created. Using a blurred baseline instead of zero (black image) is
+  // motivated by the BlurIG approach explained here:
+  // https://arxiv.org/abs/2004.03383
+  BlurBaselineConfig blur_baseline_config = 3;
 }
 
 // An explanation method that redistributes Integrated Gradients
@@ -275,6 +283,14 @@ message XraiAttribution {
   // noise can help improve the computed gradients. Refer to this paper for more
   // details: https://arxiv.org/pdf/1706.03825.pdf
   SmoothGradConfig smooth_grad_config = 2;
+
+  // Config for XRAI with blur baseline.
+  //
+  // When enabled, a linear path from the maximally blurred image to the input
+  // image is created. Using a blurred baseline instead of zero (black image) is
+  // motivated by the BlurIG approach explained here:
+  // https://arxiv.org/abs/2004.03383
+  BlurBaselineConfig blur_baseline_config = 3;
 }
 
 // Config for SmoothGrad approximation of gradients.
@@ -341,6 +357,20 @@ message FeatureNoiseSigma {
   repeated NoiseSigmaForFeature noise_sigma = 1;
 }
 
+// Config for blur baseline.
+//
+// When enabled, a linear path from the maximally blurred image to the input
+// image is created. Using a blurred baseline instead of zero (black image) is
+// motivated by the BlurIG approach explained here:
+// https://arxiv.org/abs/2004.03383
+message BlurBaselineConfig {
+  // The standard deviation of the blur kernel for the blurred baseline. The
+  // same blurring parameter is used for both the height and the width
+  // dimension. If not set, the method defaults to the zero (i.e. black for
+  // images) baseline.
+  float max_blur_sigma = 1;
+}
+
 // Similarity explainability that returns the nearest neighbors from the
 // provided dataset.
 message Similarity {

packages/google-cloud-aiplatform/protos/google/cloud/aiplatform/v1beta1/feature.proto

@@ -129,7 +129,7 @@ message Feature {
   FeaturestoreMonitoringConfig monitoring_config = 9 [(google.api.field_behavior) = OPTIONAL];
 
   // Output only. A list of historical [Snapshot
-  // Analysis][google.cloud.aiplatform.master.FeaturestoreMonitoringConfig.SnapshotAnalysis]
+  // Analysis][FeaturestoreMonitoringConfig.SnapshotAnalysis]
   // stats requested by user, sorted by [FeatureStatsAnomaly.start_time][google.cloud.aiplatform.v1beta1.FeatureStatsAnomaly.start_time]
   // descending.
   repeated FeatureStatsAnomaly monitoring_stats = 10 [(google.api.field_behavior) = OUTPUT_ONLY];

packages/google-cloud-aiplatform/protos/google/cloud/aiplatform/v1beta1/featurestore.proto

@@ -30,7 +30,9 @@ option java_package = "com.google.cloud.aiplatform.v1beta1";
 option php_namespace = "Google\\Cloud\\AIPlatform\\V1beta1";
 option ruby_package = "Google::Cloud::AIPlatform::V1beta1";
 
-// Featurestore configuration information on how the Featurestore is configured.
+// Vertex AI Feature Store provides a centralized repository for organizing,
+// storing, and serving ML features. The Featurestore is a top-level container
+// for your features and their values.
 message Featurestore {
   option (google.api.resource) = {
     type: "aiplatform.googleapis.com/Featurestore"

packages/google-cloud-aiplatform/protos/google/cloud/aiplatform/v1beta1/featurestore_online_service.proto

@@ -178,7 +178,9 @@ message FeatureValue {
     // Feature generation timestamp. Typically, it is provided by user at
     // feature ingestion time. If not, feature store
     // will use the system timestamp when the data is ingested into feature
-    // store.
+    // store. For streaming ingestion, the time, aligned by days, must be no
+    // older than five years (1825 days) and no later than one year (366 days)
+    // in the future.
     google.protobuf.Timestamp generate_time = 1;
   }
 

packages/google-cloud-aiplatform/protos/google/cloud/aiplatform/v1beta1/featurestore_service.proto

@@ -51,6 +51,7 @@ service FeaturestoreService {
       body: "featurestore"
     };
     option (google.api.method_signature) = "parent,featurestore";
+    option (google.api.method_signature) = "parent,featurestore,featurestore_id";
     option (google.longrunning.operation_info) = {
       response_type: "Featurestore"
       metadata_type: "CreateFeaturestoreOperationMetadata"
@@ -107,6 +108,7 @@ service FeaturestoreService {
       body: "entity_type"
     };
     option (google.api.method_signature) = "parent,entity_type";
+    option (google.api.method_signature) = "parent,entity_type,entity_type_id";
     option (google.longrunning.operation_info) = {
       response_type: "EntityType"
       metadata_type: "CreateEntityTypeOperationMetadata"
@@ -159,6 +161,7 @@ service FeaturestoreService {
       body: "feature"
     };
     option (google.api.method_signature) = "parent,feature";
+    option (google.api.method_signature) = "parent,feature,feature_id";
     option (google.longrunning.operation_info) = {
       response_type: "Feature"
       metadata_type: "CreateFeatureOperationMetadata"
@@ -608,18 +611,43 @@ message BatchReadFeatureValuesRequest {
 
 // Request message for [FeaturestoreService.ExportFeatureValues][google.cloud.aiplatform.v1beta1.FeaturestoreService.ExportFeatureValues].
 message ExportFeatureValuesRequest {
-  // Describes exporting Feature values as of the snapshot timestamp.
+  // Describes exporting the latest Feature values of all entities of the
+  // EntityType between [start_time, snapshot_time].
   message SnapshotExport {
     // Exports Feature values as of this timestamp. If not set,
     // retrieve values as of now. Timestamp, if present, must not have higher
     // than millisecond precision.
     google.protobuf.Timestamp snapshot_time = 1;
+
+    // Excludes Feature values with feature generation timestamp before this
+    // timestamp. If not set, retrieve oldest values kept in Feature Store.
+    // Timestamp, if present, must not have higher than millisecond precision.
+    google.protobuf.Timestamp start_time = 2;
   }
 
+  // Describes exporting all historical Feature values of all entities of the
+  // EntityType between [start_time, end_time].
+  message FullExport {
+    // Excludes Feature values with feature generation timestamp before this
+    // timestamp. If not set, retrieve oldest values kept in Feature Store.
+    // Timestamp, if present, must not have higher than millisecond precision.
+    google.protobuf.Timestamp start_time = 2;
+
+    // Exports Feature values as of this timestamp. If not set,
+    // retrieve values as of now. Timestamp, if present, must not have higher
+    // than millisecond precision.
+    google.protobuf.Timestamp end_time = 1;
+  }
+
+  // Required. The mode in which Feature values are exported.
   oneof mode {
-    // Exports Feature values of all entities of the EntityType as of a snapshot
-    // time.
+    // Exports the latest Feature values of all entities of the EntityType
+    // within a time range.
     SnapshotExport snapshot_export = 3;
+
+    // Exports all historical values of all entities of the EntityType within a
+    // time range
+    FullExport full_export = 7;
   }
 
   // Required. The resource name of the EntityType from which to export Feature values.
@@ -1141,15 +1169,15 @@ message UpdateFeaturestoreOperationMetadata {
   GenericOperationMetadata generic_metadata = 1;
 }
 
-// Details of operations that perform import feature values.
+// Details of operations that perform import Feature values.
 message ImportFeatureValuesOperationMetadata {
-  // Operation metadata for Featurestore import feature values.
+  // Operation metadata for Featurestore import Feature values.
   GenericOperationMetadata generic_metadata = 1;
 
   // Number of entities that have been imported by the operation.
   int64 imported_entity_count = 2;
 
-  // Number of feature values that have been imported by the operation.
+  // Number of Feature values that have been imported by the operation.
   int64 imported_feature_value_count = 3;
 
   // The number of rows in input source that weren't imported due to either