aiplatform/apiv1/aiplatformpb/feature_monitoring_stats.pb.go - gocloud - Git at Google

 // Copyright 2023 Google LLC
 //
 // Licensed under the Apache License, Version 2.0 (the "License");
 // you may not use this file except in compliance with the License.
 // You may obtain a copy of the License at
 //
 //     http://www.apache.org/licenses/LICENSE-2.0
 //
 // Unless required by applicable law or agreed to in writing, software
 // distributed under the License is distributed on an "AS IS" BASIS,
 // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 // See the License for the specific language governing permissions and
 // limitations under the License.

 // Code generated by protoc-gen-go. DO NOT EDIT.
 // versions:
 // 	protoc-gen-go v1.33.0
 // 	protoc        v4.25.3
 // source: google/cloud/aiplatform/v1/feature_monitoring_stats.proto

 package aiplatformpb

 import (
 	reflect "reflect"
 	sync "sync"

 	protoreflect "google.golang.org/protobuf/reflect/protoreflect"
 	protoimpl "google.golang.org/protobuf/runtime/protoimpl"
 	timestamppb "google.golang.org/protobuf/types/known/timestamppb"
 )

 const (
 	// Verify that this generated code is sufficiently up-to-date.
 	_ = protoimpl.EnforceVersion(20 - protoimpl.MinVersion)
 	// Verify that runtime/protoimpl is sufficiently up-to-date.
 	_ = protoimpl.EnforceVersion(protoimpl.MaxVersion - 20)
 )

 // Stats and Anomaly generated at specific timestamp for specific Feature.
 // The start_time and end_time are used to define the time range of the dataset
 // that current stats belongs to, e.g. prediction traffic is bucketed into
 // prediction datasets by time window. If the Dataset is not defined by time
 // window, start_time = end_time. Timestamp of the stats and anomalies always
 // refers to end_time. Raw stats and anomalies are stored in stats_uri or
 // anomaly_uri in the tensorflow defined protos. Field data_stats contains
 // almost identical information with the raw stats in Vertex AI
 // defined proto, for UI to display.
 type FeatureStatsAnomaly struct {
 	state         protoimpl.MessageState
 	sizeCache     protoimpl.SizeCache
 	unknownFields protoimpl.UnknownFields

 	// Feature importance score, only populated when cross-feature monitoring is
 	// enabled. For now only used to represent feature attribution score within
 	// range [0, 1] for
 	// [ModelDeploymentMonitoringObjectiveType.FEATURE_ATTRIBUTION_SKEW][google.cloud.aiplatform.v1.ModelDeploymentMonitoringObjectiveType.FEATURE_ATTRIBUTION_SKEW]
 	// and
 	// [ModelDeploymentMonitoringObjectiveType.FEATURE_ATTRIBUTION_DRIFT][google.cloud.aiplatform.v1.ModelDeploymentMonitoringObjectiveType.FEATURE_ATTRIBUTION_DRIFT].
 	Score float64 `protobuf:"fixed64,1,opt,name=score,proto3" json:"score,omitempty"`
 	// Path of the stats file for current feature values in Cloud Storage bucket.
 	// Format: gs://<bucket_name>/<object_name>/stats.
 	// Example: gs://monitoring_bucket/feature_name/stats.
 	// Stats are stored as binary format with Protobuf message
 	// [tensorflow.metadata.v0.FeatureNameStatistics](https://github.com/tensorflow/metadata/blob/master/tensorflow_metadata/proto/v0/statistics.proto).
 	StatsUri string `protobuf:"bytes,3,opt,name=stats_uri,json=statsUri,proto3" json:"stats_uri,omitempty"`
 	// Path of the anomaly file for current feature values in Cloud Storage
 	// bucket.
 	// Format: gs://<bucket_name>/<object_name>/anomalies.
 	// Example: gs://monitoring_bucket/feature_name/anomalies.
 	// Stats are stored as binary format with Protobuf message
 	// Anoamlies are stored as binary format with Protobuf message
 	// [tensorflow.metadata.v0.AnomalyInfo]
 	// (https://github.com/tensorflow/metadata/blob/master/tensorflow_metadata/proto/v0/anomalies.proto).
 	AnomalyUri string `protobuf:"bytes,4,opt,name=anomaly_uri,json=anomalyUri,proto3" json:"anomaly_uri,omitempty"`
 	// Deviation from the current stats to baseline stats.
 	//  1. For categorical feature, the distribution distance is calculated by
 	//     L-inifinity norm.
 	//  2. For numerical feature, the distribution distance is calculated by
 	//     Jensen–Shannon divergence.
 	DistributionDeviation float64 `protobuf:"fixed64,5,opt,name=distribution_deviation,json=distributionDeviation,proto3" json:"distribution_deviation,omitempty"`
 	// This is the threshold used when detecting anomalies.
 	// The threshold can be changed by user, so this one might be different from
 	// [ThresholdConfig.value][google.cloud.aiplatform.v1.ThresholdConfig.value].
 	AnomalyDetectionThreshold float64 `protobuf:"fixed64,9,opt,name=anomaly_detection_threshold,json=anomalyDetectionThreshold,proto3" json:"anomaly_detection_threshold,omitempty"`
 	// The start timestamp of window where stats were generated.
 	// For objectives where time window doesn't make sense (e.g. Featurestore
 	// Snapshot Monitoring), start_time is only used to indicate the monitoring
 	// intervals, so it always equals to (end_time - monitoring_interval).
 	StartTime *timestamppb.Timestamp `protobuf:"bytes,7,opt,name=start_time,json=startTime,proto3" json:"start_time,omitempty"`
 	// The end timestamp of window where stats were generated.
 	// For objectives where time window doesn't make sense (e.g. Featurestore
 	// Snapshot Monitoring), end_time indicates the timestamp of the data used to
 	// generate stats (e.g. timestamp we take snapshots for feature values).
 	EndTime *timestamppb.Timestamp `protobuf:"bytes,8,opt,name=end_time,json=endTime,proto3" json:"end_time,omitempty"`
 }

 func (x *FeatureStatsAnomaly) Reset() {
 	*x = FeatureStatsAnomaly{}
 	if protoimpl.UnsafeEnabled {
 		mi := &file_google_cloud_aiplatform_v1_feature_monitoring_stats_proto_msgTypes[0]
 		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
 		ms.StoreMessageInfo(mi)
 	}
 }

 func (x *FeatureStatsAnomaly) String() string {
 	return protoimpl.X.MessageStringOf(x)
 }

 func (*FeatureStatsAnomaly) ProtoMessage() {}

 func (x *FeatureStatsAnomaly) ProtoReflect() protoreflect.Message {
 	mi := &file_google_cloud_aiplatform_v1_feature_monitoring_stats_proto_msgTypes[0]
 	if protoimpl.UnsafeEnabled && x != nil {
 		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
 		if ms.LoadMessageInfo() == nil {
 			ms.StoreMessageInfo(mi)
 		}
 		return ms
 	}
 	return mi.MessageOf(x)
 }

 // Deprecated: Use FeatureStatsAnomaly.ProtoReflect.Descriptor instead.
 func (*FeatureStatsAnomaly) Descriptor() ([]byte, []int) {
 	return file_google_cloud_aiplatform_v1_feature_monitoring_stats_proto_rawDescGZIP(), []int{0}
 }

 func (x *FeatureStatsAnomaly) GetScore() float64 {
 	if x != nil {
 		return x.Score
 	}
 	return 0
 }

 func (x *FeatureStatsAnomaly) GetStatsUri() string {
 	if x != nil {
 		return x.StatsUri
 	}
 	return ""
 }

 func (x *FeatureStatsAnomaly) GetAnomalyUri() string {
 	if x != nil {
 		return x.AnomalyUri
 	}
 	return ""
 }

 func (x *FeatureStatsAnomaly) GetDistributionDeviation() float64 {
 	if x != nil {
 		return x.DistributionDeviation
 	}
 	return 0
 }

 func (x *FeatureStatsAnomaly) GetAnomalyDetectionThreshold() float64 {
 	if x != nil {
 		return x.AnomalyDetectionThreshold
 	}
 	return 0
 }

 func (x *FeatureStatsAnomaly) GetStartTime() *timestamppb.Timestamp {
 	if x != nil {
 		return x.StartTime
 	}
 	return nil
 }

 func (x *FeatureStatsAnomaly) GetEndTime() *timestamppb.Timestamp {
 	if x != nil {
 		return x.EndTime
 	}
 	return nil
 }

 var File_google_cloud_aiplatform_v1_feature_monitoring_stats_proto protoreflect.FileDescriptor

 var file_google_cloud_aiplatform_v1_feature_monitoring_stats_proto_rawDesc = []byte{
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 var (
 	file_google_cloud_aiplatform_v1_feature_monitoring_stats_proto_rawDescOnce sync.Once
 	file_google_cloud_aiplatform_v1_feature_monitoring_stats_proto_rawDescData = file_google_cloud_aiplatform_v1_feature_monitoring_stats_proto_rawDesc
 )

 func file_google_cloud_aiplatform_v1_feature_monitoring_stats_proto_rawDescGZIP() []byte {
 	file_google_cloud_aiplatform_v1_feature_monitoring_stats_proto_rawDescOnce.Do(func() {
 		file_google_cloud_aiplatform_v1_feature_monitoring_stats_proto_rawDescData = protoimpl.X.CompressGZIP(file_google_cloud_aiplatform_v1_feature_monitoring_stats_proto_rawDescData)
 	})
 	return file_google_cloud_aiplatform_v1_feature_monitoring_stats_proto_rawDescData
 }

 var file_google_cloud_aiplatform_v1_feature_monitoring_stats_proto_msgTypes = make([]protoimpl.MessageInfo, 1)
 var file_google_cloud_aiplatform_v1_feature_monitoring_stats_proto_goTypes = []interface{}{
 	(*FeatureStatsAnomaly)(nil),   // 0: google.cloud.aiplatform.v1.FeatureStatsAnomaly
 	(*timestamppb.Timestamp)(nil), // 1: google.protobuf.Timestamp
 }
 var file_google_cloud_aiplatform_v1_feature_monitoring_stats_proto_depIdxs = []int32{
 	1, // 0: google.cloud.aiplatform.v1.FeatureStatsAnomaly.start_time:type_name -> google.protobuf.Timestamp
 	1, // 1: google.cloud.aiplatform.v1.FeatureStatsAnomaly.end_time:type_name -> google.protobuf.Timestamp
 	2, // [2:2] is the sub-list for method output_type
 	2, // [2:2] is the sub-list for method input_type
 	2, // [2:2] is the sub-list for extension type_name
 	2, // [2:2] is the sub-list for extension extendee
 	0, // [0:2] is the sub-list for field type_name
 }

 func init() { file_google_cloud_aiplatform_v1_feature_monitoring_stats_proto_init() }
 func file_google_cloud_aiplatform_v1_feature_monitoring_stats_proto_init() {
 	if File_google_cloud_aiplatform_v1_feature_monitoring_stats_proto != nil {
 		return
 	}
 	if !protoimpl.UnsafeEnabled {
 		file_google_cloud_aiplatform_v1_feature_monitoring_stats_proto_msgTypes[0].Exporter = func(v interface{}, i int) interface{} {
 			switch v := v.(*FeatureStatsAnomaly); i {
 			case 0:
 				return &v.state
 			case 1:
 				return &v.sizeCache
 			case 2:
 				return &v.unknownFields
 			default:
 				return nil
 			}
 		}
 	}
 	type x struct{}
 	out := protoimpl.TypeBuilder{
 		File: protoimpl.DescBuilder{
 			GoPackagePath: reflect.TypeOf(x{}).PkgPath(),
 			RawDescriptor: file_google_cloud_aiplatform_v1_feature_monitoring_stats_proto_rawDesc,
 			NumEnums:      0,
 			NumMessages:   1,
 			NumExtensions: 0,
 			NumServices:   0,
 		},
 		GoTypes:           file_google_cloud_aiplatform_v1_feature_monitoring_stats_proto_goTypes,
 		DependencyIndexes: file_google_cloud_aiplatform_v1_feature_monitoring_stats_proto_depIdxs,
 		MessageInfos:      file_google_cloud_aiplatform_v1_feature_monitoring_stats_proto_msgTypes,
 	}.Build()
 	File_google_cloud_aiplatform_v1_feature_monitoring_stats_proto = out.File
 	file_google_cloud_aiplatform_v1_feature_monitoring_stats_proto_rawDesc = nil
 	file_google_cloud_aiplatform_v1_feature_monitoring_stats_proto_goTypes = nil
 	file_google_cloud_aiplatform_v1_feature_monitoring_stats_proto_depIdxs = nil
 }
	// Copyright 2023 Google LLC
	//
	// Licensed under the Apache License, Version 2.0 (the "License");
	// you may not use this file except in compliance with the License.
	// You may obtain a copy of the License at
	//
	// http://www.apache.org/licenses/LICENSE-2.0
	//
	// Unless required by applicable law or agreed to in writing, software
	// distributed under the License is distributed on an "AS IS" BASIS,
	// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
	// See the License for the specific language governing permissions and
	// limitations under the License.

	// Code generated by protoc-gen-go. DO NOT EDIT.
	// versions:
	// protoc-gen-go v1.33.0
	// protoc v4.25.3
	// source: google/cloud/aiplatform/v1/feature_monitoring_stats.proto

	package aiplatformpb

	import (
	reflect "reflect"
	sync "sync"

	protoreflect "google.golang.org/protobuf/reflect/protoreflect"
	protoimpl "google.golang.org/protobuf/runtime/protoimpl"
	timestamppb "google.golang.org/protobuf/types/known/timestamppb"
	)

	const (
	// Verify that this generated code is sufficiently up-to-date.
	_ = protoimpl.EnforceVersion(20 - protoimpl.MinVersion)
	// Verify that runtime/protoimpl is sufficiently up-to-date.
	_ = protoimpl.EnforceVersion(protoimpl.MaxVersion - 20)
	)

	// Stats and Anomaly generated at specific timestamp for specific Feature.
	// The start_time and end_time are used to define the time range of the dataset
	// that current stats belongs to, e.g. prediction traffic is bucketed into
	// prediction datasets by time window. If the Dataset is not defined by time
	// window, start_time = end_time. Timestamp of the stats and anomalies always
	// refers to end_time. Raw stats and anomalies are stored in stats_uri or
	// anomaly_uri in the tensorflow defined protos. Field data_stats contains
	// almost identical information with the raw stats in Vertex AI
	// defined proto, for UI to display.
	type FeatureStatsAnomaly struct {
	state protoimpl.MessageState
	sizeCache protoimpl.SizeCache
	unknownFields protoimpl.UnknownFields

	// Feature importance score, only populated when cross-feature monitoring is
	// enabled. For now only used to represent feature attribution score within
	// range [0, 1] for
	// [ModelDeploymentMonitoringObjectiveType.FEATURE_ATTRIBUTION_SKEW][google.cloud.aiplatform.v1.ModelDeploymentMonitoringObjectiveType.FEATURE_ATTRIBUTION_SKEW]
	// and
	// [ModelDeploymentMonitoringObjectiveType.FEATURE_ATTRIBUTION_DRIFT][google.cloud.aiplatform.v1.ModelDeploymentMonitoringObjectiveType.FEATURE_ATTRIBUTION_DRIFT].
	Score float64 `protobuf:"fixed64,1,opt,name=score,proto3" json:"score,omitempty"`
	// Path of the stats file for current feature values in Cloud Storage bucket.
	// Format: gs://<bucket_name>/<object_name>/stats.
	// Example: gs://monitoring_bucket/feature_name/stats.
	// Stats are stored as binary format with Protobuf message
	// [tensorflow.metadata.v0.FeatureNameStatistics](https://github.com/tensorflow/metadata/blob/master/tensorflow_metadata/proto/v0/statistics.proto).
	StatsUri string `protobuf:"bytes,3,opt,name=stats_uri,json=statsUri,proto3" json:"stats_uri,omitempty"`
	// Path of the anomaly file for current feature values in Cloud Storage
	// bucket.
	// Format: gs://<bucket_name>/<object_name>/anomalies.
	// Example: gs://monitoring_bucket/feature_name/anomalies.
	// Stats are stored as binary format with Protobuf message
	// Anoamlies are stored as binary format with Protobuf message
	// [tensorflow.metadata.v0.AnomalyInfo]
	// (https://github.com/tensorflow/metadata/blob/master/tensorflow_metadata/proto/v0/anomalies.proto).
	AnomalyUri string `protobuf:"bytes,4,opt,name=anomaly_uri,json=anomalyUri,proto3" json:"anomaly_uri,omitempty"`
	// Deviation from the current stats to baseline stats.
	// 1. For categorical feature, the distribution distance is calculated by
	// L-inifinity norm.
	// 2. For numerical feature, the distribution distance is calculated by
	// Jensen–Shannon divergence.
	DistributionDeviation float64 `protobuf:"fixed64,5,opt,name=distribution_deviation,json=distributionDeviation,proto3" json:"distribution_deviation,omitempty"`
	// This is the threshold used when detecting anomalies.
	// The threshold can be changed by user, so this one might be different from
	// [ThresholdConfig.value][google.cloud.aiplatform.v1.ThresholdConfig.value].
	AnomalyDetectionThreshold float64 `protobuf:"fixed64,9,opt,name=anomaly_detection_threshold,json=anomalyDetectionThreshold,proto3" json:"anomaly_detection_threshold,omitempty"`
	// The start timestamp of window where stats were generated.
	// For objectives where time window doesn't make sense (e.g. Featurestore
	// Snapshot Monitoring), start_time is only used to indicate the monitoring
	// intervals, so it always equals to (end_time - monitoring_interval).
	StartTime *timestamppb.Timestamp `protobuf:"bytes,7,opt,name=start_time,json=startTime,proto3" json:"start_time,omitempty"`
	// The end timestamp of window where stats were generated.
	// For objectives where time window doesn't make sense (e.g. Featurestore
	// Snapshot Monitoring), end_time indicates the timestamp of the data used to
	// generate stats (e.g. timestamp we take snapshots for feature values).
	EndTime *timestamppb.Timestamp `protobuf:"bytes,8,opt,name=end_time,json=endTime,proto3" json:"end_time,omitempty"`
	}

	func (x *FeatureStatsAnomaly) Reset() {
	*x = FeatureStatsAnomaly{}
	if protoimpl.UnsafeEnabled {
	mi := &file_google_cloud_aiplatform_v1_feature_monitoring_stats_proto_msgTypes[0]
	ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
	ms.StoreMessageInfo(mi)
	}
	}

	func (x *FeatureStatsAnomaly) String() string {
	return protoimpl.X.MessageStringOf(x)
	}

	func (*FeatureStatsAnomaly) ProtoMessage() {}

	func (x *FeatureStatsAnomaly) ProtoReflect() protoreflect.Message {
	mi := &file_google_cloud_aiplatform_v1_feature_monitoring_stats_proto_msgTypes[0]
	if protoimpl.UnsafeEnabled && x != nil {
	ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
	if ms.LoadMessageInfo() == nil {
	ms.StoreMessageInfo(mi)
	}
	return ms
	}
	return mi.MessageOf(x)
	}

	// Deprecated: Use FeatureStatsAnomaly.ProtoReflect.Descriptor instead.
	func (*FeatureStatsAnomaly) Descriptor() ([]byte, []int) {
	return file_google_cloud_aiplatform_v1_feature_monitoring_stats_proto_rawDescGZIP(), []int{0}
	}

	func (x *FeatureStatsAnomaly) GetScore() float64 {
	if x != nil {
	return x.Score
	}
	return 0
	}

	func (x *FeatureStatsAnomaly) GetStatsUri() string {
	if x != nil {
	return x.StatsUri
	}
	return ""
	}

	func (x *FeatureStatsAnomaly) GetAnomalyUri() string {
	if x != nil {
	return x.AnomalyUri
	}
	return ""
	}

	func (x *FeatureStatsAnomaly) GetDistributionDeviation() float64 {
	if x != nil {
	return x.DistributionDeviation
	}
	return 0
	}

	func (x *FeatureStatsAnomaly) GetAnomalyDetectionThreshold() float64 {
	if x != nil {
	return x.AnomalyDetectionThreshold
	}
	return 0
	}

	func (x FeatureStatsAnomaly) GetStartTime() timestamppb.Timestamp {
	if x != nil {
	return x.StartTime
	}
	return nil
	}

	func (x FeatureStatsAnomaly) GetEndTime() timestamppb.Timestamp {
	if x != nil {
	return x.EndTime
	}
	return nil
	}

	var File_google_cloud_aiplatform_v1_feature_monitoring_stats_proto protoreflect.FileDescriptor

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	var (
	file_google_cloud_aiplatform_v1_feature_monitoring_stats_proto_rawDescOnce sync.Once
	file_google_cloud_aiplatform_v1_feature_monitoring_stats_proto_rawDescData = file_google_cloud_aiplatform_v1_feature_monitoring_stats_proto_rawDesc
	)

	func file_google_cloud_aiplatform_v1_feature_monitoring_stats_proto_rawDescGZIP() []byte {
	file_google_cloud_aiplatform_v1_feature_monitoring_stats_proto_rawDescOnce.Do(func() {
	file_google_cloud_aiplatform_v1_feature_monitoring_stats_proto_rawDescData = protoimpl.X.CompressGZIP(file_google_cloud_aiplatform_v1_feature_monitoring_stats_proto_rawDescData)
	})
	return file_google_cloud_aiplatform_v1_feature_monitoring_stats_proto_rawDescData
	}

	var file_google_cloud_aiplatform_v1_feature_monitoring_stats_proto_msgTypes = make([]protoimpl.MessageInfo, 1)
	var file_google_cloud_aiplatform_v1_feature_monitoring_stats_proto_goTypes = []interface{}{
	(*FeatureStatsAnomaly)(nil), // 0: google.cloud.aiplatform.v1.FeatureStatsAnomaly
	(*timestamppb.Timestamp)(nil), // 1: google.protobuf.Timestamp
	}
	var file_google_cloud_aiplatform_v1_feature_monitoring_stats_proto_depIdxs = []int32{
	1, // 0: google.cloud.aiplatform.v1.FeatureStatsAnomaly.start_time:type_name -> google.protobuf.Timestamp
	1, // 1: google.cloud.aiplatform.v1.FeatureStatsAnomaly.end_time:type_name -> google.protobuf.Timestamp
	2, // [2:2] is the sub-list for method output_type
	2, // [2:2] is the sub-list for method input_type
	2, // [2:2] is the sub-list for extension type_name
	2, // [2:2] is the sub-list for extension extendee
	0, // [0:2] is the sub-list for field type_name
	}

	func init() { file_google_cloud_aiplatform_v1_feature_monitoring_stats_proto_init() }
	func file_google_cloud_aiplatform_v1_feature_monitoring_stats_proto_init() {
	if File_google_cloud_aiplatform_v1_feature_monitoring_stats_proto != nil {
	return
	}
	if !protoimpl.UnsafeEnabled {
	file_google_cloud_aiplatform_v1_feature_monitoring_stats_proto_msgTypes[0].Exporter = func(v interface{}, i int) interface{} {
	switch v := v.(*FeatureStatsAnomaly); i {
	case 0:
	return &v.state
	case 1:
	return &v.sizeCache
	case 2:
	return &v.unknownFields
	default:
	return nil
	}
	}
	}
	type x struct{}
	out := protoimpl.TypeBuilder{
	File: protoimpl.DescBuilder{
	GoPackagePath: reflect.TypeOf(x{}).PkgPath(),
	RawDescriptor: file_google_cloud_aiplatform_v1_feature_monitoring_stats_proto_rawDesc,
	NumEnums: 0,
	NumMessages: 1,
	NumExtensions: 0,
	NumServices: 0,
	},
	GoTypes: file_google_cloud_aiplatform_v1_feature_monitoring_stats_proto_goTypes,
	DependencyIndexes: file_google_cloud_aiplatform_v1_feature_monitoring_stats_proto_depIdxs,
	MessageInfos: file_google_cloud_aiplatform_v1_feature_monitoring_stats_proto_msgTypes,
	}.Build()
	File_google_cloud_aiplatform_v1_feature_monitoring_stats_proto = out.File
	file_google_cloud_aiplatform_v1_feature_monitoring_stats_proto_rawDesc = nil
	file_google_cloud_aiplatform_v1_feature_monitoring_stats_proto_goTypes = nil
	file_google_cloud_aiplatform_v1_feature_monitoring_stats_proto_depIdxs = nil
	}