// Copyright 2025 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 v1.36.11
// 	protoc        v6.33.2
// source: google/cloud/aiplatform/v1beta1/model_monitoring_job.proto

package aiplatformpb

import (
	reflect "reflect"
	sync "sync"
	unsafe "unsafe"

	_ "google.golang.org/genproto/googleapis/api/annotations"
	status "google.golang.org/genproto/googleapis/rpc/status"
	interval "google.golang.org/genproto/googleapis/type/interval"
	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)
)

// Represents a model monitoring job that analyze dataset using different
// monitoring algorithm.
type ModelMonitoringJob struct {
	state protoimpl.MessageState `protogen:"open.v1"`
	// Output only. Resource name of a ModelMonitoringJob. Format:
	// `projects/{project_id}/locations/{location_id}/modelMonitors/{model_monitor_id}/modelMonitoringJobs/{model_monitoring_job_id}`
	Name string `protobuf:"bytes,1,opt,name=name,proto3" json:"name,omitempty"`
	// The display name of the ModelMonitoringJob.
	// The name can be up to 128 characters long and can consist of any UTF-8.
	DisplayName string `protobuf:"bytes,2,opt,name=display_name,json=displayName,proto3" json:"display_name,omitempty"`
	// Monitoring monitoring job spec. It outlines the specifications for
	// monitoring objectives, notifications, and result exports. If left blank,
	// the default monitoring specifications from the top-level resource
	// 'ModelMonitor' will be applied. If provided, we will use the specification
	// defined here rather than the default one.
	ModelMonitoringSpec *ModelMonitoringSpec `protobuf:"bytes,3,opt,name=model_monitoring_spec,json=modelMonitoringSpec,proto3" json:"model_monitoring_spec,omitempty"`
	// Output only. Timestamp when this ModelMonitoringJob was created.
	CreateTime *timestamppb.Timestamp `protobuf:"bytes,4,opt,name=create_time,json=createTime,proto3" json:"create_time,omitempty"`
	// Output only. Timestamp when this ModelMonitoringJob was updated most
	// recently.
	UpdateTime *timestamppb.Timestamp `protobuf:"bytes,5,opt,name=update_time,json=updateTime,proto3" json:"update_time,omitempty"`
	// Output only. The state of the monitoring job.
	//   - When the job is still creating, the state will be 'JOB_STATE_PENDING'.
	//   - Once the job is successfully created, the state will be
	//     'JOB_STATE_RUNNING'.
	//   - Once the job is finished, the state will be one of
	//     'JOB_STATE_FAILED', 'JOB_STATE_SUCCEEDED',
	//     'JOB_STATE_PARTIALLY_SUCCEEDED'.
	State JobState `protobuf:"varint,6,opt,name=state,proto3,enum=google.cloud.aiplatform.v1beta1.JobState" json:"state,omitempty"`
	// Output only. Schedule resource name. It will only appear when this job is
	// triggered by a schedule.
	Schedule string `protobuf:"bytes,7,opt,name=schedule,proto3" json:"schedule,omitempty"`
	// Output only. Execution results for all the monitoring objectives.
	JobExecutionDetail *ModelMonitoringJobExecutionDetail `protobuf:"bytes,8,opt,name=job_execution_detail,json=jobExecutionDetail,proto3" json:"job_execution_detail,omitempty"`
	// Output only. Timestamp when this ModelMonitoringJob was scheduled. It will
	// only appear when this job is triggered by a schedule.
	ScheduleTime  *timestamppb.Timestamp `protobuf:"bytes,9,opt,name=schedule_time,json=scheduleTime,proto3" json:"schedule_time,omitempty"`
	unknownFields protoimpl.UnknownFields
	sizeCache     protoimpl.SizeCache
}

func (x *ModelMonitoringJob) Reset() {
	*x = ModelMonitoringJob{}
	mi := &file_google_cloud_aiplatform_v1beta1_model_monitoring_job_proto_msgTypes[0]
	ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
	ms.StoreMessageInfo(mi)
}

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

func (*ModelMonitoringJob) ProtoMessage() {}

func (x *ModelMonitoringJob) ProtoReflect() protoreflect.Message {
	mi := &file_google_cloud_aiplatform_v1beta1_model_monitoring_job_proto_msgTypes[0]
	if x != nil {
		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
		if ms.LoadMessageInfo() == nil {
			ms.StoreMessageInfo(mi)
		}
		return ms
	}
	return mi.MessageOf(x)
}

// Deprecated: Use ModelMonitoringJob.ProtoReflect.Descriptor instead.
func (*ModelMonitoringJob) Descriptor() ([]byte, []int) {
	return file_google_cloud_aiplatform_v1beta1_model_monitoring_job_proto_rawDescGZIP(), []int{0}
}

func (x *ModelMonitoringJob) GetName() string {
	if x != nil {
		return x.Name
	}
	return ""
}

func (x *ModelMonitoringJob) GetDisplayName() string {
	if x != nil {
		return x.DisplayName
	}
	return ""
}

func (x *ModelMonitoringJob) GetModelMonitoringSpec() *ModelMonitoringSpec {
	if x != nil {
		return x.ModelMonitoringSpec
	}
	return nil
}

func (x *ModelMonitoringJob) GetCreateTime() *timestamppb.Timestamp {
	if x != nil {
		return x.CreateTime
	}
	return nil
}

func (x *ModelMonitoringJob) GetUpdateTime() *timestamppb.Timestamp {
	if x != nil {
		return x.UpdateTime
	}
	return nil
}

func (x *ModelMonitoringJob) GetState() JobState {
	if x != nil {
		return x.State
	}
	return JobState_JOB_STATE_UNSPECIFIED
}

func (x *ModelMonitoringJob) GetSchedule() string {
	if x != nil {
		return x.Schedule
	}
	return ""
}

func (x *ModelMonitoringJob) GetJobExecutionDetail() *ModelMonitoringJobExecutionDetail {
	if x != nil {
		return x.JobExecutionDetail
	}
	return nil
}

func (x *ModelMonitoringJob) GetScheduleTime() *timestamppb.Timestamp {
	if x != nil {
		return x.ScheduleTime
	}
	return nil
}

// Represent the execution details of the job.
type ModelMonitoringJobExecutionDetail struct {
	state protoimpl.MessageState `protogen:"open.v1"`
	// Processed baseline datasets.
	BaselineDatasets []*ModelMonitoringJobExecutionDetail_ProcessedDataset `protobuf:"bytes,1,rep,name=baseline_datasets,json=baselineDatasets,proto3" json:"baseline_datasets,omitempty"`
	// Processed target datasets.
	TargetDatasets []*ModelMonitoringJobExecutionDetail_ProcessedDataset `protobuf:"bytes,2,rep,name=target_datasets,json=targetDatasets,proto3" json:"target_datasets,omitempty"`
	// Status of data processing for each monitoring objective.
	// Key is the objective.
	ObjectiveStatus map[string]*status.Status `protobuf:"bytes,3,rep,name=objective_status,json=objectiveStatus,proto3" json:"objective_status,omitempty" protobuf_key:"bytes,1,opt,name=key" protobuf_val:"bytes,2,opt,name=value"`
	// Additional job error status.
	Error         *status.Status `protobuf:"bytes,4,opt,name=error,proto3" json:"error,omitempty"`
	unknownFields protoimpl.UnknownFields
	sizeCache     protoimpl.SizeCache
}

func (x *ModelMonitoringJobExecutionDetail) Reset() {
	*x = ModelMonitoringJobExecutionDetail{}
	mi := &file_google_cloud_aiplatform_v1beta1_model_monitoring_job_proto_msgTypes[1]
	ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
	ms.StoreMessageInfo(mi)
}

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

func (*ModelMonitoringJobExecutionDetail) ProtoMessage() {}

func (x *ModelMonitoringJobExecutionDetail) ProtoReflect() protoreflect.Message {
	mi := &file_google_cloud_aiplatform_v1beta1_model_monitoring_job_proto_msgTypes[1]
	if x != nil {
		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
		if ms.LoadMessageInfo() == nil {
			ms.StoreMessageInfo(mi)
		}
		return ms
	}
	return mi.MessageOf(x)
}

// Deprecated: Use ModelMonitoringJobExecutionDetail.ProtoReflect.Descriptor instead.
func (*ModelMonitoringJobExecutionDetail) Descriptor() ([]byte, []int) {
	return file_google_cloud_aiplatform_v1beta1_model_monitoring_job_proto_rawDescGZIP(), []int{1}
}

func (x *ModelMonitoringJobExecutionDetail) GetBaselineDatasets() []*ModelMonitoringJobExecutionDetail_ProcessedDataset {
	if x != nil {
		return x.BaselineDatasets
	}
	return nil
}

func (x *ModelMonitoringJobExecutionDetail) GetTargetDatasets() []*ModelMonitoringJobExecutionDetail_ProcessedDataset {
	if x != nil {
		return x.TargetDatasets
	}
	return nil
}

func (x *ModelMonitoringJobExecutionDetail) GetObjectiveStatus() map[string]*status.Status {
	if x != nil {
		return x.ObjectiveStatus
	}
	return nil
}

func (x *ModelMonitoringJobExecutionDetail) GetError() *status.Status {
	if x != nil {
		return x.Error
	}
	return nil
}

// Processed dataset information.
type ModelMonitoringJobExecutionDetail_ProcessedDataset struct {
	state protoimpl.MessageState `protogen:"open.v1"`
	// Actual data location of the processed dataset.
	Location string `protobuf:"bytes,1,opt,name=location,proto3" json:"location,omitempty"`
	// Dataset time range information if any.
	TimeRange     *interval.Interval `protobuf:"bytes,2,opt,name=time_range,json=timeRange,proto3" json:"time_range,omitempty"`
	unknownFields protoimpl.UnknownFields
	sizeCache     protoimpl.SizeCache
}

func (x *ModelMonitoringJobExecutionDetail_ProcessedDataset) Reset() {
	*x = ModelMonitoringJobExecutionDetail_ProcessedDataset{}
	mi := &file_google_cloud_aiplatform_v1beta1_model_monitoring_job_proto_msgTypes[2]
	ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
	ms.StoreMessageInfo(mi)
}

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

func (*ModelMonitoringJobExecutionDetail_ProcessedDataset) ProtoMessage() {}

func (x *ModelMonitoringJobExecutionDetail_ProcessedDataset) ProtoReflect() protoreflect.Message {
	mi := &file_google_cloud_aiplatform_v1beta1_model_monitoring_job_proto_msgTypes[2]
	if x != nil {
		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
		if ms.LoadMessageInfo() == nil {
			ms.StoreMessageInfo(mi)
		}
		return ms
	}
	return mi.MessageOf(x)
}

// Deprecated: Use ModelMonitoringJobExecutionDetail_ProcessedDataset.ProtoReflect.Descriptor instead.
func (*ModelMonitoringJobExecutionDetail_ProcessedDataset) Descriptor() ([]byte, []int) {
	return file_google_cloud_aiplatform_v1beta1_model_monitoring_job_proto_rawDescGZIP(), []int{1, 0}
}

func (x *ModelMonitoringJobExecutionDetail_ProcessedDataset) GetLocation() string {
	if x != nil {
		return x.Location
	}
	return ""
}

func (x *ModelMonitoringJobExecutionDetail_ProcessedDataset) GetTimeRange() *interval.Interval {
	if x != nil {
		return x.TimeRange
	}
	return nil
}

var File_google_cloud_aiplatform_v1beta1_model_monitoring_job_proto protoreflect.FileDescriptor

const file_google_cloud_aiplatform_v1beta1_model_monitoring_job_proto_rawDesc = "" +
	"\n" +
	":google/cloud/aiplatform/v1beta1/model_monitoring_job.proto\x12\x1fgoogle.cloud.aiplatform.v1beta1\x1a\x1fgoogle/api/field_behavior.proto\x1a\x19google/api/resource.proto\x1a/google/cloud/aiplatform/v1beta1/job_state.proto\x1a;google/cloud/aiplatform/v1beta1/model_monitoring_spec.proto\x1a\x1fgoogle/protobuf/timestamp.proto\x1a\x17google/rpc/status.proto\x1a\x1agoogle/type/interval.proto\"\xb4\x06\n" +
	"\x12ModelMonitoringJob\x12\x17\n" +
	"\x04name\x18\x01 \x01(\tB\x03\xe0A\x03R\x04name\x12!\n" +
	"\fdisplay_name\x18\x02 \x01(\tR\vdisplayName\x12h\n" +
	"\x15model_monitoring_spec\x18\x03 \x01(\v24.google.cloud.aiplatform.v1beta1.ModelMonitoringSpecR\x13modelMonitoringSpec\x12@\n" +
	"\vcreate_time\x18\x04 \x01(\v2\x1a.google.protobuf.TimestampB\x03\xe0A\x03R\n" +
	"createTime\x12@\n" +
	"\vupdate_time\x18\x05 \x01(\v2\x1a.google.protobuf.TimestampB\x03\xe0A\x03R\n" +
	"updateTime\x12D\n" +
	"\x05state\x18\x06 \x01(\x0e2).google.cloud.aiplatform.v1beta1.JobStateB\x03\xe0A\x03R\x05state\x12F\n" +
	"\bschedule\x18\a \x01(\tB*\xe0A\x03\xfaA$\n" +
	"\"aiplatform.googleapis.com/ScheduleR\bschedule\x12y\n" +
	"\x14job_execution_detail\x18\b \x01(\v2B.google.cloud.aiplatform.v1beta1.ModelMonitoringJobExecutionDetailB\x03\xe0A\x03R\x12jobExecutionDetail\x12D\n" +
	"\rschedule_time\x18\t \x01(\v2\x1a.google.protobuf.TimestampB\x03\xe0A\x03R\fscheduleTime:\xa4\x01\xeaA\xa0\x01\n" +
	",aiplatform.googleapis.com/ModelMonitoringJob\x12pprojects/{project}/locations/{location}/modelMonitors/{model_monitor}/modelMonitoringJobs/{model_monitoring_job}\"\x91\x05\n" +
	"!ModelMonitoringJobExecutionDetail\x12\x80\x01\n" +
	"\x11baseline_datasets\x18\x01 \x03(\v2S.google.cloud.aiplatform.v1beta1.ModelMonitoringJobExecutionDetail.ProcessedDatasetR\x10baselineDatasets\x12|\n" +
	"\x0ftarget_datasets\x18\x02 \x03(\v2S.google.cloud.aiplatform.v1beta1.ModelMonitoringJobExecutionDetail.ProcessedDatasetR\x0etargetDatasets\x12\x82\x01\n" +
	"\x10objective_status\x18\x03 \x03(\v2W.google.cloud.aiplatform.v1beta1.ModelMonitoringJobExecutionDetail.ObjectiveStatusEntryR\x0fobjectiveStatus\x12(\n" +
	"\x05error\x18\x04 \x01(\v2\x12.google.rpc.StatusR\x05error\x1ad\n" +
	"\x10ProcessedDataset\x12\x1a\n" +
	"\blocation\x18\x01 \x01(\tR\blocation\x124\n" +
	"\n" +
	"time_range\x18\x02 \x01(\v2\x15.google.type.IntervalR\ttimeRange\x1aV\n" +
	"\x14ObjectiveStatusEntry\x12\x10\n" +
	"\x03key\x18\x01 \x01(\tR\x03key\x12(\n" +
	"\x05value\x18\x02 \x01(\v2\x12.google.rpc.StatusR\x05value:\x028\x01B\xee\x01\n" +
	"#com.google.cloud.aiplatform.v1beta1B\x17ModelMonitoringJobProtoP\x01ZCcloud.google.com/go/aiplatform/apiv1beta1/aiplatformpb;aiplatformpb\xaa\x02\x1fGoogle.Cloud.AIPlatform.V1Beta1\xca\x02\x1fGoogle\\Cloud\\AIPlatform\\V1beta1\xea\x02\"Google::Cloud::AIPlatform::V1beta1b\x06proto3"

var (
	file_google_cloud_aiplatform_v1beta1_model_monitoring_job_proto_rawDescOnce sync.Once
	file_google_cloud_aiplatform_v1beta1_model_monitoring_job_proto_rawDescData []byte
)

func file_google_cloud_aiplatform_v1beta1_model_monitoring_job_proto_rawDescGZIP() []byte {
	file_google_cloud_aiplatform_v1beta1_model_monitoring_job_proto_rawDescOnce.Do(func() {
		file_google_cloud_aiplatform_v1beta1_model_monitoring_job_proto_rawDescData = protoimpl.X.CompressGZIP(unsafe.Slice(unsafe.StringData(file_google_cloud_aiplatform_v1beta1_model_monitoring_job_proto_rawDesc), len(file_google_cloud_aiplatform_v1beta1_model_monitoring_job_proto_rawDesc)))
	})
	return file_google_cloud_aiplatform_v1beta1_model_monitoring_job_proto_rawDescData
}

var file_google_cloud_aiplatform_v1beta1_model_monitoring_job_proto_msgTypes = make([]protoimpl.MessageInfo, 4)
var file_google_cloud_aiplatform_v1beta1_model_monitoring_job_proto_goTypes = []any{
	(*ModelMonitoringJob)(nil),                                 // 0: google.cloud.aiplatform.v1beta1.ModelMonitoringJob
	(*ModelMonitoringJobExecutionDetail)(nil),                  // 1: google.cloud.aiplatform.v1beta1.ModelMonitoringJobExecutionDetail
	(*ModelMonitoringJobExecutionDetail_ProcessedDataset)(nil), // 2: google.cloud.aiplatform.v1beta1.ModelMonitoringJobExecutionDetail.ProcessedDataset
	nil,                           // 3: google.cloud.aiplatform.v1beta1.ModelMonitoringJobExecutionDetail.ObjectiveStatusEntry
	(*ModelMonitoringSpec)(nil),   // 4: google.cloud.aiplatform.v1beta1.ModelMonitoringSpec
	(*timestamppb.Timestamp)(nil), // 5: google.protobuf.Timestamp
	(JobState)(0),                 // 6: google.cloud.aiplatform.v1beta1.JobState
	(*status.Status)(nil),         // 7: google.rpc.Status
	(*interval.Interval)(nil),     // 8: google.type.Interval
}
var file_google_cloud_aiplatform_v1beta1_model_monitoring_job_proto_depIdxs = []int32{
	4,  // 0: google.cloud.aiplatform.v1beta1.ModelMonitoringJob.model_monitoring_spec:type_name -> google.cloud.aiplatform.v1beta1.ModelMonitoringSpec
	5,  // 1: google.cloud.aiplatform.v1beta1.ModelMonitoringJob.create_time:type_name -> google.protobuf.Timestamp
	5,  // 2: google.cloud.aiplatform.v1beta1.ModelMonitoringJob.update_time:type_name -> google.protobuf.Timestamp
	6,  // 3: google.cloud.aiplatform.v1beta1.ModelMonitoringJob.state:type_name -> google.cloud.aiplatform.v1beta1.JobState
	1,  // 4: google.cloud.aiplatform.v1beta1.ModelMonitoringJob.job_execution_detail:type_name -> google.cloud.aiplatform.v1beta1.ModelMonitoringJobExecutionDetail
	5,  // 5: google.cloud.aiplatform.v1beta1.ModelMonitoringJob.schedule_time:type_name -> google.protobuf.Timestamp
	2,  // 6: google.cloud.aiplatform.v1beta1.ModelMonitoringJobExecutionDetail.baseline_datasets:type_name -> google.cloud.aiplatform.v1beta1.ModelMonitoringJobExecutionDetail.ProcessedDataset
	2,  // 7: google.cloud.aiplatform.v1beta1.ModelMonitoringJobExecutionDetail.target_datasets:type_name -> google.cloud.aiplatform.v1beta1.ModelMonitoringJobExecutionDetail.ProcessedDataset
	3,  // 8: google.cloud.aiplatform.v1beta1.ModelMonitoringJobExecutionDetail.objective_status:type_name -> google.cloud.aiplatform.v1beta1.ModelMonitoringJobExecutionDetail.ObjectiveStatusEntry
	7,  // 9: google.cloud.aiplatform.v1beta1.ModelMonitoringJobExecutionDetail.error:type_name -> google.rpc.Status
	8,  // 10: google.cloud.aiplatform.v1beta1.ModelMonitoringJobExecutionDetail.ProcessedDataset.time_range:type_name -> google.type.Interval
	7,  // 11: google.cloud.aiplatform.v1beta1.ModelMonitoringJobExecutionDetail.ObjectiveStatusEntry.value:type_name -> google.rpc.Status
	12, // [12:12] is the sub-list for method output_type
	12, // [12:12] is the sub-list for method input_type
	12, // [12:12] is the sub-list for extension type_name
	12, // [12:12] is the sub-list for extension extendee
	0,  // [0:12] is the sub-list for field type_name
}

func init() { file_google_cloud_aiplatform_v1beta1_model_monitoring_job_proto_init() }
func file_google_cloud_aiplatform_v1beta1_model_monitoring_job_proto_init() {
	if File_google_cloud_aiplatform_v1beta1_model_monitoring_job_proto != nil {
		return
	}
	file_google_cloud_aiplatform_v1beta1_job_state_proto_init()
	file_google_cloud_aiplatform_v1beta1_model_monitoring_spec_proto_init()
	type x struct{}
	out := protoimpl.TypeBuilder{
		File: protoimpl.DescBuilder{
			GoPackagePath: reflect.TypeOf(x{}).PkgPath(),
			RawDescriptor: unsafe.Slice(unsafe.StringData(file_google_cloud_aiplatform_v1beta1_model_monitoring_job_proto_rawDesc), len(file_google_cloud_aiplatform_v1beta1_model_monitoring_job_proto_rawDesc)),
			NumEnums:      0,
			NumMessages:   4,
			NumExtensions: 0,
			NumServices:   0,
		},
		GoTypes:           file_google_cloud_aiplatform_v1beta1_model_monitoring_job_proto_goTypes,
		DependencyIndexes: file_google_cloud_aiplatform_v1beta1_model_monitoring_job_proto_depIdxs,
		MessageInfos:      file_google_cloud_aiplatform_v1beta1_model_monitoring_job_proto_msgTypes,
	}.Build()
	File_google_cloud_aiplatform_v1beta1_model_monitoring_job_proto = out.File
	file_google_cloud_aiplatform_v1beta1_model_monitoring_job_proto_goTypes = nil
	file_google_cloud_aiplatform_v1beta1_model_monitoring_job_proto_depIdxs = nil
}
