# frozen_string_literal: true
# Generated by the protocol buffer compiler.  DO NOT EDIT!
# source: google/cloud/aiplatform/v1/model_deployment_monitoring_job.proto

require 'google/protobuf'

require 'google/api/field_behavior_pb'
require 'google/api/resource_pb'
require 'google/cloud/aiplatform/v1/encryption_spec_pb'
require 'google/cloud/aiplatform/v1/feature_monitoring_stats_pb'
require 'google/cloud/aiplatform/v1/io_pb'
require 'google/cloud/aiplatform/v1/job_state_pb'
require 'google/cloud/aiplatform/v1/model_monitoring_pb'
require 'google/protobuf/duration_pb'
require 'google/protobuf/struct_pb'
require 'google/protobuf/timestamp_pb'
require 'google/rpc/status_pb'


descriptor_data = "\n@google/cloud/aiplatform/v1/model_deployment_monitoring_job.proto\x12\x1agoogle.cloud.aiplatform.v1\x1a\x1fgoogle/api/field_behavior.proto\x1a\x19google/api/resource.proto\x1a\x30google/cloud/aiplatform/v1/encryption_spec.proto\x1a\x39google/cloud/aiplatform/v1/feature_monitoring_stats.proto\x1a#google/cloud/aiplatform/v1/io.proto\x1a*google/cloud/aiplatform/v1/job_state.proto\x1a\x31google/cloud/aiplatform/v1/model_monitoring.proto\x1a\x1egoogle/protobuf/duration.proto\x1a\x1cgoogle/protobuf/struct.proto\x1a\x1fgoogle/protobuf/timestamp.proto\x1a\x17google/rpc/status.proto\"\xad\x10\n\x1cModelDeploymentMonitoringJob\x12\x11\n\x04name\x18\x01 \x01(\tB\x03\xe0\x41\x03\x12\x19\n\x0c\x64isplay_name\x18\x02 \x01(\tB\x03\xe0\x41\x02\x12<\n\x08\x65ndpoint\x18\x03 \x01(\tB*\xe0\x41\x02\xfa\x41$\n\"aiplatform.googleapis.com/Endpoint\x12\x38\n\x05state\x18\x04 \x01(\x0e\x32$.google.cloud.aiplatform.v1.JobStateB\x03\xe0\x41\x03\x12m\n\x0eschedule_state\x18\x05 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\x01(\x0e\x32J.google.cloud.aiplatform.v1.ModelDeploymentMonitoringBigQueryTable.LogType\x12\x1b\n\x13\x62igquery_table_path\x18\x03 \x01(\t\x12\x34\n\'request_response_logging_schema_version\x18\x04 \x01(\tB\x03\xe0\x41\x03\"B\n\tLogSource\x12\x1a\n\x16LOG_SOURCE_UNSPECIFIED\x10\x00\x12\x0c\n\x08TRAINING\x10\x01\x12\x0b\n\x07SERVING\x10\x02\"=\n\x07LogType\x12\x18\n\x14LOG_TYPE_UNSPECIFIED\x10\x00\x12\x0b\n\x07PREDICT\x10\x01\x12\x0b\n\x07\x45XPLAIN\x10\x02\"\x9b\x01\n(ModelDeploymentMonitoringObjectiveConfig\x12\x19\n\x11\x64\x65ployed_model_id\x18\x01 \x01(\t\x12T\n\x10objective_config\x18\x02 \x01(\x0b\x32:.google.cloud.aiplatform.v1.ModelMonitoringObjectiveConfig\"\x96\x01\n\'ModelDeploymentMonitoringScheduleConfig\x12\x38\n\x10monitor_interval\x18\x01 \x01(\x0b\x32\x19.google.protobuf.DurationB\x03\xe0\x41\x02\x12\x31\n\x0emonitor_window\x18\x02 \x01(\x0b\x32\x19.google.protobuf.Duration\"\xac\x04\n\x1dModelMonitoringStatsAnomalies\x12U\n\tobjective\x18\x01 \x01(\x0e\x32\x42.google.cloud.aiplatform.v1.ModelDeploymentMonitoringObjectiveType\x12\x19\n\x11\x64\x65ployed_model_id\x18\x02 \x01(\t\x12\x15\n\ranomaly_count\x18\x03 \x01(\x05\x12n\n\rfeature_stats\x18\x04 \x03(\x0b\x32W.google.cloud.aiplatform.v1.ModelMonitoringStatsAnomalies.FeatureHistoricStatsAnomalies\x1a\x91\x02\n\x1d\x46\x65\x61tureHistoricStatsAnomalies\x12\x1c\n\x14\x66\x65\x61ture_display_name\x18\x01 \x01(\t\x12>\n\tthreshold\x18\x03 \x01(\x0b\x32+.google.cloud.aiplatform.v1.ThresholdConfig\x12G\n\x0etraining_stats\x18\x04 \x01(\x0b\x32/.google.cloud.aiplatform.v1.FeatureStatsAnomaly\x12I\n\x10prediction_stats\x18\x05 \x03(\x0b\x32/.google.cloud.aiplatform.v1.FeatureStatsAnomaly*\xce\x01\n&ModelDeploymentMonitoringObjectiveType\x12:\n6MODEL_DEPLOYMENT_MONITORING_OBJECTIVE_TYPE_UNSPECIFIED\x10\x00\x12\x14\n\x10RAW_FEATURE_SKEW\x10\x01\x12\x15\n\x11RAW_FEATURE_DRIFT\x10\x02\x12\x1c\n\x18\x46\x45\x41TURE_ATTRIBUTION_SKEW\x10\x03\x12\x1d\n\x19\x46\x45\x41TURE_ATTRIBUTION_DRIFT\x10\x04\x42\xdf\x01\n\x1e\x63om.google.cloud.aiplatform.v1B!ModelDeploymentMonitoringJobProtoP\x01Z>cloud.google.com/go/aiplatform/apiv1/aiplatformpb;aiplatformpb\xaa\x02\x1aGoogle.Cloud.AIPlatform.V1\xca\x02\x1aGoogle\\Cloud\\AIPlatform\\V1\xea\x02\x1dGoogle::Cloud::AIPlatform::V1b\x06proto3"

pool = Google::Protobuf::DescriptorPool.generated_pool

begin
  pool.add_serialized_file(descriptor_data)
rescue TypeError
  # Compatibility code: will be removed in the next major version.
  require 'google/protobuf/descriptor_pb'
  parsed = Google::Protobuf::FileDescriptorProto.decode(descriptor_data)
  parsed.clear_dependency
  serialized = parsed.class.encode(parsed)
  file = pool.add_serialized_file(serialized)
  warn "Warning: Protobuf detected an import path issue while loading generated file #{__FILE__}"
  imports = [
    ["google.cloud.aiplatform.v1.SamplingStrategy", "google/cloud/aiplatform/v1/model_monitoring.proto"],
    ["google.protobuf.Value", "google/protobuf/struct.proto"],
    ["google.protobuf.Duration", "google/protobuf/duration.proto"],
    ["google.protobuf.Timestamp", "google/protobuf/timestamp.proto"],
    ["google.cloud.aiplatform.v1.GcsDestination", "google/cloud/aiplatform/v1/io.proto"],
    ["google.cloud.aiplatform.v1.EncryptionSpec", "google/cloud/aiplatform/v1/encryption_spec.proto"],
    ["google.rpc.Status", "google/rpc/status.proto"],
    ["google.cloud.aiplatform.v1.FeatureStatsAnomaly", "google/cloud/aiplatform/v1/feature_monitoring_stats.proto"],
  ]
  imports.each do |type_name, expected_filename|
    import_file = pool.lookup(type_name).file_descriptor
    if import_file.name != expected_filename
      warn "- #{file.name} imports #{expected_filename}, but that import was loaded as #{import_file.name}"
    end
  end
  warn "Each proto file must use a consistent fully-qualified name."
  warn "This will become an error in the next major version."
end

module Google
  module Cloud
    module AIPlatform
      module V1
        ModelDeploymentMonitoringJob = ::Google::Protobuf::DescriptorPool.generated_pool.lookup("google.cloud.aiplatform.v1.ModelDeploymentMonitoringJob").msgclass
        ModelDeploymentMonitoringJob::LatestMonitoringPipelineMetadata = ::Google::Protobuf::DescriptorPool.generated_pool.lookup("google.cloud.aiplatform.v1.ModelDeploymentMonitoringJob.LatestMonitoringPipelineMetadata").msgclass
        ModelDeploymentMonitoringJob::MonitoringScheduleState = ::Google::Protobuf::DescriptorPool.generated_pool.lookup("google.cloud.aiplatform.v1.ModelDeploymentMonitoringJob.MonitoringScheduleState").enummodule
        ModelDeploymentMonitoringBigQueryTable = ::Google::Protobuf::DescriptorPool.generated_pool.lookup("google.cloud.aiplatform.v1.ModelDeploymentMonitoringBigQueryTable").msgclass
        ModelDeploymentMonitoringBigQueryTable::LogSource = ::Google::Protobuf::DescriptorPool.generated_pool.lookup("google.cloud.aiplatform.v1.ModelDeploymentMonitoringBigQueryTable.LogSource").enummodule
        ModelDeploymentMonitoringBigQueryTable::LogType = ::Google::Protobuf::DescriptorPool.generated_pool.lookup("google.cloud.aiplatform.v1.ModelDeploymentMonitoringBigQueryTable.LogType").enummodule
        ModelDeploymentMonitoringObjectiveConfig = ::Google::Protobuf::DescriptorPool.generated_pool.lookup("google.cloud.aiplatform.v1.ModelDeploymentMonitoringObjectiveConfig").msgclass
        ModelDeploymentMonitoringScheduleConfig = ::Google::Protobuf::DescriptorPool.generated_pool.lookup("google.cloud.aiplatform.v1.ModelDeploymentMonitoringScheduleConfig").msgclass
        ModelMonitoringStatsAnomalies = ::Google::Protobuf::DescriptorPool.generated_pool.lookup("google.cloud.aiplatform.v1.ModelMonitoringStatsAnomalies").msgclass
        ModelMonitoringStatsAnomalies::FeatureHistoricStatsAnomalies = ::Google::Protobuf::DescriptorPool.generated_pool.lookup("google.cloud.aiplatform.v1.ModelMonitoringStatsAnomalies.FeatureHistoricStatsAnomalies").msgclass
        ModelDeploymentMonitoringObjectiveType = ::Google::Protobuf::DescriptorPool.generated_pool.lookup("google.cloud.aiplatform.v1.ModelDeploymentMonitoringObjectiveType").enummodule
      end
    end
  end
end