PNG  IHDR;IDATxܻn0K )(pA 7LeG{ §㻢|ذaÆ 6lذaÆ 6lذaÆ 6lom$^yذag5bÆ 6lذaÆ 6lذa{ 6lذaÆ `}HFkm,mӪôô! x|'ܢ˟;E:9&ᶒ}{v]n&6 h_tڠ͵-ҫZ;Z$.Pkž)!o>}leQfJTu іچ\X=8Rن4`Vwl>nG^is"ms$ui?wbs[m6K4O.4%/bC%t Mז -lG6mrz2s%9s@-k9=)kB5\+͂Zsٲ Rn~GRC wIcIn7jJhۛNCS|j08yiHKֶۛkɈ+;SzL/F*\Ԕ#"5m2[S=gnaPeғL lذaÆ 6l^ḵaÆ 6lذaÆ 6lذa; _ذaÆ 6lذaÆ 6lذaÆ RIENDB` package Paws::SageMaker::CreateModelQualityJobDefinition; use Moose; has JobDefinitionName => (is => 'ro', isa => 'Str', required => 1); has JobResources => (is => 'ro', isa => 'Paws::SageMaker::MonitoringResources', required => 1); has ModelQualityAppSpecification => (is => 'ro', isa => 'Paws::SageMaker::ModelQualityAppSpecification', required => 1); has ModelQualityBaselineConfig => (is => 'ro', isa => 'Paws::SageMaker::ModelQualityBaselineConfig'); has ModelQualityJobInput => (is => 'ro', isa => 'Paws::SageMaker::ModelQualityJobInput', required => 1); has ModelQualityJobOutputConfig => (is => 'ro', isa => 'Paws::SageMaker::MonitoringOutputConfig', required => 1); has NetworkConfig => (is => 'ro', isa => 'Paws::SageMaker::MonitoringNetworkConfig'); has RoleArn => (is => 'ro', isa => 'Str', required => 1); has StoppingCondition => (is => 'ro', isa => 'Paws::SageMaker::MonitoringStoppingCondition'); has Tags => (is => 'ro', isa => 'ArrayRef[Paws::SageMaker::Tag]'); use MooseX::ClassAttribute; class_has _api_call => (isa => 'Str', is => 'ro', default => 'CreateModelQualityJobDefinition'); class_has _returns => (isa => 'Str', is => 'ro', default => 'Paws::SageMaker::CreateModelQualityJobDefinitionResponse'); class_has _result_key => (isa => 'Str', is => 'ro'); 1; ### main pod documentation begin ### =head1 NAME Paws::SageMaker::CreateModelQualityJobDefinition - Arguments for method CreateModelQualityJobDefinition on L =head1 DESCRIPTION This class represents the parameters used for calling the method CreateModelQualityJobDefinition on the L service. Use the attributes of this class as arguments to method CreateModelQualityJobDefinition. You shouldn't make instances of this class. Each attribute should be used as a named argument in the call to CreateModelQualityJobDefinition. =head1 SYNOPSIS my $api.sagemaker = Paws->service('SageMaker'); my $CreateModelQualityJobDefinitionResponse = $api . sagemaker->CreateModelQualityJobDefinition( JobDefinitionName => 'MyMonitoringJobDefinitionName', JobResources => { ClusterConfig => { InstanceCount => 1, # min: 1, max: 100 InstanceType => 'ml.t3.medium' , # values: ml.t3.medium, ml.t3.large, ml.t3.xlarge, ml.t3.2xlarge, ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, ml.c4.xlarge, ml.c4.2xlarge, ml.c4.4xlarge, ml.c4.8xlarge, ml.p2.xlarge, ml.p2.8xlarge, ml.p2.16xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.12xlarge, ml.m5.24xlarge, ml.r5.large, ml.r5.xlarge, ml.r5.2xlarge, ml.r5.4xlarge, ml.r5.8xlarge, ml.r5.12xlarge, ml.r5.16xlarge, ml.r5.24xlarge, ml.g4dn.xlarge, ml.g4dn.2xlarge, ml.g4dn.4xlarge, ml.g4dn.8xlarge, ml.g4dn.12xlarge, ml.g4dn.16xlarge VolumeSizeInGB => 1, # min: 1, max: 16384 VolumeKmsKeyId => 'MyKmsKeyId', # max: 2048; OPTIONAL }, }, ModelQualityAppSpecification => { ImageUri => 'MyImageUri', # max: 255 ContainerArguments => [ 'MyContainerArgument', ... # max: 256 ], # min: 1, max: 50; OPTIONAL ContainerEntrypoint => [ 'MyContainerEntrypointString', ... # max: 256 ], # min: 1, max: 100; OPTIONAL Environment => { 'MyProcessingEnvironmentKey' => 'MyProcessingEnvironmentValue', # key: max: 256, value: max: 256 }, # max: 50; OPTIONAL PostAnalyticsProcessorSourceUri => 'MyS3Uri', # max: 1024; OPTIONAL ProblemType => 'BinaryClassification' , # values: BinaryClassification, MulticlassClassification, Regression; OPTIONAL RecordPreprocessorSourceUri => 'MyS3Uri', # max: 1024; OPTIONAL }, ModelQualityJobInput => { EndpointInput => { EndpointName => 'MyEndpointName', # max: 63 LocalPath => 'MyProcessingLocalPath', # max: 256 EndTimeOffset => 'MyMonitoringTimeOffsetString', # min: 1, max: 15; OPTIONAL FeaturesAttribute => 'MyString', # OPTIONAL InferenceAttribute => 'MyString', # OPTIONAL ProbabilityAttribute => 'MyString', # OPTIONAL ProbabilityThresholdAttribute => 1, # OPTIONAL S3DataDistributionType => 'FullyReplicated' , # values: FullyReplicated, ShardedByS3Key; OPTIONAL S3InputMode => 'Pipe', # values: Pipe, File; OPTIONAL StartTimeOffset => 'MyMonitoringTimeOffsetString', # min: 1, max: 15; OPTIONAL }, GroundTruthS3Input => { S3Uri => 'MyMonitoringS3Uri', # max: 512; OPTIONAL }, }, ModelQualityJobOutputConfig => { MonitoringOutputs => [ { S3Output => { LocalPath => 'MyProcessingLocalPath', # max: 256 S3Uri => 'MyMonitoringS3Uri', # max: 512; OPTIONAL S3UploadMode => 'Continuous', # values: Continuous, EndOfJob; OPTIONAL }, }, ... ], # min: 1, max: 1 KmsKeyId => 'MyKmsKeyId', # max: 2048; OPTIONAL }, RoleArn => 'MyRoleArn', ModelQualityBaselineConfig => { BaseliningJobName => 'MyProcessingJobName', # min: 1, max: 63; OPTIONAL ConstraintsResource => { S3Uri => 'MyS3Uri', # max: 1024; OPTIONAL }, # OPTIONAL }, # OPTIONAL NetworkConfig => { EnableInterContainerTrafficEncryption => 1, # OPTIONAL EnableNetworkIsolation => 1, # OPTIONAL VpcConfig => { SecurityGroupIds => [ 'MySecurityGroupId', ... # max: 32 ], # min: 1, max: 5 Subnets => [ 'MySubnetId', ... # max: 32 ], # min: 1, max: 16 }, # OPTIONAL }, # OPTIONAL StoppingCondition => { MaxRuntimeInSeconds => 1, # min: 1, max: 86400 }, # OPTIONAL Tags => [ { Key => 'MyTagKey', # min: 1, max: 128 Value => 'MyTagValue', # max: 256 }, ... ], # OPTIONAL ); # Results: my $JobDefinitionArn = $CreateModelQualityJobDefinitionResponse->JobDefinitionArn; # Returns a L object. Values for attributes that are native types (Int, String, Float, etc) can passed as-is (scalar values). Values for complex Types (objects) can be passed as a HashRef. The keys and values of the hashref will be used to instance the underlying object. For the AWS API documentation, see L =head1 ATTRIBUTES =head2 B JobDefinitionName => Str The name of the monitoring job definition. =head2 B JobResources => L =head2 B ModelQualityAppSpecification => L The container that runs the monitoring job. =head2 ModelQualityBaselineConfig => L Specifies the constraints and baselines for the monitoring job. =head2 B ModelQualityJobInput => L A list of the inputs that are monitored. Currently endpoints are supported. =head2 B ModelQualityJobOutputConfig => L =head2 NetworkConfig => L Specifies the network configuration for the monitoring job. =head2 B RoleArn => Str The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf. =head2 StoppingCondition => L =head2 Tags => ArrayRef[L] (Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags (https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-whatURL) in the I. =head1 SEE ALSO This class forms part of L, documenting arguments for method CreateModelQualityJobDefinition in L =head1 BUGS and CONTRIBUTIONS The source code is located here: L Please report bugs to: L =cut