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::LookoutEquipment::CreateInferenceScheduler; use Moose; has ClientToken => (is => 'ro', isa => 'Str', required => 1); has DataDelayOffsetInMinutes => (is => 'ro', isa => 'Int'); has DataInputConfiguration => (is => 'ro', isa => 'Paws::LookoutEquipment::InferenceInputConfiguration', required => 1); has DataOutputConfiguration => (is => 'ro', isa => 'Paws::LookoutEquipment::InferenceOutputConfiguration', required => 1); has DataUploadFrequency => (is => 'ro', isa => 'Str', required => 1); has InferenceSchedulerName => (is => 'ro', isa => 'Str', required => 1); has ModelName => (is => 'ro', isa => 'Str', required => 1); has RoleArn => (is => 'ro', isa => 'Str', required => 1); has ServerSideKmsKeyId => (is => 'ro', isa => 'Str'); has Tags => (is => 'ro', isa => 'ArrayRef[Paws::LookoutEquipment::Tag]'); use MooseX::ClassAttribute; class_has _api_call => (isa => 'Str', is => 'ro', default => 'CreateInferenceScheduler'); class_has _returns => (isa => 'Str', is => 'ro', default => 'Paws::LookoutEquipment::CreateInferenceSchedulerResponse'); class_has _result_key => (isa => 'Str', is => 'ro'); 1; ### main pod documentation begin ### =head1 NAME Paws::LookoutEquipment::CreateInferenceScheduler - Arguments for method CreateInferenceScheduler on L =head1 DESCRIPTION This class represents the parameters used for calling the method CreateInferenceScheduler on the L service. Use the attributes of this class as arguments to method CreateInferenceScheduler. You shouldn't make instances of this class. Each attribute should be used as a named argument in the call to CreateInferenceScheduler. =head1 SYNOPSIS my $lookoutequipment = Paws->service('LookoutEquipment'); my $CreateInferenceSchedulerResponse = $lookoutequipment->CreateInferenceScheduler( ClientToken => 'MyIdempotenceToken', DataInputConfiguration => { InferenceInputNameConfiguration => { ComponentTimestampDelimiter => 'MyComponentTimestampDelimiter', # max: 1; OPTIONAL TimestampFormat => 'MyFileNameTimestampFormat', # OPTIONAL }, # OPTIONAL InputTimeZoneOffset => 'MyTimeZoneOffset', # OPTIONAL S3InputConfiguration => { Bucket => 'MyS3Bucket', # min: 3, max: 63 Prefix => 'MyS3Prefix', # max: 1024; OPTIONAL }, # OPTIONAL }, DataOutputConfiguration => { S3OutputConfiguration => { Bucket => 'MyS3Bucket', # min: 3, max: 63 Prefix => 'MyS3Prefix', # max: 1024; OPTIONAL }, KmsKeyId => 'MyNameOrArn', # min: 1, max: 2048; OPTIONAL }, DataUploadFrequency => 'PT5M', InferenceSchedulerName => 'MyInferenceSchedulerName', ModelName => 'MyModelName', RoleArn => 'MyIamRoleArn', DataDelayOffsetInMinutes => 1, # OPTIONAL ServerSideKmsKeyId => 'MyNameOrArn', # OPTIONAL Tags => [ { Key => 'MyTagKey', # min: 1, max: 128 Value => 'MyTagValue', # max: 256 }, ... ], # OPTIONAL ); # Results: my $InferenceSchedulerArn = $CreateInferenceSchedulerResponse->InferenceSchedulerArn; my $InferenceSchedulerName = $CreateInferenceSchedulerResponse->InferenceSchedulerName; my $Status = $CreateInferenceSchedulerResponse->Status; # 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 ClientToken => Str A unique identifier for the request. If you do not set the client request token, Amazon Lookout for Equipment generates one. =head2 DataDelayOffsetInMinutes => Int A period of time (in minutes) by which inference on the data is delayed after the data starts. For instance, if you select an offset delay time of five minutes, inference will not begin on the data until the first data measurement after the five minute mark. For example, if five minutes is selected, the inference scheduler will wake up at the configured frequency with the additional five minute delay time to check the customer S3 bucket. The customer can upload data at the same frequency and they don't need to stop and restart the scheduler when uploading new data. =head2 B DataInputConfiguration => L Specifies configuration information for the input data for the inference scheduler, including delimiter, format, and dataset location. =head2 B DataOutputConfiguration => L Specifies configuration information for the output results for the inference scheduler, including the S3 location for the output. =head2 B DataUploadFrequency => Str How often data is uploaded to the source S3 bucket for the input data. The value chosen is the length of time between data uploads. For instance, if you select 5 minutes, Amazon Lookout for Equipment will upload the real-time data to the source bucket once every 5 minutes. This frequency also determines how often Amazon Lookout for Equipment starts a scheduled inference on your data. In this example, it starts once every 5 minutes. Valid values are: C<"PT5M">, C<"PT10M">, C<"PT15M">, C<"PT30M">, C<"PT1H"> =head2 B InferenceSchedulerName => Str The name of the inference scheduler being created. =head2 B ModelName => Str The name of the previously trained ML model being used to create the inference scheduler. =head2 B RoleArn => Str The Amazon Resource Name (ARN) of a role with permission to access the data source being used for the inference. =head2 ServerSideKmsKeyId => Str Provides the identifier of the AWS KMS customer master key (CMK) used to encrypt inference scheduler data by Amazon Lookout for Equipment. =head2 Tags => ArrayRef[L] Any tags associated with the inference scheduler. =head1 SEE ALSO This class forms part of L, documenting arguments for method CreateInferenceScheduler in L =head1 BUGS and CONTRIBUTIONS The source code is located here: L Please report bugs to: L =cut