package Paws::MachineLearning::GetMLModel; use Moose; has MLModelId => (is => 'ro', isa => 'Str', required => 1); has Verbose => (is => 'ro', isa => 'Bool'); use MooseX::ClassAttribute; class_has _api_call => (isa => 'Str', is => 'ro', default => 'GetMLModel'); class_has _returns => (isa => 'Str', is => 'ro', default => 'Paws::MachineLearning::GetMLModelOutput'); class_has _result_key => (isa => 'Str', is => 'ro'); 1; ### main pod documentation begin ### =head1 NAME Paws::MachineLearning::GetMLModel - Arguments for method GetMLModel on L =head1 DESCRIPTION This class represents the parameters used for calling the method GetMLModel on the L service. Use the attributes of this class as arguments to method GetMLModel. You shouldn't make instances of this class. Each attribute should be used as a named argument in the call to GetMLModel. =head1 SYNOPSIS my $machinelearning = Paws->service('MachineLearning'); my $GetMLModelOutput = $machinelearning->GetMLModel( MLModelId => 'MyEntityId', Verbose => 1, # OPTIONAL ); # Results: my $ComputeTime = $GetMLModelOutput->ComputeTime; my $CreatedAt = $GetMLModelOutput->CreatedAt; my $CreatedByIamUser = $GetMLModelOutput->CreatedByIamUser; my $EndpointInfo = $GetMLModelOutput->EndpointInfo; my $FinishedAt = $GetMLModelOutput->FinishedAt; my $InputDataLocationS3 = $GetMLModelOutput->InputDataLocationS3; my $LastUpdatedAt = $GetMLModelOutput->LastUpdatedAt; my $LogUri = $GetMLModelOutput->LogUri; my $MLModelId = $GetMLModelOutput->MLModelId; my $MLModelType = $GetMLModelOutput->MLModelType; my $Message = $GetMLModelOutput->Message; my $Name = $GetMLModelOutput->Name; my $Recipe = $GetMLModelOutput->Recipe; my $Schema = $GetMLModelOutput->Schema; my $ScoreThreshold = $GetMLModelOutput->ScoreThreshold; my $ScoreThresholdLastUpdatedAt = $GetMLModelOutput->ScoreThresholdLastUpdatedAt; my $SizeInBytes = $GetMLModelOutput->SizeInBytes; my $StartedAt = $GetMLModelOutput->StartedAt; my $Status = $GetMLModelOutput->Status; my $TrainingDataSourceId = $GetMLModelOutput->TrainingDataSourceId; my $TrainingParameters = $GetMLModelOutput->TrainingParameters; # 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 MLModelId => Str The ID assigned to the C at creation. =head2 Verbose => Bool Specifies whether the C operation should return C. If true, C is returned. If false, C is not returned. =head1 SEE ALSO This class forms part of L, documenting arguments for method GetMLModel in L =head1 BUGS and CONTRIBUTIONS The source code is located here: L Please report bugs to: L =cut