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` # Generated by default/object.tt package Paws::SageMaker::S3DataSource; use Moose; has AttributeNames => (is => 'ro', isa => 'ArrayRef[Str|Undef]'); has S3DataDistributionType => (is => 'ro', isa => 'Str'); has S3DataType => (is => 'ro', isa => 'Str', required => 1); has S3Uri => (is => 'ro', isa => 'Str', required => 1); 1; ### main pod documentation begin ### =head1 NAME Paws::SageMaker::S3DataSource =head1 USAGE This class represents one of two things: =head3 Arguments in a call to a service Use the attributes of this class as arguments to methods. You shouldn't make instances of this class. Each attribute should be used as a named argument in the calls that expect this type of object. As an example, if Att1 is expected to be a Paws::SageMaker::S3DataSource object: $service_obj->Method(Att1 => { AttributeNames => $value, ..., S3Uri => $value }); =head3 Results returned from an API call Use accessors for each attribute. If Att1 is expected to be an Paws::SageMaker::S3DataSource object: $result = $service_obj->Method(...); $result->Att1->AttributeNames =head1 DESCRIPTION Describes the S3 data source. =head1 ATTRIBUTES =head2 AttributeNames => ArrayRef[Str|Undef] A list of one or more attribute names to use that are found in a specified augmented manifest file. =head2 S3DataDistributionType => Str If you want Amazon SageMaker to replicate the entire dataset on each ML compute instance that is launched for model training, specify C. If you want Amazon SageMaker to replicate a subset of data on each ML compute instance that is launched for model training, specify C. If there are I ML compute instances launched for a training job, each instance gets approximately 1/I of the number of S3 objects. In this case, model training on each machine uses only the subset of training data. Don't choose more ML compute instances for training than available S3 objects. If you do, some nodes won't get any data and you will pay for nodes that aren't getting any training data. This applies in both File and Pipe modes. Keep this in mind when developing algorithms. In distributed training, where you use multiple ML compute EC2 instances, you might choose C. If the algorithm requires copying training data to the ML storage volume (when C is set to C), this copies 1/I of the number of objects. =head2 B S3DataType => Str If you choose C, C identifies a key name prefix. Amazon SageMaker uses all objects that match the specified key name prefix for model training. If you choose C, C identifies an object that is a manifest file containing a list of object keys that you want Amazon SageMaker to use for model training. If you choose C, S3Uri identifies an object that is an augmented manifest file in JSON lines format. This file contains the data you want to use for model training. C can only be used if the Channel's input mode is C. =head2 B S3Uri => Str Depending on the value specified for the C, identifies either a key name prefix or a manifest. For example: =over =item * A key name prefix might look like this: C =item * A manifest might look like this: C A manifest is an S3 object which is a JSON file consisting of an array of elements. The first element is a prefix which is followed by one or more suffixes. SageMaker appends the suffix elements to the prefix to get a full set of C. Note that the prefix must be a valid non-empty C that precludes users from specifying a manifest whose individual C is sourced from different S3 buckets. The following code example shows a valid manifest format: C<[ {"prefix": "s3://customer_bucket/some/prefix/"},> C<"relative/path/to/custdata-1",> C<"relative/path/custdata-2",> C<...> C<"relative/path/custdata-N"> C<]> This JSON is equivalent to the following C list: C C C<...> C The complete set of C in this manifest is the input data for the channel for this data source. The object that each C points to must be readable by the IAM role that Amazon SageMaker uses to perform tasks on your behalf. =back =head1 SEE ALSO This class forms part of L, describing an object used in L =head1 BUGS and CONTRIBUTIONS The source code is located here: L Please report bugs to: L =cut