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::TransformInput; use Moose; has CompressionType => (is => 'ro', isa => 'Str'); has ContentType => (is => 'ro', isa => 'Str'); has DataSource => (is => 'ro', isa => 'Paws::SageMaker::TransformDataSource', required => 1); has SplitType => (is => 'ro', isa => 'Str'); 1; ### main pod documentation begin ### =head1 NAME Paws::SageMaker::TransformInput =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::TransformInput object: $service_obj->Method(Att1 => { CompressionType => $value, ..., SplitType => $value }); =head3 Results returned from an API call Use accessors for each attribute. If Att1 is expected to be an Paws::SageMaker::TransformInput object: $result = $service_obj->Method(...); $result->Att1->CompressionType =head1 DESCRIPTION Describes the input source of a transform job and the way the transform job consumes it. =head1 ATTRIBUTES =head2 CompressionType => Str If your transform data is compressed, specify the compression type. Amazon SageMaker automatically decompresses the data for the transform job accordingly. The default value is C. =head2 ContentType => Str The multipurpose internet mail extension (MIME) type of the data. Amazon SageMaker uses the MIME type with each http call to transfer data to the transform job. =head2 B DataSource => L Describes the location of the channel data, which is, the S3 location of the input data that the model can consume. =head2 SplitType => Str The method to use to split the transform job's data files into smaller batches. Splitting is necessary when the total size of each object is too large to fit in a single request. You can also use data splitting to improve performance by processing multiple concurrent mini-batches. The default value for C is C, which indicates that input data files are not split, and request payloads contain the entire contents of an input object. Set the value of this parameter to C to split records on a newline character boundary. C also supports a number of record-oriented binary data formats. Currently, the supported record formats are: =over =item * RecordIO =item * TFRecord =back When splitting is enabled, the size of a mini-batch depends on the values of the C and C parameters. When the value of C is C, Amazon SageMaker sends the maximum number of records in each request, up to the C limit. If the value of C is C, Amazon SageMaker sends individual records in each request. Some data formats represent a record as a binary payload wrapped with extra padding bytes. When splitting is applied to a binary data format, padding is removed if the value of C is set to C. Padding is not removed if the value of C is set to C. For more information about C, see Create a Dataset Using RecordIO (https://mxnet.apache.org/api/faq/recordio) in the MXNet documentation. For more information about C, see Consuming TFRecord data (https://www.tensorflow.org/guide/data#consuming_tfrecord_data) in the TensorFlow documentation. =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