NAME

Paws::SageMaker::Channel

USAGE

This class represents one of two things:

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::Channel object:

  $service_obj->Method(Att1 => { ChannelName => $value, ..., ShuffleConfig => $value  });

Results returned from an API call

Use accessors for each attribute. If Att1 is expected to be an Paws::SageMaker::Channel object:

  $result = $service_obj->Method(...);
  $result->Att1->ChannelName

DESCRIPTION

A channel is a named input source that training algorithms can consume.

ATTRIBUTES

REQUIRED ChannelName => Str

  The name of the channel.

CompressionType => Str

  If training data is compressed, the compression type. The default value
is C<None>. C<CompressionType> is used only in Pipe input mode. In File
mode, leave this field unset or set it to None.

ContentType => Str

  The MIME type of the data.

REQUIRED DataSource => Paws::SageMaker::DataSource

  The location of the channel data.

InputMode => Str

  (Optional) The input mode to use for the data channel in a training
job. If you don't set a value for C<InputMode>, Amazon SageMaker uses
the value set for C<TrainingInputMode>. Use this parameter to override
the C<TrainingInputMode> setting in a AlgorithmSpecification request
when you have a channel that needs a different input mode from the
training job's general setting. To download the data from Amazon Simple
Storage Service (Amazon S3) to the provisioned ML storage volume, and
mount the directory to a Docker volume, use C<File> input mode. To
stream data directly from Amazon S3 to the container, choose C<Pipe>
input mode.

To use a model for incremental training, choose File input model.

RecordWrapperType => Str

  Specify RecordIO as the value when input data is in raw format but the
training algorithm requires the RecordIO format. In this case, Amazon
SageMaker wraps each individual S3 object in a RecordIO record. If the
input data is already in RecordIO format, you don't need to set this
attribute. For more information, see Create a Dataset Using RecordIO
(https://mxnet.incubator.apache.org/architecture/note_data_loading.html#data-format).

In File mode, leave this field unset or set it to None.

ShuffleConfig => Paws::SageMaker::ShuffleConfig

  A configuration for a shuffle option for input data in a channel. If
you use C<S3Prefix> for C<S3DataType>, this shuffles the results of the
S3 key prefix matches. If you use C<ManifestFile>, the order of the S3
object references in the C<ManifestFile> is shuffled. If you use
C<AugmentedManifestFile>, the order of the JSON lines in the
C<AugmentedManifestFile> is shuffled. The shuffling order is determined
using the C<Seed> value.

For Pipe input mode, shuffling is done at the start of every epoch. With large datasets this ensures that the order of the training data is different for each epoch, it helps reduce bias and possible overfitting. In a multi-node training job when ShuffleConfig is combined with S3DataDistributionType of ShardedByS3Key, the data is shuffled across nodes so that the content sent to a particular node on the first epoch might be sent to a different node on the second epoch.

SEE ALSO

This class forms part of Paws, describing an object used in Paws::SageMaker

BUGS and CONTRIBUTIONS

The source code is located here: https://github.com/pplu/aws-sdk-perl

Please report bugs to: https://github.com/pplu/aws-sdk-perl/issues