Amazon SageMaker
Developer Guide

Channel

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

Contents

ChannelName

The name of the channel.

Type: String

Length Constraints: Minimum length of 1. Maximum length of 64.

Pattern: [A-Za-z0-9\.\-_]+

Required: Yes

CompressionType

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

Type: String

Valid Values: None | Gzip

Required: No

ContentType

The MIME type of the data.

Type: String

Length Constraints: Maximum length of 256.

Required: No

DataSource

The location of the channel data.

Type: DataSource object

Required: Yes

InputMode

(Optional) The input mode to use for the data channel in a training job. If you don't set a value for InputMode, Amazon SageMaker uses the value set for TrainingInputMode. Use this parameter to override the 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 File input mode. To stream data directly from Amazon S3 to the container, choose Pipe input mode.

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

Type: String

Valid Values: Pipe | File

Required: No

RecordWrapperType

Specify RecordIO as the value when input data is in raw format but the training algorithm requires the RecordIO format, in which 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.

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

Type: String

Valid Values: None | RecordIO

Required: No

See Also

For more information about using this API in one of the language-specific AWS SDKs, see the following:

On this page: