AutoMLJobChannel - Amazon SageMaker (original) (raw)

A channel is a named input source that training algorithms can consume. This channel is used for AutoML jobs V2 (jobs created by calling CreateAutoMLJobV2).

ChannelType

The type of channel. Defines whether the data are used for training or validation. The default value is training. Channels for training andvalidation must share the same ContentType

Note

The type of channel defaults to training for the time-series forecasting problem type.

Type: String

Valid Values: training | validation

Required: No

CompressionType

The allowed compression types depend on the input format and problem type. We allow the compression type Gzip for S3Prefix inputs on tabular data only. For all other inputs, the compression type should be None. If no compression type is provided, we default to None.

Type: String

Valid Values: None | Gzip

Required: No

ContentType

The content type of the data from the input source. The following are the allowed content types for different problems:

For tabular problem types: text/csv;header=present orx-application/vnd.amazon+parquet. The default value istext/csv;header=present.
For image classification: image/png, image/jpeg, orimage/*. The default value is image/*.
For text classification: text/csv;header=present orx-application/vnd.amazon+parquet. The default value istext/csv;header=present.
For time-series forecasting: text/csv;header=present orx-application/vnd.amazon+parquet. The default value istext/csv;header=present.
For text generation (LLMs fine-tuning): text/csv;header=present orx-application/vnd.amazon+parquet. The default value istext/csv;header=present.

Type: String

Length Constraints: Minimum length of 0. Maximum length of 256.

Pattern: .*

Required: No

DataSource

The data source for an AutoML channel (Required).

Type: AutoMLDataSource object

Required: No

AutoMLJobChannel - Amazon SageMaker (original) (raw)

Contents

Note

See Also