Channel

class aws_cdk.aws_stepfunctions_tasks.Channel(*, channel_name, data_source, compression_type=None, content_type=None, input_mode=None, record_wrapper_type=None, shuffle_config=None)

Bases: object

(experimental) Describes the training, validation or test dataset and the Amazon S3 location where it is stored.

Parameters

• channel_name (str) – (experimental) Name of the channel.

• data_source (DataSource) – (experimental) Location of the channel data.

• compression_type (Optional[CompressionType]) – (experimental) Compression type if training data is compressed. Default: - None

• content_type (Optional[str]) – (experimental) The MIME type of the data. Default: - None

• input_mode (Optional[InputMode]) – (experimental) Input mode to use for the data channel in a training job. Default: - None

• record_wrapper_type (Optional[RecordWrapperType]) – (experimental) 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. Default: - None

• shuffle_config (Optional[ShuffleConfig]) – (experimental) Shuffle config option for input data in a channel. Default: - None

Stability

experimental

Attributes

channel_name

(experimental) Name of the channel.

Stability

experimental

Return type

str

compression_type

(experimental) Compression type if training data is compressed.

Default

• None

Stability

experimental

Return type

Optional[CompressionType]

content_type

(experimental) The MIME type of the data.

Default

• None

Stability

experimental

Return type

Optional[str]

data_source

(experimental) Location of the channel data.

Stability

experimental

Return type

DataSource

input_mode

(experimental) Input mode to use for the data channel in a training job.

Default

• None

Stability

experimental

Return type

Optional[InputMode]

record_wrapper_type

(experimental) 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.

Default

• None

Stability

experimental

Return type

Optional[RecordWrapperType]

shuffle_config

(experimental) Shuffle config option for input data in a channel.

Default

• None

Stability

experimental

Return type

Optional[ShuffleConfig]