software.amazon.awssdk.services.sagemaker.model

Interface AutoMLJobChannel.Builder

All Superinterfaces:

Buildable, CopyableBuilder<AutoMLJobChannel.Builder,AutoMLJobChannel>, SdkBuilder<AutoMLJobChannel.Builder,AutoMLJobChannel>, SdkPojo

Enclosing class:

AutoMLJobChannel

public static interface AutoMLJobChannel.Builder
extends SdkPojo, CopyableBuilder<AutoMLJobChannel.Builder,AutoMLJobChannel>

Method Summary

Modifier and Type	Method and Description
AutoMLJobChannel.Builder	channelType(AutoMLChannelType channelType) The type of channel.
AutoMLJobChannel.Builder	channelType(String channelType) The type of channel.
AutoMLJobChannel.Builder	compressionType(CompressionType compressionType) The allowed compression types depend on the input format and problem type.
AutoMLJobChannel.Builder	compressionType(String compressionType) The allowed compression types depend on the input format and problem type.
AutoMLJobChannel.Builder	contentType(String contentType) The content type of the data from the input source.
AutoMLJobChannel.Builder	dataSource(AutoMLDataSource dataSource) The data source for an AutoML channel (Required).
default AutoMLJobChannel.Builder	dataSource(Consumer<AutoMLDataSource.Builder> dataSource) The data source for an AutoML channel (Required).

Methods inherited from interface software.amazon.awssdk.core.SdkPojo

equalsBySdkFields, sdkFields

Methods inherited from interface software.amazon.awssdk.utils.builder.CopyableBuilder

copy

Methods inherited from interface software.amazon.awssdk.utils.builder.SdkBuilder

applyMutation, build

Method Detail

channelType

AutoMLJobChannel.Builder channelType(String channelType)

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

Parameters:

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

Returns:

Returns a reference to this object so that method calls can be chained together.

See Also:

AutoMLChannelType, AutoMLChannelType

channelType

AutoMLJobChannel.Builder channelType(AutoMLChannelType channelType)

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

Parameters:

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

Returns:

Returns a reference to this object so that method calls can be chained together.

See Also:

AutoMLChannelType, AutoMLChannelType

contentType

AutoMLJobChannel.Builder contentType(String 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 or x-application/vnd.amazon+parquet. The default value is text/csv;header=present.

• For ImageClassification: image/png, image/jpeg, or image/*. The default value is image/*.

• For TextClassification: text/csv;header=present or x-application/vnd.amazon+parquet . The default value is text/csv;header=present.

Parameters:

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 or x-application/vnd.amazon+parquet. The default value is text/csv;header=present.

• For ImageClassification: image/png, image/jpeg, or image/*. The default value is image/*.

• For TextClassification: text/csv;header=present or x-application/vnd.amazon+parquet. The default value is text/csv;header=present.

Returns:

Returns a reference to this object so that method calls can be chained together.

compressionType

AutoMLJobChannel.Builder compressionType(String 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.

Parameters:

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.

Returns:

Returns a reference to this object so that method calls can be chained together.

See Also:

CompressionType, CompressionType

compressionType

AutoMLJobChannel.Builder compressionType(CompressionType 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.

Parameters:

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.

Returns:

Returns a reference to this object so that method calls can be chained together.

See Also:

CompressionType, CompressionType

dataSource

AutoMLJobChannel.Builder dataSource(AutoMLDataSource dataSource)

The data source for an AutoML channel (Required).

Parameters:

dataSource - The data source for an AutoML channel (Required).

Returns:

Returns a reference to this object so that method calls can be chained together.

dataSource

default AutoMLJobChannel.Builder dataSource(Consumer<AutoMLDataSource.Builder> dataSource)

The data source for an AutoML channel (Required).

This is a convenience method that creates an instance of the AutoMLDataSource.Builder avoiding the need to create one manually via AutoMLDataSource.builder().

When the Consumer completes, SdkBuilder.build() is called immediately and its result is passed to dataSource(AutoMLDataSource).

Parameters:

dataSource - a consumer that will call methods on AutoMLDataSource.Builder

Returns:

Returns a reference to this object so that method calls can be chained together.

See Also:

dataSource(AutoMLDataSource)