AutoMLJobChannel (AWS SDK for Java

java.lang.Object
- com.amazonaws.services.sagemaker.model.AutoMLJobChannel

All Implemented Interfaces:

StructuredPojo, Serializable, Cloneable
```
@Generated(value="com.amazonaws:aws-java-sdk-code-generator")
public class AutoMLJobChannel
extends Object
implements Serializable, Cloneable, StructuredPojo
```
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).

See Also:

AWS API Documentation, Serialized Form

Constructor Summary

Constructors
Constructor and Description

AutoMLJobChannel()

Constructors
Constructor and Description
`AutoMLJobChannel()`

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`AutoMLJobChannel`	`clone()`
`boolean`	`equals(Object obj)`
`String`	`getChannelType()` The type of channel.
`String`	`getCompressionType()` The allowed compression types depend on the input format and problem type.
`String`	`getContentType()` The content type of the data from the input source.
`AutoMLDataSource`	`getDataSource()` The data source for an AutoML channel (Required).
`int`	`hashCode()`
`void`	`marshall(ProtocolMarshaller protocolMarshaller)` Marshalls this structured data using the given `ProtocolMarshaller`.
`void`	`setChannelType(String channelType)` The type of channel.
`void`	`setCompressionType(String compressionType)` The allowed compression types depend on the input format and problem type.
`void`	`setContentType(String contentType)` The content type of the data from the input source.
`void`	`setDataSource(AutoMLDataSource dataSource)` The data source for an AutoML channel (Required).
`String`	`toString()` Returns a string representation of this object.
`AutoMLJobChannel`	`withChannelType(AutoMLChannelType channelType)` The type of channel.
`AutoMLJobChannel`	`withChannelType(String channelType)` The type of channel.
`AutoMLJobChannel`	`withCompressionType(CompressionType compressionType)` The allowed compression types depend on the input format and problem type.
`AutoMLJobChannel`	`withCompressionType(String compressionType)` The allowed compression types depend on the input format and problem type.
`AutoMLJobChannel`	`withContentType(String contentType)` The content type of the data from the input source.
`AutoMLJobChannel`	`withDataSource(AutoMLDataSource dataSource)` The data source for an AutoML channel (Required).

Methods inherited from class java.lang.Object
getClass, notify, notifyAll, wait, wait, wait

- Constructor Detail
  - AutoMLJobChannel
```
public AutoMLJobChannel()
```
- Method Detail
  - setChannelType
```
public void setChannelType(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
    
    The type of channel defaults to training for the time-series forecasting problem type.
    
    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
    
    The type of channel defaults to training for the time-series forecasting problem type.
    
    See Also:
    
    AutoMLChannelType
  - getChannelType
```
public String getChannelType()
```
    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
    
    The type of channel defaults to training for the time-series forecasting problem type.
    
    Returns:
    
    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
    
    The type of channel defaults to training for the time-series forecasting problem type.
    
    See Also:
    
    AutoMLChannelType
  - withChannelType
```
public AutoMLJobChannel withChannelType(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
    
    The type of channel defaults to training for the time-series forecasting problem type.
    
    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
    
    The type of channel defaults to training for the time-series forecasting problem type.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
    
    See Also:
    
    AutoMLChannelType
  - withChannelType
```
public AutoMLJobChannel withChannelType(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
    
    The type of channel defaults to training for the time-series forecasting problem type.
    
    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
    
    The type of channel defaults to training for the time-series forecasting problem type.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
    
    See Also:
    
    AutoMLChannelType
  - setContentType
```
public void setContentType(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 image classification: image/png, image/jpeg, or image/*. The default value is image/*.
    - For text classification: text/csv;header=present or x-application/vnd.amazon+parquet. The default value is text/csv;header=present.
    - For time-series forecasting: text/csv;header=present or x-application/vnd.amazon+parquet. The default value is text/csv;header=present.
    - For text generation (LLMs fine-tuning): 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 image classification: image/png, image/jpeg, or image/*. The default value is image/*.
    
    For text classification: text/csv;header=present or x-application/vnd.amazon+parquet. The default value is text/csv;header=present.
    
    For time-series forecasting: text/csv;header=present or x-application/vnd.amazon+parquet. The default value is text/csv;header=present.
    
    For text generation (LLMs fine-tuning): text/csv;header=present or x-application/vnd.amazon+parquet. The default value is text/csv;header=present.
  - getContentType
```
public String getContentType()
```
    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 image classification: image/png, image/jpeg, or image/*. The default value is image/*.
    - For text classification: text/csv;header=present or x-application/vnd.amazon+parquet. The default value is text/csv;header=present.
    - For time-series forecasting: text/csv;header=present or x-application/vnd.amazon+parquet. The default value is text/csv;header=present.
    - For text generation (LLMs fine-tuning): text/csv;header=present or x-application/vnd.amazon+parquet. The default value is text/csv;header=present.
    Returns:
    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 image classification: image/png, image/jpeg, or image/*. The default value is image/*.
    
    For text classification: text/csv;header=present or x-application/vnd.amazon+parquet. The default value is text/csv;header=present.
    
    For time-series forecasting: text/csv;header=present or x-application/vnd.amazon+parquet. The default value is text/csv;header=present.
    
    For text generation (LLMs fine-tuning): text/csv;header=present or x-application/vnd.amazon+parquet. The default value is text/csv;header=present.
  - withContentType
```
public AutoMLJobChannel withContentType(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 image classification: image/png, image/jpeg, or image/*. The default value is image/*.
    - For text classification: text/csv;header=present or x-application/vnd.amazon+parquet. The default value is text/csv;header=present.
    - For time-series forecasting: text/csv;header=present or x-application/vnd.amazon+parquet. The default value is text/csv;header=present.
    - For text generation (LLMs fine-tuning): 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 image classification: image/png, image/jpeg, or image/*. The default value is image/*.
    
    For text classification: text/csv;header=present or x-application/vnd.amazon+parquet. The default value is text/csv;header=present.
    
    For time-series forecasting: text/csv;header=present or x-application/vnd.amazon+parquet. The default value is text/csv;header=present.
    
    For text generation (LLMs fine-tuning): 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.
  - setCompressionType
```
public void setCompressionType(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.
    
    See Also:
    
    CompressionType
  - getCompressionType
```
public String getCompressionType()
```
    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:
    
    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.
    
    See Also:
    
    CompressionType
  - withCompressionType
```
public AutoMLJobChannel withCompressionType(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
  - withCompressionType
```
public AutoMLJobChannel withCompressionType(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
  - setDataSource
```
public void setDataSource(AutoMLDataSource dataSource)
```
    The data source for an AutoML channel (Required).
    
    Parameters:
    
    dataSource - The data source for an AutoML channel (Required).
  - getDataSource
```
public AutoMLDataSource getDataSource()
```
    The data source for an AutoML channel (Required).
    
    Returns:
    
    The data source for an AutoML channel (Required).
  - withDataSource
```
public AutoMLJobChannel withDataSource(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.
  - toString
```
public String toString()
```
    Returns a string representation of this object. This is useful for testing and debugging. Sensitive data will be redacted from this string using a placeholder value.
    
    Overrides:
    
    toString in class Object
    
    Returns:
    
    A string representation of this object.
    
    See Also:
    
    Object.toString()
  - equals
```
public boolean equals(Object obj)
```
    Overrides:
    
    equals in class Object
  - hashCode
```
public int hashCode()
```
    Overrides:
    
    hashCode in class Object
  - clone
```
public AutoMLJobChannel clone()
```
    Overrides:
    
    clone in class Object
  - marshall
```
public void marshall(ProtocolMarshaller protocolMarshaller)
```
    Description copied from interface: StructuredPojo
    
    Marshalls this structured data using the given ProtocolMarshaller.
    
    Specified by:
    
    marshall in interface StructuredPojo
    
    Parameters:
    
    protocolMarshaller - Implementation of ProtocolMarshaller used to marshall this object's data.

AWS SDK for Java 1.x API Reference - 1.12.793

Class AutoMLJobChannel

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Constructor Detail

AutoMLJobChannel

Method Detail

setChannelType

getChannelType

withChannelType

withChannelType

setContentType

getContentType

withContentType

setCompressionType

getCompressionType

withCompressionType

withCompressionType

setDataSource

getDataSource

withDataSource

toString

equals

hashCode

clone

marshall