TrainingSpecification (AWS SDK for Java

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

All Implemented Interfaces:: StructuredPojo, Serializable, Cloneable

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

Defines how the algorithm is used for a training job.

See Also:: AWS API Documentation, Serialized Form

Constructor Summary

Constructors
Constructor and Description

TrainingSpecification()

Constructors
Constructor and Description
`TrainingSpecification()`

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`TrainingSpecification`	`clone()`
`boolean`	`equals(Object obj)`
`List<MetricDefinition>`	`getMetricDefinitions()` A list of `MetricDefinition` objects, which are used for parsing metrics generated by the algorithm.
`List<HyperParameterSpecification>`	`getSupportedHyperParameters()` A list of the `HyperParameterSpecification` objects, that define the supported hyperparameters.
`List<String>`	`getSupportedTrainingInstanceTypes()` A list of the instance types that this algorithm can use for training.
`List<HyperParameterTuningJobObjective>`	`getSupportedTuningJobObjectiveMetrics()` A list of the metrics that the algorithm emits that can be used as the objective metric in a hyperparameter tuning job.
`Boolean`	`getSupportsDistributedTraining()` Indicates whether the algorithm supports distributed training.
`List<ChannelSpecification>`	`getTrainingChannels()` A list of `ChannelSpecification` objects, which specify the input sources to be used by the algorithm.
`String`	`getTrainingImage()` The Amazon ECR registry path of the Docker image that contains the training algorithm.
`String`	`getTrainingImageDigest()` An MD5 hash of the training algorithm that identifies the Docker image used for training.
`int`	`hashCode()`
`Boolean`	`isSupportsDistributedTraining()` Indicates whether the algorithm supports distributed training.
`void`	`marshall(ProtocolMarshaller protocolMarshaller)` Marshalls this structured data using the given `ProtocolMarshaller`.
`void`	`setMetricDefinitions(Collection<MetricDefinition> metricDefinitions)` A list of `MetricDefinition` objects, which are used for parsing metrics generated by the algorithm.
`void`	`setSupportedHyperParameters(Collection<HyperParameterSpecification> supportedHyperParameters)` A list of the `HyperParameterSpecification` objects, that define the supported hyperparameters.
`void`	`setSupportedTrainingInstanceTypes(Collection<String> supportedTrainingInstanceTypes)` A list of the instance types that this algorithm can use for training.
`void`	`setSupportedTuningJobObjectiveMetrics(Collection<HyperParameterTuningJobObjective> supportedTuningJobObjectiveMetrics)` A list of the metrics that the algorithm emits that can be used as the objective metric in a hyperparameter tuning job.
`void`	`setSupportsDistributedTraining(Boolean supportsDistributedTraining)` Indicates whether the algorithm supports distributed training.
`void`	`setTrainingChannels(Collection<ChannelSpecification> trainingChannels)` A list of `ChannelSpecification` objects, which specify the input sources to be used by the algorithm.
`void`	`setTrainingImage(String trainingImage)` The Amazon ECR registry path of the Docker image that contains the training algorithm.
`void`	`setTrainingImageDigest(String trainingImageDigest)` An MD5 hash of the training algorithm that identifies the Docker image used for training.
`String`	`toString()` Returns a string representation of this object.
`TrainingSpecification`	`withMetricDefinitions(Collection<MetricDefinition> metricDefinitions)` A list of `MetricDefinition` objects, which are used for parsing metrics generated by the algorithm.
`TrainingSpecification`	`withMetricDefinitions(MetricDefinition... metricDefinitions)` A list of `MetricDefinition` objects, which are used for parsing metrics generated by the algorithm.
`TrainingSpecification`	`withSupportedHyperParameters(Collection<HyperParameterSpecification> supportedHyperParameters)` A list of the `HyperParameterSpecification` objects, that define the supported hyperparameters.
`TrainingSpecification`	`withSupportedHyperParameters(HyperParameterSpecification... supportedHyperParameters)` A list of the `HyperParameterSpecification` objects, that define the supported hyperparameters.
`TrainingSpecification`	`withSupportedTrainingInstanceTypes(Collection<String> supportedTrainingInstanceTypes)` A list of the instance types that this algorithm can use for training.
`TrainingSpecification`	`withSupportedTrainingInstanceTypes(String... supportedTrainingInstanceTypes)` A list of the instance types that this algorithm can use for training.
`TrainingSpecification`	`withSupportedTrainingInstanceTypes(TrainingInstanceType... supportedTrainingInstanceTypes)` A list of the instance types that this algorithm can use for training.
`TrainingSpecification`	`withSupportedTuningJobObjectiveMetrics(Collection<HyperParameterTuningJobObjective> supportedTuningJobObjectiveMetrics)` A list of the metrics that the algorithm emits that can be used as the objective metric in a hyperparameter tuning job.
`TrainingSpecification`	`withSupportedTuningJobObjectiveMetrics(HyperParameterTuningJobObjective... supportedTuningJobObjectiveMetrics)` A list of the metrics that the algorithm emits that can be used as the objective metric in a hyperparameter tuning job.
`TrainingSpecification`	`withSupportsDistributedTraining(Boolean supportsDistributedTraining)` Indicates whether the algorithm supports distributed training.
`TrainingSpecification`	`withTrainingChannels(ChannelSpecification... trainingChannels)` A list of `ChannelSpecification` objects, which specify the input sources to be used by the algorithm.
`TrainingSpecification`	`withTrainingChannels(Collection<ChannelSpecification> trainingChannels)` A list of `ChannelSpecification` objects, which specify the input sources to be used by the algorithm.
`TrainingSpecification`	`withTrainingImage(String trainingImage)` The Amazon ECR registry path of the Docker image that contains the training algorithm.
`TrainingSpecification`	`withTrainingImageDigest(String trainingImageDigest)` An MD5 hash of the training algorithm that identifies the Docker image used for training.

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

- Constructor Detail
  - TrainingSpecification
```
public TrainingSpecification()
```
- Method Detail
  - setTrainingImage
```
public void setTrainingImage(String trainingImage)
```
    The Amazon ECR registry path of the Docker image that contains the training algorithm.
    
    Parameters:
    
    trainingImage - The Amazon ECR registry path of the Docker image that contains the training algorithm.
  - getTrainingImage
```
public String getTrainingImage()
```
    The Amazon ECR registry path of the Docker image that contains the training algorithm.
    
    Returns:
    
    The Amazon ECR registry path of the Docker image that contains the training algorithm.
  - withTrainingImage
```
public TrainingSpecification withTrainingImage(String trainingImage)
```
    The Amazon ECR registry path of the Docker image that contains the training algorithm.
    
    Parameters:
    
    trainingImage - The Amazon ECR registry path of the Docker image that contains the training algorithm.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setTrainingImageDigest
```
public void setTrainingImageDigest(String trainingImageDigest)
```
    An MD5 hash of the training algorithm that identifies the Docker image used for training.
    
    Parameters:
    
    trainingImageDigest - An MD5 hash of the training algorithm that identifies the Docker image used for training.
  - getTrainingImageDigest
```
public String getTrainingImageDigest()
```
    An MD5 hash of the training algorithm that identifies the Docker image used for training.
    
    Returns:
    
    An MD5 hash of the training algorithm that identifies the Docker image used for training.
  - withTrainingImageDigest
```
public TrainingSpecification withTrainingImageDigest(String trainingImageDigest)
```
    An MD5 hash of the training algorithm that identifies the Docker image used for training.
    
    Parameters:
    
    trainingImageDigest - An MD5 hash of the training algorithm that identifies the Docker image used for training.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - getSupportedHyperParameters
```
public List<HyperParameterSpecification> getSupportedHyperParameters()
```
    A list of the HyperParameterSpecification objects, that define the supported hyperparameters. This is required if the algorithm supports automatic model tuning.>
    
    Returns:
    
    A list of the HyperParameterSpecification objects, that define the supported hyperparameters. This is required if the algorithm supports automatic model tuning.>
  - setSupportedHyperParameters
```
public void setSupportedHyperParameters(Collection<HyperParameterSpecification> supportedHyperParameters)
```
    A list of the HyperParameterSpecification objects, that define the supported hyperparameters. This is required if the algorithm supports automatic model tuning.>
    
    Parameters:
    
    supportedHyperParameters - A list of the HyperParameterSpecification objects, that define the supported hyperparameters. This is required if the algorithm supports automatic model tuning.>
  - withSupportedHyperParameters
```
public TrainingSpecification withSupportedHyperParameters(HyperParameterSpecification... supportedHyperParameters)
```
    A list of the HyperParameterSpecification objects, that define the supported hyperparameters. This is required if the algorithm supports automatic model tuning.>
    
    NOTE: This method appends the values to the existing list (if any). Use setSupportedHyperParameters(java.util.Collection) or withSupportedHyperParameters(java.util.Collection) if you want to override the existing values.
    
    Parameters:
    
    supportedHyperParameters - A list of the HyperParameterSpecification objects, that define the supported hyperparameters. This is required if the algorithm supports automatic model tuning.>
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - withSupportedHyperParameters
```
public TrainingSpecification withSupportedHyperParameters(Collection<HyperParameterSpecification> supportedHyperParameters)
```
    A list of the HyperParameterSpecification objects, that define the supported hyperparameters. This is required if the algorithm supports automatic model tuning.>
    
    Parameters:
    
    supportedHyperParameters - A list of the HyperParameterSpecification objects, that define the supported hyperparameters. This is required if the algorithm supports automatic model tuning.>
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - getSupportedTrainingInstanceTypes
```
public List<String> getSupportedTrainingInstanceTypes()
```
    A list of the instance types that this algorithm can use for training.
    
    Returns:
    
    A list of the instance types that this algorithm can use for training.
    
    See Also:
    
    TrainingInstanceType
  - setSupportedTrainingInstanceTypes
```
public void setSupportedTrainingInstanceTypes(Collection<String> supportedTrainingInstanceTypes)
```
    A list of the instance types that this algorithm can use for training.
    
    Parameters:
    
    supportedTrainingInstanceTypes - A list of the instance types that this algorithm can use for training.
    
    See Also:
    
    TrainingInstanceType
  - withSupportedTrainingInstanceTypes
```
public TrainingSpecification withSupportedTrainingInstanceTypes(String... supportedTrainingInstanceTypes)
```
    A list of the instance types that this algorithm can use for training.
    
    NOTE: This method appends the values to the existing list (if any). Use setSupportedTrainingInstanceTypes(java.util.Collection) or withSupportedTrainingInstanceTypes(java.util.Collection) if you want to override the existing values.
    
    Parameters:
    
    supportedTrainingInstanceTypes - A list of the instance types that this algorithm can use for training.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
    
    See Also:
    
    TrainingInstanceType
  - withSupportedTrainingInstanceTypes
```
public TrainingSpecification withSupportedTrainingInstanceTypes(Collection<String> supportedTrainingInstanceTypes)
```
    A list of the instance types that this algorithm can use for training.
    
    Parameters:
    
    supportedTrainingInstanceTypes - A list of the instance types that this algorithm can use for training.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
    
    See Also:
    
    TrainingInstanceType
  - withSupportedTrainingInstanceTypes
```
public TrainingSpecification withSupportedTrainingInstanceTypes(TrainingInstanceType... supportedTrainingInstanceTypes)
```
    A list of the instance types that this algorithm can use for training.
    
    Parameters:
    
    supportedTrainingInstanceTypes - A list of the instance types that this algorithm can use for training.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
    
    See Also:
    
    TrainingInstanceType
  - setSupportsDistributedTraining
```
public void setSupportsDistributedTraining(Boolean supportsDistributedTraining)
```
    Indicates whether the algorithm supports distributed training. If set to false, buyers can't request more than one instance during training.
    
    Parameters:
    
    supportsDistributedTraining - Indicates whether the algorithm supports distributed training. If set to false, buyers can't request more than one instance during training.
  - getSupportsDistributedTraining
```
public Boolean getSupportsDistributedTraining()
```
    Indicates whether the algorithm supports distributed training. If set to false, buyers can't request more than one instance during training.
    
    Returns:
    
    Indicates whether the algorithm supports distributed training. If set to false, buyers can't request more than one instance during training.
  - withSupportsDistributedTraining
```
public TrainingSpecification withSupportsDistributedTraining(Boolean supportsDistributedTraining)
```
    Indicates whether the algorithm supports distributed training. If set to false, buyers can't request more than one instance during training.
    
    Parameters:
    
    supportsDistributedTraining - Indicates whether the algorithm supports distributed training. If set to false, buyers can't request more than one instance during training.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - isSupportsDistributedTraining
```
public Boolean isSupportsDistributedTraining()
```
    Indicates whether the algorithm supports distributed training. If set to false, buyers can't request more than one instance during training.
    
    Returns:
    
    Indicates whether the algorithm supports distributed training. If set to false, buyers can't request more than one instance during training.
  - getMetricDefinitions
```
public List<MetricDefinition> getMetricDefinitions()
```
    A list of MetricDefinition objects, which are used for parsing metrics generated by the algorithm.
    
    Returns:
    
    A list of MetricDefinition objects, which are used for parsing metrics generated by the algorithm.
  - setMetricDefinitions
```
public void setMetricDefinitions(Collection<MetricDefinition> metricDefinitions)
```
    A list of MetricDefinition objects, which are used for parsing metrics generated by the algorithm.
    
    Parameters:
    
    metricDefinitions - A list of MetricDefinition objects, which are used for parsing metrics generated by the algorithm.
  - withMetricDefinitions
```
public TrainingSpecification withMetricDefinitions(MetricDefinition... metricDefinitions)
```
    A list of MetricDefinition objects, which are used for parsing metrics generated by the algorithm.
    
    NOTE: This method appends the values to the existing list (if any). Use setMetricDefinitions(java.util.Collection) or withMetricDefinitions(java.util.Collection) if you want to override the existing values.
    
    Parameters:
    
    metricDefinitions - A list of MetricDefinition objects, which are used for parsing metrics generated by the algorithm.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - withMetricDefinitions
```
public TrainingSpecification withMetricDefinitions(Collection<MetricDefinition> metricDefinitions)
```
    A list of MetricDefinition objects, which are used for parsing metrics generated by the algorithm.
    
    Parameters:
    
    metricDefinitions - A list of MetricDefinition objects, which are used for parsing metrics generated by the algorithm.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - getTrainingChannels
```
public List<ChannelSpecification> getTrainingChannels()
```
    A list of ChannelSpecification objects, which specify the input sources to be used by the algorithm.
    
    Returns:
    
    A list of ChannelSpecification objects, which specify the input sources to be used by the algorithm.
  - setTrainingChannels
```
public void setTrainingChannels(Collection<ChannelSpecification> trainingChannels)
```
    A list of ChannelSpecification objects, which specify the input sources to be used by the algorithm.
    
    Parameters:
    
    trainingChannels - A list of ChannelSpecification objects, which specify the input sources to be used by the algorithm.
  - withTrainingChannels
```
public TrainingSpecification withTrainingChannels(ChannelSpecification... trainingChannels)
```
    A list of ChannelSpecification objects, which specify the input sources to be used by the algorithm.
    
    NOTE: This method appends the values to the existing list (if any). Use setTrainingChannels(java.util.Collection) or withTrainingChannels(java.util.Collection) if you want to override the existing values.
    
    Parameters:
    
    trainingChannels - A list of ChannelSpecification objects, which specify the input sources to be used by the algorithm.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - withTrainingChannels
```
public TrainingSpecification withTrainingChannels(Collection<ChannelSpecification> trainingChannels)
```
    A list of ChannelSpecification objects, which specify the input sources to be used by the algorithm.
    
    Parameters:
    
    trainingChannels - A list of ChannelSpecification objects, which specify the input sources to be used by the algorithm.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - getSupportedTuningJobObjectiveMetrics
```
public List<HyperParameterTuningJobObjective> getSupportedTuningJobObjectiveMetrics()
```
    A list of the metrics that the algorithm emits that can be used as the objective metric in a hyperparameter tuning job.
    
    Returns:
    
    A list of the metrics that the algorithm emits that can be used as the objective metric in a hyperparameter tuning job.
  - setSupportedTuningJobObjectiveMetrics
```
public void setSupportedTuningJobObjectiveMetrics(Collection<HyperParameterTuningJobObjective> supportedTuningJobObjectiveMetrics)
```
    A list of the metrics that the algorithm emits that can be used as the objective metric in a hyperparameter tuning job.
    
    Parameters:
    
    supportedTuningJobObjectiveMetrics - A list of the metrics that the algorithm emits that can be used as the objective metric in a hyperparameter tuning job.
  - withSupportedTuningJobObjectiveMetrics
```
public TrainingSpecification withSupportedTuningJobObjectiveMetrics(HyperParameterTuningJobObjective... supportedTuningJobObjectiveMetrics)
```
    A list of the metrics that the algorithm emits that can be used as the objective metric in a hyperparameter tuning job.
    
    NOTE: This method appends the values to the existing list (if any). Use setSupportedTuningJobObjectiveMetrics(java.util.Collection) or withSupportedTuningJobObjectiveMetrics(java.util.Collection) if you want to override the existing values.
    
    Parameters:
    
    supportedTuningJobObjectiveMetrics - A list of the metrics that the algorithm emits that can be used as the objective metric in a hyperparameter tuning job.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - withSupportedTuningJobObjectiveMetrics
```
public TrainingSpecification withSupportedTuningJobObjectiveMetrics(Collection<HyperParameterTuningJobObjective> supportedTuningJobObjectiveMetrics)
```
    A list of the metrics that the algorithm emits that can be used as the objective metric in a hyperparameter tuning job.
    
    Parameters:
    
    supportedTuningJobObjectiveMetrics - A list of the metrics that the algorithm emits that can be used as the objective metric in a hyperparameter tuning job.
    
    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 TrainingSpecification 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.

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Class TrainingSpecification

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Constructor Detail

TrainingSpecification

Method Detail

setTrainingImage

getTrainingImage

withTrainingImage

setTrainingImageDigest

getTrainingImageDigest

withTrainingImageDigest

getSupportedHyperParameters

setSupportedHyperParameters

withSupportedHyperParameters

withSupportedHyperParameters

getSupportedTrainingInstanceTypes

setSupportedTrainingInstanceTypes

withSupportedTrainingInstanceTypes

withSupportedTrainingInstanceTypes

withSupportedTrainingInstanceTypes

setSupportsDistributedTraining

getSupportsDistributedTraining

withSupportsDistributedTraining

isSupportsDistributedTraining

getMetricDefinitions

setMetricDefinitions

withMetricDefinitions

withMetricDefinitions

getTrainingChannels

setTrainingChannels

withTrainingChannels

withTrainingChannels

getSupportedTuningJobObjectiveMetrics

setSupportedTuningJobObjectiveMetrics

withSupportedTuningJobObjectiveMetrics

withSupportedTuningJobObjectiveMetrics

toString

equals

hashCode

clone

marshall