@Generated(value="com.amazonaws:aws-java-sdk-code-generator") public class SolutionVersion extends Object implements Serializable, Cloneable, StructuredPojo
An object that provides information about a specific version of a Solution.
Constructor and Description |
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SolutionVersion() |
Modifier and Type | Method and Description |
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SolutionVersion |
clone() |
boolean |
equals(Object obj) |
Date |
getCreationDateTime()
The date and time (in Unix time) that this version of the solution was created.
|
String |
getDatasetGroupArn()
The Amazon Resource Name (ARN) of the dataset group providing the training data.
|
String |
getEventType()
The event type (for example, 'click' or 'like') that is used for training the model.
|
String |
getFailureReason()
If training a solution version fails, the reason for the failure.
|
Date |
getLastUpdatedDateTime()
The date and time (in Unix time) that the solution was last updated.
|
Boolean |
getPerformAutoML()
When true, Amazon Personalize searches for the most optimal recipe according to the solution configuration.
|
Boolean |
getPerformHPO()
Whether to perform hyperparameter optimization (HPO) on the chosen recipe.
|
String |
getRecipeArn()
The ARN of the recipe used in the solution.
|
String |
getSolutionArn()
The ARN of the solution.
|
SolutionConfig |
getSolutionConfig()
Describes the configuration properties for the solution.
|
String |
getSolutionVersionArn()
The ARN of the solution version.
|
String |
getStatus()
The status of the solution version.
|
Double |
getTrainingHours()
The time used to train the model.
|
String |
getTrainingMode()
The scope of training used to create the solution version.
|
TunedHPOParams |
getTunedHPOParams()
If hyperparameter optimization was performed, contains the hyperparameter values of the best performing model.
|
int |
hashCode() |
Boolean |
isPerformAutoML()
When true, Amazon Personalize searches for the most optimal recipe according to the solution configuration.
|
Boolean |
isPerformHPO()
Whether to perform hyperparameter optimization (HPO) on the chosen recipe.
|
void |
marshall(ProtocolMarshaller protocolMarshaller)
Marshalls this structured data using the given
ProtocolMarshaller . |
void |
setCreationDateTime(Date creationDateTime)
The date and time (in Unix time) that this version of the solution was created.
|
void |
setDatasetGroupArn(String datasetGroupArn)
The Amazon Resource Name (ARN) of the dataset group providing the training data.
|
void |
setEventType(String eventType)
The event type (for example, 'click' or 'like') that is used for training the model.
|
void |
setFailureReason(String failureReason)
If training a solution version fails, the reason for the failure.
|
void |
setLastUpdatedDateTime(Date lastUpdatedDateTime)
The date and time (in Unix time) that the solution was last updated.
|
void |
setPerformAutoML(Boolean performAutoML)
When true, Amazon Personalize searches for the most optimal recipe according to the solution configuration.
|
void |
setPerformHPO(Boolean performHPO)
Whether to perform hyperparameter optimization (HPO) on the chosen recipe.
|
void |
setRecipeArn(String recipeArn)
The ARN of the recipe used in the solution.
|
void |
setSolutionArn(String solutionArn)
The ARN of the solution.
|
void |
setSolutionConfig(SolutionConfig solutionConfig)
Describes the configuration properties for the solution.
|
void |
setSolutionVersionArn(String solutionVersionArn)
The ARN of the solution version.
|
void |
setStatus(String status)
The status of the solution version.
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void |
setTrainingHours(Double trainingHours)
The time used to train the model.
|
void |
setTrainingMode(String trainingMode)
The scope of training used to create the solution version.
|
void |
setTunedHPOParams(TunedHPOParams tunedHPOParams)
If hyperparameter optimization was performed, contains the hyperparameter values of the best performing model.
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String |
toString()
Returns a string representation of this object.
|
SolutionVersion |
withCreationDateTime(Date creationDateTime)
The date and time (in Unix time) that this version of the solution was created.
|
SolutionVersion |
withDatasetGroupArn(String datasetGroupArn)
The Amazon Resource Name (ARN) of the dataset group providing the training data.
|
SolutionVersion |
withEventType(String eventType)
The event type (for example, 'click' or 'like') that is used for training the model.
|
SolutionVersion |
withFailureReason(String failureReason)
If training a solution version fails, the reason for the failure.
|
SolutionVersion |
withLastUpdatedDateTime(Date lastUpdatedDateTime)
The date and time (in Unix time) that the solution was last updated.
|
SolutionVersion |
withPerformAutoML(Boolean performAutoML)
When true, Amazon Personalize searches for the most optimal recipe according to the solution configuration.
|
SolutionVersion |
withPerformHPO(Boolean performHPO)
Whether to perform hyperparameter optimization (HPO) on the chosen recipe.
|
SolutionVersion |
withRecipeArn(String recipeArn)
The ARN of the recipe used in the solution.
|
SolutionVersion |
withSolutionArn(String solutionArn)
The ARN of the solution.
|
SolutionVersion |
withSolutionConfig(SolutionConfig solutionConfig)
Describes the configuration properties for the solution.
|
SolutionVersion |
withSolutionVersionArn(String solutionVersionArn)
The ARN of the solution version.
|
SolutionVersion |
withStatus(String status)
The status of the solution version.
|
SolutionVersion |
withTrainingHours(Double trainingHours)
The time used to train the model.
|
SolutionVersion |
withTrainingMode(String trainingMode)
The scope of training used to create the solution version.
|
SolutionVersion |
withTrainingMode(TrainingMode trainingMode)
The scope of training used to create the solution version.
|
SolutionVersion |
withTunedHPOParams(TunedHPOParams tunedHPOParams)
If hyperparameter optimization was performed, contains the hyperparameter values of the best performing model.
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public void setSolutionVersionArn(String solutionVersionArn)
The ARN of the solution version.
solutionVersionArn
- The ARN of the solution version.public String getSolutionVersionArn()
The ARN of the solution version.
public SolutionVersion withSolutionVersionArn(String solutionVersionArn)
The ARN of the solution version.
solutionVersionArn
- The ARN of the solution version.public void setSolutionArn(String solutionArn)
The ARN of the solution.
solutionArn
- The ARN of the solution.public String getSolutionArn()
The ARN of the solution.
public SolutionVersion withSolutionArn(String solutionArn)
The ARN of the solution.
solutionArn
- The ARN of the solution.public void setPerformHPO(Boolean performHPO)
Whether to perform hyperparameter optimization (HPO) on the chosen recipe. The default is false
.
performHPO
- Whether to perform hyperparameter optimization (HPO) on the chosen recipe. The default is
false
.public Boolean getPerformHPO()
Whether to perform hyperparameter optimization (HPO) on the chosen recipe. The default is false
.
false
.public SolutionVersion withPerformHPO(Boolean performHPO)
Whether to perform hyperparameter optimization (HPO) on the chosen recipe. The default is false
.
performHPO
- Whether to perform hyperparameter optimization (HPO) on the chosen recipe. The default is
false
.public Boolean isPerformHPO()
Whether to perform hyperparameter optimization (HPO) on the chosen recipe. The default is false
.
false
.public void setPerformAutoML(Boolean performAutoML)
When true, Amazon Personalize searches for the most optimal recipe according to the solution configuration. When
false (the default), Amazon Personalize uses recipeArn
.
performAutoML
- When true, Amazon Personalize searches for the most optimal recipe according to the solution
configuration. When false (the default), Amazon Personalize uses recipeArn
.public Boolean getPerformAutoML()
When true, Amazon Personalize searches for the most optimal recipe according to the solution configuration. When
false (the default), Amazon Personalize uses recipeArn
.
recipeArn
.public SolutionVersion withPerformAutoML(Boolean performAutoML)
When true, Amazon Personalize searches for the most optimal recipe according to the solution configuration. When
false (the default), Amazon Personalize uses recipeArn
.
performAutoML
- When true, Amazon Personalize searches for the most optimal recipe according to the solution
configuration. When false (the default), Amazon Personalize uses recipeArn
.public Boolean isPerformAutoML()
When true, Amazon Personalize searches for the most optimal recipe according to the solution configuration. When
false (the default), Amazon Personalize uses recipeArn
.
recipeArn
.public void setRecipeArn(String recipeArn)
The ARN of the recipe used in the solution.
recipeArn
- The ARN of the recipe used in the solution.public String getRecipeArn()
The ARN of the recipe used in the solution.
public SolutionVersion withRecipeArn(String recipeArn)
The ARN of the recipe used in the solution.
recipeArn
- The ARN of the recipe used in the solution.public void setEventType(String eventType)
The event type (for example, 'click' or 'like') that is used for training the model.
eventType
- The event type (for example, 'click' or 'like') that is used for training the model.public String getEventType()
The event type (for example, 'click' or 'like') that is used for training the model.
public SolutionVersion withEventType(String eventType)
The event type (for example, 'click' or 'like') that is used for training the model.
eventType
- The event type (for example, 'click' or 'like') that is used for training the model.public void setDatasetGroupArn(String datasetGroupArn)
The Amazon Resource Name (ARN) of the dataset group providing the training data.
datasetGroupArn
- The Amazon Resource Name (ARN) of the dataset group providing the training data.public String getDatasetGroupArn()
The Amazon Resource Name (ARN) of the dataset group providing the training data.
public SolutionVersion withDatasetGroupArn(String datasetGroupArn)
The Amazon Resource Name (ARN) of the dataset group providing the training data.
datasetGroupArn
- The Amazon Resource Name (ARN) of the dataset group providing the training data.public void setSolutionConfig(SolutionConfig solutionConfig)
Describes the configuration properties for the solution.
solutionConfig
- Describes the configuration properties for the solution.public SolutionConfig getSolutionConfig()
Describes the configuration properties for the solution.
public SolutionVersion withSolutionConfig(SolutionConfig solutionConfig)
Describes the configuration properties for the solution.
solutionConfig
- Describes the configuration properties for the solution.public void setTrainingHours(Double trainingHours)
The time used to train the model. You are billed for the time it takes to train a model. This field is visible only after Amazon Personalize successfully trains a model.
trainingHours
- The time used to train the model. You are billed for the time it takes to train a model. This field is
visible only after Amazon Personalize successfully trains a model.public Double getTrainingHours()
The time used to train the model. You are billed for the time it takes to train a model. This field is visible only after Amazon Personalize successfully trains a model.
public SolutionVersion withTrainingHours(Double trainingHours)
The time used to train the model. You are billed for the time it takes to train a model. This field is visible only after Amazon Personalize successfully trains a model.
trainingHours
- The time used to train the model. You are billed for the time it takes to train a model. This field is
visible only after Amazon Personalize successfully trains a model.public void setTrainingMode(String trainingMode)
The scope of training used to create the solution version. The FULL
option trains the solution
version based on the entirety of the input solution's training data, while the UPDATE
option
processes only the training data that has changed since the creation of the last solution version. Choose
UPDATE
when you want to start recommending items added to the dataset without retraining the model.
The UPDATE
option can only be used after you've created a solution version with the
FULL
option and the training solution uses the native-recipe-hrnn-coldstart.
trainingMode
- The scope of training used to create the solution version. The FULL
option trains the
solution version based on the entirety of the input solution's training data, while the
UPDATE
option processes only the training data that has changed since the creation of the
last solution version. Choose UPDATE
when you want to start recommending items added to the
dataset without retraining the model.
The UPDATE
option can only be used after you've created a solution version with the
FULL
option and the training solution uses the native-recipe-hrnn-coldstart.
TrainingMode
public String getTrainingMode()
The scope of training used to create the solution version. The FULL
option trains the solution
version based on the entirety of the input solution's training data, while the UPDATE
option
processes only the training data that has changed since the creation of the last solution version. Choose
UPDATE
when you want to start recommending items added to the dataset without retraining the model.
The UPDATE
option can only be used after you've created a solution version with the
FULL
option and the training solution uses the native-recipe-hrnn-coldstart.
FULL
option trains the
solution version based on the entirety of the input solution's training data, while the
UPDATE
option processes only the training data that has changed since the creation of the
last solution version. Choose UPDATE
when you want to start recommending items added to the
dataset without retraining the model.
The UPDATE
option can only be used after you've created a solution version with the
FULL
option and the training solution uses the native-recipe-hrnn-coldstart.
TrainingMode
public SolutionVersion withTrainingMode(String trainingMode)
The scope of training used to create the solution version. The FULL
option trains the solution
version based on the entirety of the input solution's training data, while the UPDATE
option
processes only the training data that has changed since the creation of the last solution version. Choose
UPDATE
when you want to start recommending items added to the dataset without retraining the model.
The UPDATE
option can only be used after you've created a solution version with the
FULL
option and the training solution uses the native-recipe-hrnn-coldstart.
trainingMode
- The scope of training used to create the solution version. The FULL
option trains the
solution version based on the entirety of the input solution's training data, while the
UPDATE
option processes only the training data that has changed since the creation of the
last solution version. Choose UPDATE
when you want to start recommending items added to the
dataset without retraining the model.
The UPDATE
option can only be used after you've created a solution version with the
FULL
option and the training solution uses the native-recipe-hrnn-coldstart.
TrainingMode
public SolutionVersion withTrainingMode(TrainingMode trainingMode)
The scope of training used to create the solution version. The FULL
option trains the solution
version based on the entirety of the input solution's training data, while the UPDATE
option
processes only the training data that has changed since the creation of the last solution version. Choose
UPDATE
when you want to start recommending items added to the dataset without retraining the model.
The UPDATE
option can only be used after you've created a solution version with the
FULL
option and the training solution uses the native-recipe-hrnn-coldstart.
trainingMode
- The scope of training used to create the solution version. The FULL
option trains the
solution version based on the entirety of the input solution's training data, while the
UPDATE
option processes only the training data that has changed since the creation of the
last solution version. Choose UPDATE
when you want to start recommending items added to the
dataset without retraining the model.
The UPDATE
option can only be used after you've created a solution version with the
FULL
option and the training solution uses the native-recipe-hrnn-coldstart.
TrainingMode
public void setTunedHPOParams(TunedHPOParams tunedHPOParams)
If hyperparameter optimization was performed, contains the hyperparameter values of the best performing model.
tunedHPOParams
- If hyperparameter optimization was performed, contains the hyperparameter values of the best performing
model.public TunedHPOParams getTunedHPOParams()
If hyperparameter optimization was performed, contains the hyperparameter values of the best performing model.
public SolutionVersion withTunedHPOParams(TunedHPOParams tunedHPOParams)
If hyperparameter optimization was performed, contains the hyperparameter values of the best performing model.
tunedHPOParams
- If hyperparameter optimization was performed, contains the hyperparameter values of the best performing
model.public void setStatus(String status)
The status of the solution version.
A solution version can be in one of the following states:
CREATE PENDING
CREATE IN_PROGRESS
ACTIVE
CREATE FAILED
status
- The status of the solution version.
A solution version can be in one of the following states:
CREATE PENDING
CREATE IN_PROGRESS
ACTIVE
CREATE FAILED
public String getStatus()
The status of the solution version.
A solution version can be in one of the following states:
CREATE PENDING
CREATE IN_PROGRESS
ACTIVE
CREATE FAILED
A solution version can be in one of the following states:
CREATE PENDING
CREATE IN_PROGRESS
ACTIVE
CREATE FAILED
public SolutionVersion withStatus(String status)
The status of the solution version.
A solution version can be in one of the following states:
CREATE PENDING
CREATE IN_PROGRESS
ACTIVE
CREATE FAILED
status
- The status of the solution version.
A solution version can be in one of the following states:
CREATE PENDING
CREATE IN_PROGRESS
ACTIVE
CREATE FAILED
public void setFailureReason(String failureReason)
If training a solution version fails, the reason for the failure.
failureReason
- If training a solution version fails, the reason for the failure.public String getFailureReason()
If training a solution version fails, the reason for the failure.
public SolutionVersion withFailureReason(String failureReason)
If training a solution version fails, the reason for the failure.
failureReason
- If training a solution version fails, the reason for the failure.public void setCreationDateTime(Date creationDateTime)
The date and time (in Unix time) that this version of the solution was created.
creationDateTime
- The date and time (in Unix time) that this version of the solution was created.public Date getCreationDateTime()
The date and time (in Unix time) that this version of the solution was created.
public SolutionVersion withCreationDateTime(Date creationDateTime)
The date and time (in Unix time) that this version of the solution was created.
creationDateTime
- The date and time (in Unix time) that this version of the solution was created.public void setLastUpdatedDateTime(Date lastUpdatedDateTime)
The date and time (in Unix time) that the solution was last updated.
lastUpdatedDateTime
- The date and time (in Unix time) that the solution was last updated.public Date getLastUpdatedDateTime()
The date and time (in Unix time) that the solution was last updated.
public SolutionVersion withLastUpdatedDateTime(Date lastUpdatedDateTime)
The date and time (in Unix time) that the solution was last updated.
lastUpdatedDateTime
- The date and time (in Unix time) that the solution was last updated.public String toString()
toString
in class Object
Object.toString()
public SolutionVersion clone()
public void marshall(ProtocolMarshaller protocolMarshaller)
StructuredPojo
ProtocolMarshaller
.marshall
in interface StructuredPojo
protocolMarshaller
- Implementation of ProtocolMarshaller
used to marshall this object's data.