@Generated(value="com.amazonaws:awsjavasdkcodegenerator") public class CreateAlgorithmRequest extends AmazonWebServiceRequest implements Serializable, Cloneable
NOOP
Constructor and Description 

CreateAlgorithmRequest() 
Modifier and Type  Method and Description 

CreateAlgorithmRequest 
clone()
Creates a shallow clone of this object for all fields except the handler context.

boolean 
equals(Object obj) 
String 
getAlgorithmDescription()
A description of the algorithm.

String 
getAlgorithmName()
The name of the algorithm.

Boolean 
getCertifyForMarketplace()
Whether to certify the algorithm so that it can be listed in AWS Marketplace.

InferenceSpecification 
getInferenceSpecification()
Specifies details about inference jobs that the algorithm runs, including the following:

TrainingSpecification 
getTrainingSpecification()
Specifies details about training jobs run by this algorithm, including the following:

AlgorithmValidationSpecification 
getValidationSpecification()
Specifies configurations for one or more training jobs and that Amazon SageMaker runs to test the algorithm's
training code and, optionally, one or more batch transform jobs that Amazon SageMaker runs to test the
algorithm's inference code.

int 
hashCode() 
Boolean 
isCertifyForMarketplace()
Whether to certify the algorithm so that it can be listed in AWS Marketplace.

void 
setAlgorithmDescription(String algorithmDescription)
A description of the algorithm.

void 
setAlgorithmName(String algorithmName)
The name of the algorithm.

void 
setCertifyForMarketplace(Boolean certifyForMarketplace)
Whether to certify the algorithm so that it can be listed in AWS Marketplace.

void 
setInferenceSpecification(InferenceSpecification inferenceSpecification)
Specifies details about inference jobs that the algorithm runs, including the following:

void 
setTrainingSpecification(TrainingSpecification trainingSpecification)
Specifies details about training jobs run by this algorithm, including the following:

void 
setValidationSpecification(AlgorithmValidationSpecification validationSpecification)
Specifies configurations for one or more training jobs and that Amazon SageMaker runs to test the algorithm's
training code and, optionally, one or more batch transform jobs that Amazon SageMaker runs to test the
algorithm's inference code.

String 
toString()
Returns a string representation of this object.

CreateAlgorithmRequest 
withAlgorithmDescription(String algorithmDescription)
A description of the algorithm.

CreateAlgorithmRequest 
withAlgorithmName(String algorithmName)
The name of the algorithm.

CreateAlgorithmRequest 
withCertifyForMarketplace(Boolean certifyForMarketplace)
Whether to certify the algorithm so that it can be listed in AWS Marketplace.

CreateAlgorithmRequest 
withInferenceSpecification(InferenceSpecification inferenceSpecification)
Specifies details about inference jobs that the algorithm runs, including the following:

CreateAlgorithmRequest 
withTrainingSpecification(TrainingSpecification trainingSpecification)
Specifies details about training jobs run by this algorithm, including the following:

CreateAlgorithmRequest 
withValidationSpecification(AlgorithmValidationSpecification validationSpecification)
Specifies configurations for one or more training jobs and that Amazon SageMaker runs to test the algorithm's
training code and, optionally, one or more batch transform jobs that Amazon SageMaker runs to test the
algorithm's inference code.

addHandlerContext, getCloneRoot, getCloneSource, getCustomQueryParameters, getCustomRequestHeaders, getGeneralProgressListener, getHandlerContext, getReadLimit, getRequestClientOptions, getRequestCredentials, getRequestCredentialsProvider, getRequestMetricCollector, getSdkClientExecutionTimeout, getSdkRequestTimeout, putCustomQueryParameter, putCustomRequestHeader, setGeneralProgressListener, setRequestCredentials, setRequestCredentialsProvider, setRequestMetricCollector, setSdkClientExecutionTimeout, setSdkRequestTimeout, withGeneralProgressListener, withRequestCredentialsProvider, withRequestMetricCollector, withSdkClientExecutionTimeout, withSdkRequestTimeout
public void setAlgorithmName(String algorithmName)
The name of the algorithm.
algorithmName
 The name of the algorithm.public String getAlgorithmName()
The name of the algorithm.
public CreateAlgorithmRequest withAlgorithmName(String algorithmName)
The name of the algorithm.
algorithmName
 The name of the algorithm.public void setAlgorithmDescription(String algorithmDescription)
A description of the algorithm.
algorithmDescription
 A description of the algorithm.public String getAlgorithmDescription()
A description of the algorithm.
public CreateAlgorithmRequest withAlgorithmDescription(String algorithmDescription)
A description of the algorithm.
algorithmDescription
 A description of the algorithm.public void setTrainingSpecification(TrainingSpecification trainingSpecification)
Specifies details about training jobs run by this algorithm, including the following:
The Amazon ECR path of the container and the version digest of the algorithm.
The hyperparameters that the algorithm supports.
The instance types that the algorithm supports for training.
Whether the algorithm supports distributed training.
The metrics that the algorithm emits to Amazon CloudWatch.
Which metrics that the algorithm emits can be used as the objective metric for hyperparameter tuning jobs.
The input channels that the algorithm supports for training data. For example, an algorithm might support
train
, validation
, and test
channels.
trainingSpecification
 Specifies details about training jobs run by this algorithm, including the following:
The Amazon ECR path of the container and the version digest of the algorithm.
The hyperparameters that the algorithm supports.
The instance types that the algorithm supports for training.
Whether the algorithm supports distributed training.
The metrics that the algorithm emits to Amazon CloudWatch.
Which metrics that the algorithm emits can be used as the objective metric for hyperparameter tuning jobs.
The input channels that the algorithm supports for training data. For example, an algorithm might support
train
, validation
, and test
channels.
public TrainingSpecification getTrainingSpecification()
Specifies details about training jobs run by this algorithm, including the following:
The Amazon ECR path of the container and the version digest of the algorithm.
The hyperparameters that the algorithm supports.
The instance types that the algorithm supports for training.
Whether the algorithm supports distributed training.
The metrics that the algorithm emits to Amazon CloudWatch.
Which metrics that the algorithm emits can be used as the objective metric for hyperparameter tuning jobs.
The input channels that the algorithm supports for training data. For example, an algorithm might support
train
, validation
, and test
channels.
The Amazon ECR path of the container and the version digest of the algorithm.
The hyperparameters that the algorithm supports.
The instance types that the algorithm supports for training.
Whether the algorithm supports distributed training.
The metrics that the algorithm emits to Amazon CloudWatch.
Which metrics that the algorithm emits can be used as the objective metric for hyperparameter tuning jobs.
The input channels that the algorithm supports for training data. For example, an algorithm might support
train
, validation
, and test
channels.
public CreateAlgorithmRequest withTrainingSpecification(TrainingSpecification trainingSpecification)
Specifies details about training jobs run by this algorithm, including the following:
The Amazon ECR path of the container and the version digest of the algorithm.
The hyperparameters that the algorithm supports.
The instance types that the algorithm supports for training.
Whether the algorithm supports distributed training.
The metrics that the algorithm emits to Amazon CloudWatch.
Which metrics that the algorithm emits can be used as the objective metric for hyperparameter tuning jobs.
The input channels that the algorithm supports for training data. For example, an algorithm might support
train
, validation
, and test
channels.
trainingSpecification
 Specifies details about training jobs run by this algorithm, including the following:
The Amazon ECR path of the container and the version digest of the algorithm.
The hyperparameters that the algorithm supports.
The instance types that the algorithm supports for training.
Whether the algorithm supports distributed training.
The metrics that the algorithm emits to Amazon CloudWatch.
Which metrics that the algorithm emits can be used as the objective metric for hyperparameter tuning jobs.
The input channels that the algorithm supports for training data. For example, an algorithm might support
train
, validation
, and test
channels.
public void setInferenceSpecification(InferenceSpecification inferenceSpecification)
Specifies details about inference jobs that the algorithm runs, including the following:
The Amazon ECR paths of containers that contain the inference code and model artifacts.
The instance types that the algorithm supports for transform jobs and realtime endpoints used for inference.
The input and output content formats that the algorithm supports for inference.
inferenceSpecification
 Specifies details about inference jobs that the algorithm runs, including the following:
The Amazon ECR paths of containers that contain the inference code and model artifacts.
The instance types that the algorithm supports for transform jobs and realtime endpoints used for inference.
The input and output content formats that the algorithm supports for inference.
public InferenceSpecification getInferenceSpecification()
Specifies details about inference jobs that the algorithm runs, including the following:
The Amazon ECR paths of containers that contain the inference code and model artifacts.
The instance types that the algorithm supports for transform jobs and realtime endpoints used for inference.
The input and output content formats that the algorithm supports for inference.
The Amazon ECR paths of containers that contain the inference code and model artifacts.
The instance types that the algorithm supports for transform jobs and realtime endpoints used for inference.
The input and output content formats that the algorithm supports for inference.
public CreateAlgorithmRequest withInferenceSpecification(InferenceSpecification inferenceSpecification)
Specifies details about inference jobs that the algorithm runs, including the following:
The Amazon ECR paths of containers that contain the inference code and model artifacts.
The instance types that the algorithm supports for transform jobs and realtime endpoints used for inference.
The input and output content formats that the algorithm supports for inference.
inferenceSpecification
 Specifies details about inference jobs that the algorithm runs, including the following:
The Amazon ECR paths of containers that contain the inference code and model artifacts.
The instance types that the algorithm supports for transform jobs and realtime endpoints used for inference.
The input and output content formats that the algorithm supports for inference.
public void setValidationSpecification(AlgorithmValidationSpecification validationSpecification)
Specifies configurations for one or more training jobs and that Amazon SageMaker runs to test the algorithm's training code and, optionally, one or more batch transform jobs that Amazon SageMaker runs to test the algorithm's inference code.
validationSpecification
 Specifies configurations for one or more training jobs and that Amazon SageMaker runs to test the
algorithm's training code and, optionally, one or more batch transform jobs that Amazon SageMaker runs to
test the algorithm's inference code.public AlgorithmValidationSpecification getValidationSpecification()
Specifies configurations for one or more training jobs and that Amazon SageMaker runs to test the algorithm's training code and, optionally, one or more batch transform jobs that Amazon SageMaker runs to test the algorithm's inference code.
public CreateAlgorithmRequest withValidationSpecification(AlgorithmValidationSpecification validationSpecification)
Specifies configurations for one or more training jobs and that Amazon SageMaker runs to test the algorithm's training code and, optionally, one or more batch transform jobs that Amazon SageMaker runs to test the algorithm's inference code.
validationSpecification
 Specifies configurations for one or more training jobs and that Amazon SageMaker runs to test the
algorithm's training code and, optionally, one or more batch transform jobs that Amazon SageMaker runs to
test the algorithm's inference code.public void setCertifyForMarketplace(Boolean certifyForMarketplace)
Whether to certify the algorithm so that it can be listed in AWS Marketplace.
certifyForMarketplace
 Whether to certify the algorithm so that it can be listed in AWS Marketplace.public Boolean getCertifyForMarketplace()
Whether to certify the algorithm so that it can be listed in AWS Marketplace.
public CreateAlgorithmRequest withCertifyForMarketplace(Boolean certifyForMarketplace)
Whether to certify the algorithm so that it can be listed in AWS Marketplace.
certifyForMarketplace
 Whether to certify the algorithm so that it can be listed in AWS Marketplace.public Boolean isCertifyForMarketplace()
Whether to certify the algorithm so that it can be listed in AWS Marketplace.
public String toString()
toString
in class Object
Object.toString()
public CreateAlgorithmRequest clone()
AmazonWebServiceRequest
clone
in class AmazonWebServiceRequest
Object.clone()