Serialized Form (AWS Java SDK for Amazon SageMaker 1.11.355 API)

Package com.amazonaws.services.sagemaker.model
- Class com.amazonaws.services.sagemaker.model.AddTagsRequest extends AmazonWebServiceRequest implements Serializable
  - Serialized Fields
    - resourceArn
```
String resourceArn
```
      The Amazon Resource Name (ARN) of the resource that you want to tag.
    - tags
```
List<E> tags
```
      An array of Tag objects. Each tag is a key-value pair. Only the key parameter is required. If you don't specify a value, Amazon SageMaker sets the value to an empty string.
- Class com.amazonaws.services.sagemaker.model.AddTagsResult extends AmazonWebServiceResult<ResponseMetadata> implements Serializable
  - Serialized Fields
    - tags
```
List<E> tags
```
      A list of tags associated with the Amazon SageMaker resource.
- Class com.amazonaws.services.sagemaker.model.AlgorithmSpecification extends Object implements Serializable
  - Serialized Fields
    - trainingImage
```
String trainingImage
```
      The registry path of the Docker image that contains the training algorithm. For information about docker registry paths for built-in algorithms, see sagemaker-algo-docker-registry-paths.
    - trainingInputMode
```
String trainingInputMode
```
      The input mode that the algorithm supports. For the input modes that Amazon SageMaker algorithms support, see Algorithms. If an algorithm supports the File input mode, Amazon SageMaker downloads the training data from S3 to the provisioned ML storage Volume, and mounts the directory to docker volume for training container. If an algorithm supports the Pipe input mode, Amazon SageMaker streams data directly from S3 to the container.
      
      In File mode, make sure you provision ML storage volume with sufficient capacity to accommodate the data download from S3. In addition to the training data, the ML storage volume also stores the output model. The algorithm container use ML storage volume to also store intermediate information, if any.
      
      For distributed algorithms using File mode, training data is distributed uniformly, and your training duration is predictable if the input data objects size is approximately same. Amazon SageMaker does not split the files any further for model training. If the object sizes are skewed, training won't be optimal as the data distribution is also skewed where one host in a training cluster is overloaded, thus becoming bottleneck in training.
- Class com.amazonaws.services.sagemaker.model.AmazonSageMakerException extends AmazonServiceException implements Serializable
  
  serialVersionUID:
  
  1L
- Class com.amazonaws.services.sagemaker.model.CategoricalParameterRange extends Object implements Serializable
  - Serialized Fields
    - name
```
String name
```
      The name of the categorical hyperparameter to tune.
    - values
```
List<E> values
```
      A list of the categories for the hyperparameter.
- Class com.amazonaws.services.sagemaker.model.Channel extends Object implements Serializable
  - Serialized Fields
    - channelName
```
String channelName
```
      The name of the channel.
    - dataSource
```
DataSource dataSource
```
      The location of the channel data.
    - contentType
```
String contentType
```
      The MIME type of the data.
    - compressionType
```
String compressionType
```
      If training data is compressed, the compression type. The default value is None. CompressionType is used only in Pipe input mode. In File mode, leave this field unset or set it to None.
    - recordWrapperType
```
String recordWrapperType
```
      Specify RecordIO as the value when input data is in raw format but the training algorithm requires the RecordIO format, in which case, Amazon SageMaker wraps each individual S3 object in a RecordIO record. If the input data is already in RecordIO format, you don't need to set this attribute. For more information, see Create a Dataset Using RecordIO.
      
      In FILE mode, leave this field unset or set it to None.
- Class com.amazonaws.services.sagemaker.model.ContainerDefinition extends Object implements Serializable
  - Serialized Fields
    - containerHostname
```
String containerHostname
```
      The DNS host name for the container after Amazon SageMaker deploys it.
    - image
```
String image
```
      The Amazon EC2 Container Registry (Amazon ECR) path where inference code is stored. If you are using your own custom algorithm instead of an algorithm provided by Amazon SageMaker, the inference code must meet Amazon SageMaker requirements. For more information, see Using Your Own Algorithms with Amazon SageMaker
    - modelDataUrl
```
String modelDataUrl
```
      The S3 path where the model artifacts, which result from model training, are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).
    - environment
```
Map<K,V> environment
```
      The environment variables to set in the Docker container. Each key and value in the Environment string to string map can have length of up to 1024. We support up to 16 entries in the map.
- Class com.amazonaws.services.sagemaker.model.ContinuousParameterRange extends Object implements Serializable
  - Serialized Fields
    - name
```
String name
```
      The name of the continuous hyperparameter to tune.
    - minValue
```
String minValue
```
      The minimum value for the hyperparameter. The tuning job uses floating-point values between this value and MaxValuefor tuning.
    - maxValue
```
String maxValue
```
      The maximum value for the hyperparameter. The tuning job uses floating-point values between MinValue value and this value for tuning.
- Class com.amazonaws.services.sagemaker.model.CreateEndpointConfigRequest extends AmazonWebServiceRequest implements Serializable
  - Serialized Fields
    - endpointConfigName
```
String endpointConfigName
```
      The name of the endpoint configuration. You specify this name in a CreateEndpoint request.
    - productionVariants
```
List<E> productionVariants
```
      An array of ProductionVariant objects, one for each model that you want to host at this endpoint.
    - tags
```
List<E> tags
```
      An array of key-value pairs. For more information, see Using Cost Allocation Tags in the AWS Billing and Cost Management User Guide.
    - kmsKeyId
```
String kmsKeyId
```
      The Amazon Resource Name (ARN) of a AWS Key Management Service key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint.
- Class com.amazonaws.services.sagemaker.model.CreateEndpointConfigResult extends AmazonWebServiceResult<ResponseMetadata> implements Serializable
  - Serialized Fields
    - endpointConfigArn
```
String endpointConfigArn
```
      The Amazon Resource Name (ARN) of the endpoint configuration.
- Class com.amazonaws.services.sagemaker.model.CreateEndpointRequest extends AmazonWebServiceRequest implements Serializable
  - Serialized Fields
    - endpointName
```
String endpointName
```
      The name of the endpoint. The name must be unique within an AWS Region in your AWS account.
    - endpointConfigName
```
String endpointConfigName
```
      The name of an endpoint configuration. For more information, see CreateEndpointConfig.
    - tags
```
List<E> tags
```
      An array of key-value pairs. For more information, see Using Cost Allocation Tagsin the AWS Billing and Cost Management User Guide.
- Class com.amazonaws.services.sagemaker.model.CreateEndpointResult extends AmazonWebServiceResult<ResponseMetadata> implements Serializable
  - Serialized Fields
    - endpointArn
```
String endpointArn
```
      The Amazon Resource Name (ARN) of the endpoint.
- Class com.amazonaws.services.sagemaker.model.CreateHyperParameterTuningJobRequest extends AmazonWebServiceRequest implements Serializable
  - Serialized Fields
    - hyperParameterTuningJobName
```
String hyperParameterTuningJobName
```
      The name of the tuning job. This name is the prefix for the names of all training jobs that this tuning job launches. The name must be unique within the same AWS account and AWS Region. Names are not case sensitive, and must be between 1-32 characters.
    - hyperParameterTuningJobConfig
```
HyperParameterTuningJobConfig hyperParameterTuningJobConfig
```
      The object that describes the tuning job, including the search strategy, metric used to evaluate training jobs, ranges of parameters to search, and resource limits for the tuning job.
    - trainingJobDefinition
```
HyperParameterTrainingJobDefinition trainingJobDefinition
```
      The object that describes the training jobs that this tuning job launches, including static hyperparameters, input data configuration, output data configuration, resource configuration, and stopping condition.
    - tags
```
List<E> tags
```
      An array of key-value pairs. You can use tags to categorize your AWS resources in different ways, for example, by purpose, owner, or environment. For more information, see Using Cost Allocation Tags in the AWS Billing and Cost Management User Guide.
- Class com.amazonaws.services.sagemaker.model.CreateHyperParameterTuningJobResult extends AmazonWebServiceResult<ResponseMetadata> implements Serializable
  - Serialized Fields
    - hyperParameterTuningJobArn
```
String hyperParameterTuningJobArn
```
      The Amazon Resource Name (ARN) of the tuning job.
- Class com.amazonaws.services.sagemaker.model.CreateModelRequest extends AmazonWebServiceRequest implements Serializable
  - Serialized Fields
    - modelName
```
String modelName
```
      The name of the new model.
    - primaryContainer
```
ContainerDefinition primaryContainer
```
      The location of the primary docker image containing inference code, associated artifacts, and custom environment map that the inference code uses when the model is deployed into production.
    - executionRoleArn
```
String executionRoleArn
```
      The Amazon Resource Name (ARN) of the IAM role that Amazon SageMaker can assume to access model artifacts and docker image for deployment on ML compute instances. Deploying on ML compute instances is part of model hosting. For more information, see Amazon SageMaker Roles.
      
      To be able to pass this role to Amazon SageMaker, the caller of this API must have the iam:PassRole permission.
    - tags
```
List<E> tags
```
      An array of key-value pairs. For more information, see Using Cost Allocation Tags in the AWS Billing and Cost Management User Guide.
    - vpcConfig
```
VpcConfig vpcConfig
```
      A object that specifies the VPC that you want your model to connect to. Control access to and from your model container by configuring the VPC. For more information, see host-vpc.
- Class com.amazonaws.services.sagemaker.model.CreateModelResult extends AmazonWebServiceResult<ResponseMetadata> implements Serializable
  - Serialized Fields
    - modelArn
```
String modelArn
```
      The ARN of the model created in Amazon SageMaker.
- Class com.amazonaws.services.sagemaker.model.CreateNotebookInstanceLifecycleConfigRequest extends AmazonWebServiceRequest implements Serializable
  - Serialized Fields
    - notebookInstanceLifecycleConfigName
```
String notebookInstanceLifecycleConfigName
```
      The name of the lifecycle configuration.
    - onCreate
```
List<E> onCreate
```
      A shell script that runs only once, when you create a notebook instance.
    - onStart
```
List<E> onStart
```
      A shell script that runs every time you start a notebook instance, including when you create the notebook instance.
- Class com.amazonaws.services.sagemaker.model.CreateNotebookInstanceLifecycleConfigResult extends AmazonWebServiceResult<ResponseMetadata> implements Serializable
  - Serialized Fields
    - notebookInstanceLifecycleConfigArn
```
String notebookInstanceLifecycleConfigArn
```
      The Amazon Resource Name (ARN) of the lifecycle configuration.
- Class com.amazonaws.services.sagemaker.model.CreateNotebookInstanceRequest extends AmazonWebServiceRequest implements Serializable
  - Serialized Fields
    - notebookInstanceName
```
String notebookInstanceName
```
      The name of the new notebook instance.
    - instanceType
```
String instanceType
```
      The type of ML compute instance to launch for the notebook instance.
    - subnetId
```
String subnetId
```
      The ID of the subnet in a VPC to which you would like to have a connectivity from your ML compute instance.
    - securityGroupIds
```
List<E> securityGroupIds
```
      The VPC security group IDs, in the form sg-xxxxxxxx. The security groups must be for the same VPC as specified in the subnet.
    - roleArn
```
String roleArn
```
      When you send any requests to AWS resources from the notebook instance, Amazon SageMaker assumes this role to perform tasks on your behalf. You must grant this role necessary permissions so Amazon SageMaker can perform these tasks. The policy must allow the Amazon SageMaker service principal (sagemaker.amazonaws.com) permissions to assume this role. For more information, see Amazon SageMaker Roles.
      
      To be able to pass this role to Amazon SageMaker, the caller of this API must have the iam:PassRole permission.
    - kmsKeyId
```
String kmsKeyId
```
      If you provide a AWS KMS key ID, Amazon SageMaker uses it to encrypt data at rest on the ML storage volume that is attached to your notebook instance.
    - tags
```
List<E> tags
```
      A list of tags to associate with the notebook instance. You can add tags later by using the CreateTags API.
    - lifecycleConfigName
```
String lifecycleConfigName
```
      The name of a lifecycle configuration to associate with the notebook instance. For information about lifestyle configurations, see notebook-lifecycle-config.
    - directInternetAccess
```
String directInternetAccess
```
      Sets whether Amazon SageMaker provides internet access to the notebook instance. If you set this to Disabled this notebook instance will be able to access resources only in your VPC, and will not be able to connect to Amazon SageMaker training and endpoint services unless your configure a NAT Gateway in your VPC.
      
      For more information, see appendix-notebook-and-internet-access. You can set the value of this parameter to Disabled only if you set a value for the SubnetId parameter.
- Class com.amazonaws.services.sagemaker.model.CreateNotebookInstanceResult extends AmazonWebServiceResult<ResponseMetadata> implements Serializable
  - Serialized Fields
    - notebookInstanceArn
```
String notebookInstanceArn
```
      The Amazon Resource Name (ARN) of the notebook instance.
- Class com.amazonaws.services.sagemaker.model.CreatePresignedNotebookInstanceUrlRequest extends AmazonWebServiceRequest implements Serializable
  - Serialized Fields
    - notebookInstanceName
```
String notebookInstanceName
```
      The name of the notebook instance.
    - sessionExpirationDurationInSeconds
```
Integer sessionExpirationDurationInSeconds
```
      The duration of the session, in seconds. The default is 12 hours.
- Class com.amazonaws.services.sagemaker.model.CreatePresignedNotebookInstanceUrlResult extends AmazonWebServiceResult<ResponseMetadata> implements Serializable
  - Serialized Fields
    - authorizedUrl
```
String authorizedUrl
```
      A JSON object that contains the URL string.
- Class com.amazonaws.services.sagemaker.model.CreateTrainingJobRequest extends AmazonWebServiceRequest implements Serializable
  - Serialized Fields
    - trainingJobName
```
String trainingJobName
```
      The name of the training job. The name must be unique within an AWS Region in an AWS account. It appears in the Amazon SageMaker console.
    - hyperParameters
```
Map<K,V> hyperParameters
```
      Algorithm-specific parameters that influence the quality of the model. You set hyperparameters before you start the learning process. For a list of hyperparameters for each training algorithm provided by Amazon SageMaker, see Algorithms.
      
      You can specify a maximum of 100 hyperparameters. Each hyperparameter is a key-value pair. Each key and value is limited to 256 characters, as specified by the Length Constraint.
    - algorithmSpecification
```
AlgorithmSpecification algorithmSpecification
```
      The registry path of the Docker image that contains the training algorithm and algorithm-specific metadata, including the input mode. For more information about algorithms provided by Amazon SageMaker, see Algorithms. For information about providing your own algorithms, see your-algorithms.
    - roleArn
```
String roleArn
```
      The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
      
      During model training, Amazon SageMaker needs your permission to read input data from an S3 bucket, download a Docker image that contains training code, write model artifacts to an S3 bucket, write logs to Amazon CloudWatch Logs, and publish metrics to Amazon CloudWatch. You grant permissions for all of these tasks to an IAM role. For more information, see Amazon SageMaker Roles.
      
      To be able to pass this role to Amazon SageMaker, the caller of this API must have the iam:PassRole permission.
    - inputDataConfig
```
List<E> inputDataConfig
```
      An array of Channel objects. Each channel is a named input source. InputDataConfig describes the input data and its location.
      
      Algorithms can accept input data from one or more channels. For example, an algorithm might have two channels of input data, training_data and validation_data. The configuration for each channel provides the S3 location where the input data is stored. It also provides information about the stored data: the MIME type, compression method, and whether the data is wrapped in RecordIO format.
      
      Depending on the input mode that the algorithm supports, Amazon SageMaker either copies input data files from an S3 bucket to a local directory in the Docker container, or makes it available as input streams.
    - outputDataConfig
```
OutputDataConfig outputDataConfig
```
      Specifies the path to the S3 bucket where you want to store model artifacts. Amazon SageMaker creates subfolders for the artifacts.
    - resourceConfig
```
ResourceConfig resourceConfig
```
      The resources, including the ML compute instances and ML storage volumes, to use for model training.
      
      ML storage volumes store model artifacts and incremental states. Training algorithms might also use ML storage volumes for scratch space. If you want Amazon SageMaker to use the ML storage volume to store the training data, choose File as the TrainingInputMode in the algorithm specification. For distributed training algorithms, specify an instance count greater than 1.
    - vpcConfig
```
VpcConfig vpcConfig
```
      A object that specifies the VPC that you want your training job to connect to. Control access to and from your training container by configuring the VPC. For more information, see train-vpc
    - stoppingCondition
```
StoppingCondition stoppingCondition
```
      Sets a duration for training. Use this parameter to cap model training costs. To stop a job, Amazon SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms might use this 120-second window to save the model artifacts.
      
      When Amazon SageMaker terminates a job because the stopping condition has been met, training algorithms provided by Amazon SageMaker save the intermediate results of the job. This intermediate data is a valid model artifact. You can use it to create a model using the CreateModel API.
    - tags
```
List<E> tags
```
      An array of key-value pairs. For more information, see Using Cost Allocation Tags in the AWS Billing and Cost Management User Guide.
- Class com.amazonaws.services.sagemaker.model.CreateTrainingJobResult extends AmazonWebServiceResult<ResponseMetadata> implements Serializable
  - Serialized Fields
    - trainingJobArn
```
String trainingJobArn
```
      The Amazon Resource Name (ARN) of the training job.
- Class com.amazonaws.services.sagemaker.model.DataSource extends Object implements Serializable
  - Serialized Fields
    - s3DataSource
```
S3DataSource s3DataSource
```
      The S3 location of the data source that is associated with a channel.
- Class com.amazonaws.services.sagemaker.model.DeleteEndpointConfigRequest extends AmazonWebServiceRequest implements Serializable
  - Serialized Fields
    - endpointConfigName
```
String endpointConfigName
```
      The name of the endpoint configuration that you want to delete.
- Class com.amazonaws.services.sagemaker.model.DeleteEndpointConfigResult extends AmazonWebServiceResult<ResponseMetadata> implements Serializable
- Class com.amazonaws.services.sagemaker.model.DeleteEndpointRequest extends AmazonWebServiceRequest implements Serializable
  - Serialized Fields
    - endpointName
```
String endpointName
```
      The name of the endpoint that you want to delete.
- Class com.amazonaws.services.sagemaker.model.DeleteEndpointResult extends AmazonWebServiceResult<ResponseMetadata> implements Serializable
- Class com.amazonaws.services.sagemaker.model.DeleteModelRequest extends AmazonWebServiceRequest implements Serializable
  - Serialized Fields
    - modelName
```
String modelName
```
      The name of the model to delete.
- Class com.amazonaws.services.sagemaker.model.DeleteModelResult extends AmazonWebServiceResult<ResponseMetadata> implements Serializable
- Class com.amazonaws.services.sagemaker.model.DeleteNotebookInstanceLifecycleConfigRequest extends AmazonWebServiceRequest implements Serializable
  - Serialized Fields
    - notebookInstanceLifecycleConfigName
```
String notebookInstanceLifecycleConfigName
```
      The name of the lifecycle configuration to delete.
- Class com.amazonaws.services.sagemaker.model.DeleteNotebookInstanceLifecycleConfigResult extends AmazonWebServiceResult<ResponseMetadata> implements Serializable
- Class com.amazonaws.services.sagemaker.model.DeleteNotebookInstanceRequest extends AmazonWebServiceRequest implements Serializable
  - Serialized Fields
    - notebookInstanceName
```
String notebookInstanceName
```
      The name of the Amazon SageMaker notebook instance to delete.
- Class com.amazonaws.services.sagemaker.model.DeleteNotebookInstanceResult extends AmazonWebServiceResult<ResponseMetadata> implements Serializable
- Class com.amazonaws.services.sagemaker.model.DeleteTagsRequest extends AmazonWebServiceRequest implements Serializable
  - Serialized Fields
    - resourceArn
```
String resourceArn
```
      The Amazon Resource Name (ARN) of the resource whose tags you want to delete.
    - tagKeys
```
List<E> tagKeys
```
      An array or one or more tag keys to delete.
- Class com.amazonaws.services.sagemaker.model.DeleteTagsResult extends AmazonWebServiceResult<ResponseMetadata> implements Serializable
- Class com.amazonaws.services.sagemaker.model.DescribeEndpointConfigRequest extends AmazonWebServiceRequest implements Serializable
  - Serialized Fields
    - endpointConfigName
```
String endpointConfigName
```
      The name of the endpoint configuration.
- Class com.amazonaws.services.sagemaker.model.DescribeEndpointConfigResult extends AmazonWebServiceResult<ResponseMetadata> implements Serializable
  - Serialized Fields
    - endpointConfigName
```
String endpointConfigName
```
      Name of the Amazon SageMaker endpoint configuration.
    - endpointConfigArn
```
String endpointConfigArn
```
      The Amazon Resource Name (ARN) of the endpoint configuration.
    - productionVariants
```
List<E> productionVariants
```
      An array of ProductionVariant objects, one for each model that you want to host at this endpoint.
    - kmsKeyId
```
String kmsKeyId
```
      AWS KMS key ID Amazon SageMaker uses to encrypt data when storing it on the ML storage volume attached to the instance.
    - creationTime
```
Date creationTime
```
      A timestamp that shows when the endpoint configuration was created.
- Class com.amazonaws.services.sagemaker.model.DescribeEndpointRequest extends AmazonWebServiceRequest implements Serializable
  - Serialized Fields
    - endpointName
```
String endpointName
```
      The name of the endpoint.
- Class com.amazonaws.services.sagemaker.model.DescribeEndpointResult extends AmazonWebServiceResult<ResponseMetadata> implements Serializable
  - Serialized Fields
    - endpointName
```
String endpointName
```
      Name of the endpoint.
    - endpointArn
```
String endpointArn
```
      The Amazon Resource Name (ARN) of the endpoint.
    - endpointConfigName
```
String endpointConfigName
```
      The name of the endpoint configuration associated with this endpoint.
    - productionVariants
```
List<E> productionVariants
```
      An array of ProductionVariant objects, one for each model hosted behind this endpoint.
    - endpointStatus
```
String endpointStatus
```
      The status of the endpoint.
    - failureReason
```
String failureReason
```
      If the status of the endpoint is Failed, the reason why it failed.
    - creationTime
```
Date creationTime
```
      A timestamp that shows when the endpoint was created.
    - lastModifiedTime
```
Date lastModifiedTime
```
      A timestamp that shows when the endpoint was last modified.
- Class com.amazonaws.services.sagemaker.model.DescribeHyperParameterTuningJobRequest extends AmazonWebServiceRequest implements Serializable
  - Serialized Fields
    - hyperParameterTuningJobName
```
String hyperParameterTuningJobName
```
      The name of the tuning job to describe.
- Class com.amazonaws.services.sagemaker.model.DescribeHyperParameterTuningJobResult extends AmazonWebServiceResult<ResponseMetadata> implements Serializable
  - Serialized Fields
    - hyperParameterTuningJobName
```
String hyperParameterTuningJobName
```
      The name of the tuning job.
    - hyperParameterTuningJobArn
```
String hyperParameterTuningJobArn
```
      The Amazon Resource Name (ARN) of the tuning job.
    - hyperParameterTuningJobConfig
```
HyperParameterTuningJobConfig hyperParameterTuningJobConfig
```
      The object that specifies the configuration of the tuning job.
    - trainingJobDefinition
```
HyperParameterTrainingJobDefinition trainingJobDefinition
```
      The object that specifies the definition of the training jobs that this tuning job launches.
    - hyperParameterTuningJobStatus
```
String hyperParameterTuningJobStatus
```
      The status of the tuning job: InProgress, Completed, Failed, Stopping, or Stopped.
    - creationTime
```
Date creationTime
```
      The date and time that the tuning job started.
    - hyperParameterTuningEndTime
```
Date hyperParameterTuningEndTime
```
      The date and time that the tuning job ended.
    - lastModifiedTime
```
Date lastModifiedTime
```
      The date and time that the status of the tuning job was modified.
    - trainingJobStatusCounters
```
TrainingJobStatusCounters trainingJobStatusCounters
```
      The object that specifies the number of training jobs, categorized by status, that this tuning job launched.
    - objectiveStatusCounters
```
ObjectiveStatusCounters objectiveStatusCounters
```
      The object that specifies the number of training jobs, categorized by the status of their final objective metric, that this tuning job launched.
    - bestTrainingJob
```
HyperParameterTrainingJobSummary bestTrainingJob
```
      A object that describes the training job that completed with the best current .
    - failureReason
```
String failureReason
```
      If the tuning job failed, the reason it failed.
- Class com.amazonaws.services.sagemaker.model.DescribeModelRequest extends AmazonWebServiceRequest implements Serializable
  - Serialized Fields
    - modelName
```
String modelName
```
      The name of the model.
- Class com.amazonaws.services.sagemaker.model.DescribeModelResult extends AmazonWebServiceResult<ResponseMetadata> implements Serializable
  - Serialized Fields
    - modelName
```
String modelName
```
      Name of the Amazon SageMaker model.
    - primaryContainer
```
ContainerDefinition primaryContainer
```
      The location of the primary inference code, associated artifacts, and custom environment map that the inference code uses when it is deployed in production.
    - executionRoleArn
```
String executionRoleArn
```
      The Amazon Resource Name (ARN) of the IAM role that you specified for the model.
    - vpcConfig
```
VpcConfig vpcConfig
```
      A object that specifies the VPC that this model has access to. For more information, see host-vpc
    - creationTime
```
Date creationTime
```
      A timestamp that shows when the model was created.
    - modelArn
```
String modelArn
```
      The Amazon Resource Name (ARN) of the model.
- Class com.amazonaws.services.sagemaker.model.DescribeNotebookInstanceLifecycleConfigRequest extends AmazonWebServiceRequest implements Serializable
  - Serialized Fields
    - notebookInstanceLifecycleConfigName
```
String notebookInstanceLifecycleConfigName
```
      The name of the lifecycle configuration to describe.
- Class com.amazonaws.services.sagemaker.model.DescribeNotebookInstanceLifecycleConfigResult extends AmazonWebServiceResult<ResponseMetadata> implements Serializable
  - Serialized Fields
    - notebookInstanceLifecycleConfigArn
```
String notebookInstanceLifecycleConfigArn
```
      The Amazon Resource Name (ARN) of the lifecycle configuration.
    - notebookInstanceLifecycleConfigName
```
String notebookInstanceLifecycleConfigName
```
      The name of the lifecycle configuration.
    - onCreate
```
List<E> onCreate
```
      The shell script that runs only once, when you create a notebook instance.
    - onStart
```
List<E> onStart
```
      The shell script that runs every time you start a notebook instance, including when you create the notebook instance.
    - lastModifiedTime
```
Date lastModifiedTime
```
      A timestamp that tells when the lifecycle configuration was last modified.
    - creationTime
```
Date creationTime
```
      A timestamp that tells when the lifecycle configuration was created.
- Class com.amazonaws.services.sagemaker.model.DescribeNotebookInstanceRequest extends AmazonWebServiceRequest implements Serializable
  - Serialized Fields
    - notebookInstanceName
```
String notebookInstanceName
```
      The name of the notebook instance that you want information about.
- Class com.amazonaws.services.sagemaker.model.DescribeNotebookInstanceResult extends AmazonWebServiceResult<ResponseMetadata> implements Serializable
  - Serialized Fields
    - notebookInstanceArn
```
String notebookInstanceArn
```
      The Amazon Resource Name (ARN) of the notebook instance.
    - notebookInstanceName
```
String notebookInstanceName
```
      Name of the Amazon SageMaker notebook instance.
    - notebookInstanceStatus
```
String notebookInstanceStatus
```
      The status of the notebook instance.
    - failureReason
```
String failureReason
```
      If status is failed, the reason it failed.
    - url
```
String url
```
      The URL that you use to connect to the Jupyter notebook that is running in your notebook instance.
    - instanceType
```
String instanceType
```
      The type of ML compute instance running on the notebook instance.
    - subnetId
```
String subnetId
```
      The ID of the VPC subnet.
    - securityGroups
```
List<E> securityGroups
```
      The IDs of the VPC security groups.
    - roleArn
```
String roleArn
```
      Amazon Resource Name (ARN) of the IAM role associated with the instance.
    - kmsKeyId
```
String kmsKeyId
```
      AWS KMS key ID Amazon SageMaker uses to encrypt data when storing it on the ML storage volume attached to the instance.
    - networkInterfaceId
```
String networkInterfaceId
```
      Network interface IDs that Amazon SageMaker created at the time of creating the instance.
    - lastModifiedTime
```
Date lastModifiedTime
```
      A timestamp. Use this parameter to retrieve the time when the notebook instance was last modified.
    - creationTime
```
Date creationTime
```
      A timestamp. Use this parameter to return the time when the notebook instance was created
    - notebookInstanceLifecycleConfigName
```
String notebookInstanceLifecycleConfigName
```
      Returns the name of a notebook instance lifecycle configuration.
      
      For information about notebook instance lifestyle configurations, see notebook-lifecycle-config.
    - directInternetAccess
```
String directInternetAccess
```
      Describes whether Amazon SageMaker provides internet access to the notebook instance. If this value is set to Disabled, he notebook instance does not have internet access, and cannot connect to Amazon SageMaker training and endpoint services.
      
      For more information, see appendix-notebook-and-internet-access.
- Class com.amazonaws.services.sagemaker.model.DescribeTrainingJobRequest extends AmazonWebServiceRequest implements Serializable
  - Serialized Fields
    - trainingJobName
```
String trainingJobName
```
      The name of the training job.
- Class com.amazonaws.services.sagemaker.model.DescribeTrainingJobResult extends AmazonWebServiceResult<ResponseMetadata> implements Serializable
  - Serialized Fields
    - trainingJobName
```
String trainingJobName
```
      Name of the model training job.
    - trainingJobArn
```
String trainingJobArn
```
      The Amazon Resource Name (ARN) of the training job.
    - tuningJobArn
```
String tuningJobArn
```
      The Amazon Resource Name (ARN) of the associated hyperparameter tuning job if the training job was launched by a hyperparameter tuning job.
    - modelArtifacts
```
ModelArtifacts modelArtifacts
```
      Information about the Amazon S3 location that is configured for storing model artifacts.
    - trainingJobStatus
```
String trainingJobStatus
```
      The status of the training job.
      
      For the InProgress status, Amazon SageMaker can return these secondary statuses:
      
      Starting - Preparing for training.
      
      Downloading - Optional stage for algorithms that support File training input mode. It indicates data is being downloaded to ML storage volumes.
      
      Training - Training is in progress.
      
      Uploading - Training is complete and model upload is in progress.
      
      For the Stopped training status, Amazon SageMaker can return these secondary statuses:
      
      MaxRuntimeExceeded - Job stopped as a result of maximum allowed runtime exceeded.
    - secondaryStatus
```
String secondaryStatus
```
      Provides granular information about the system state. For more information, see TrainingJobStatus.
    - failureReason
```
String failureReason
```
      If the training job failed, the reason it failed.
    - hyperParameters
```
Map<K,V> hyperParameters
```
      Algorithm-specific parameters.
    - algorithmSpecification
```
AlgorithmSpecification algorithmSpecification
```
      Information about the algorithm used for training, and algorithm metadata.
    - roleArn
```
String roleArn
```
      The AWS Identity and Access Management (IAM) role configured for the training job.
    - inputDataConfig
```
List<E> inputDataConfig
```
      An array of Channel objects that describes each data input channel.
    - outputDataConfig
```
OutputDataConfig outputDataConfig
```
      The S3 path where model artifacts that you configured when creating the job are stored. Amazon SageMaker creates subfolders for model artifacts.
    - resourceConfig
```
ResourceConfig resourceConfig
```
      Resources, including ML compute instances and ML storage volumes, that are configured for model training.
    - vpcConfig
```
VpcConfig vpcConfig
```
      A object that specifies the VPC that this training job has access to. For more information, see train-vpc.
    - stoppingCondition
```
StoppingCondition stoppingCondition
```
      The condition under which to stop the training job.
    - creationTime
```
Date creationTime
```
      A timestamp that indicates when the training job was created.
    - trainingStartTime
```
Date trainingStartTime
```
      Indicates the time when the training job starts on training instances. You are billed for the time interval between this time and the value of TrainingEndTime. The start time in CloudWatch Logs might be later than this time. The difference is due to the time it takes to download the training data and to the size of the training container.
    - trainingEndTime
```
Date trainingEndTime
```
      Indicates the time when the training job ends on training instances. You are billed for the time interval between the value of TrainingStartTime and this time. For successful jobs and stopped jobs, this is the time after model artifacts are uploaded. For failed jobs, this is the time when Amazon SageMaker detects a job failure.
    - lastModifiedTime
```
Date lastModifiedTime
```
      A timestamp that indicates when the status of the training job was last modified.
- Class com.amazonaws.services.sagemaker.model.DesiredWeightAndCapacity extends Object implements Serializable
  - Serialized Fields
    - variantName
```
String variantName
```
      The name of the variant to update.
    - desiredWeight
```
Float desiredWeight
```
      The variant's weight.
    - desiredInstanceCount
```
Integer desiredInstanceCount
```
      The variant's capacity.
- Class com.amazonaws.services.sagemaker.model.EndpointConfigSummary extends Object implements Serializable
  - Serialized Fields
    - endpointConfigName
```
String endpointConfigName
```
      The name of the endpoint configuration.
    - endpointConfigArn
```
String endpointConfigArn
```
      The Amazon Resource Name (ARN) of the endpoint configuration.
    - creationTime
```
Date creationTime
```
      A timestamp that shows when the endpoint configuration was created.
- Class com.amazonaws.services.sagemaker.model.EndpointSummary extends Object implements Serializable
  - Serialized Fields
    - endpointName
```
String endpointName
```
      The name of the endpoint.
    - endpointArn
```
String endpointArn
```
      The Amazon Resource Name (ARN) of the endpoint.
    - creationTime
```
Date creationTime
```
      A timestamp that shows when the endpoint was created.
    - lastModifiedTime
```
Date lastModifiedTime
```
      A timestamp that shows when the endpoint was last modified.
    - endpointStatus
```
String endpointStatus
```
      The status of the endpoint.
- Class com.amazonaws.services.sagemaker.model.FinalHyperParameterTuningJobObjectiveMetric extends Object implements Serializable
  - Serialized Fields
    - type
```
String type
```
      Whether to minimize or maximize the objective metric. Valid values are Minimize and Maximize.
    - metricName
```
String metricName
```
      The name of the objective metric.
    - value
```
Float value
```
      The value of the objective metric.
- Class com.amazonaws.services.sagemaker.model.HyperParameterAlgorithmSpecification extends Object implements Serializable
  - Serialized Fields
    - trainingImage
```
String trainingImage
```
      The registry path of the Docker image that contains the training algorithm. For information about Docker registry paths for built-in algorithms, see sagemaker-algo-docker-registry-paths.
    - trainingInputMode
```
String trainingInputMode
```
      The input mode that the algorithm supports: File or Pipe. In File input mode, Amazon SageMaker downloads the training data from Amazon S3 to the storage volume that is attached to the training instance and mounts the directory to the Docker volume for the training container. In Pipe input mode, Amazon SageMaker streams data directly from Amazon S3 to the container.
      
      If you specify File mode, make sure that you provision the storage volume that is attached to the training instance with enough capacity to accommodate the training data downloaded from Amazon S3, the model artifacts, and intermediate information.
      
      For more information about input modes, see Algorithms.
    - metricDefinitions
```
List<E> metricDefinitions
```
      An array of objects that specify the metrics that the algorithm emits.
- Class com.amazonaws.services.sagemaker.model.HyperParameterTrainingJobDefinition extends Object implements Serializable
  - Serialized Fields
    - staticHyperParameters
```
Map<K,V> staticHyperParameters
```
      Specifies the values of hyperparameters that do not change for the tuning job.
    - algorithmSpecification
```
HyperParameterAlgorithmSpecification algorithmSpecification
```
      The object that specifies the algorithm to use for the training jobs that the tuning job launches.
    - roleArn
```
String roleArn
```
      The Amazon Resource Name (ARN) of the IAM role associated with the training jobs that the tuning job launches.
    - inputDataConfig
```
List<E> inputDataConfig
```
      An array of objects that specify the input for the training jobs that the tuning job launches.
    - vpcConfig
```
VpcConfig vpcConfig
```
      The object that specifies the VPC that you want the training jobs that this hyperparameter tuning job launches to connect to. Control access to and from your training container by configuring the VPC. For more information, see train-vpc.
    - outputDataConfig
```
OutputDataConfig outputDataConfig
```
      Specifies the path to the Amazon S3 bucket where you store model artifacts from the training jobs that the tuning job launches.
    - resourceConfig
```
ResourceConfig resourceConfig
```
      The resources, including the compute instances and storage volumes, to use for the training jobs that the tuning job launches.
      
      Storage volumes store model artifacts and incremental states. Training algorithms might also use storage volumes for scratch space. If you want Amazon SageMaker to use the storage volume to store the training data, choose File as the TrainingInputMode in the algorithm specification. For distributed training algorithms, specify an instance count greater than 1.
    - stoppingCondition
```
StoppingCondition stoppingCondition
```
      Sets a maximum duration for the training jobs that the tuning job launches. Use this parameter to limit model training costs.
      
      To stop a job, Amazon SageMaker sends the algorithm the SIGTERM signal. This delays job termination for 120 seconds. Algorithms might use this 120-second window to save the model artifacts.
      
      When Amazon SageMaker terminates a job because the stopping condition has been met, training algorithms provided by Amazon SageMaker save the intermediate results of the job.
- Class com.amazonaws.services.sagemaker.model.HyperParameterTrainingJobSummary extends Object implements Serializable
  - Serialized Fields
    - trainingJobName
```
String trainingJobName
```
      The name of the training job.
    - trainingJobArn
```
String trainingJobArn
```
      The Amazon Resource Name (ARN) of the training job.
    - creationTime
```
Date creationTime
```
      The date and time that the training job was created.
    - trainingStartTime
```
Date trainingStartTime
```
      The date and time that the training job started.
    - trainingEndTime
```
Date trainingEndTime
```
      The date and time that the training job ended.
    - trainingJobStatus
```
String trainingJobStatus
```
      The status of the training job.
    - tunedHyperParameters
```
Map<K,V> tunedHyperParameters
```
      A list of the hyperparameters for which you specified ranges to search.
    - failureReason
```
String failureReason
```
      The reason that the
    - finalHyperParameterTuningJobObjectiveMetric
```
FinalHyperParameterTuningJobObjectiveMetric finalHyperParameterTuningJobObjectiveMetric
```
      The object that specifies the value of the objective metric of the tuning job that launched this training job.
    - objectiveStatus
```
String objectiveStatus
```
      The status of the objective metric for the training job:
      
      Succeeded: The final objective metric for the training job was evaluated by the hyperparameter tuning job and used in the hyperparameter tuning process.
      
      Pending: The training job is in progress and evaluation of its final objective metric is pending.
      
      Failed: The final objective metric for the training job was not evaluated, and was not used in the hyperparameter tuning process. This typically occurs when the training job failed or did not emit an objective metric.
- Class com.amazonaws.services.sagemaker.model.HyperParameterTuningJobConfig extends Object implements Serializable
  - Serialized Fields
    - strategy
```
String strategy
```
      Specifies the search strategy for hyperparameters. Currently, the only valid value is Bayesian.
    - hyperParameterTuningJobObjective
```
HyperParameterTuningJobObjective hyperParameterTuningJobObjective
```
      The object that specifies the objective metric for this tuning job.
    - resourceLimits
```
ResourceLimits resourceLimits
```
      The object that specifies the maximum number of training jobs and parallel training jobs for this tuning job.
    - parameterRanges
```
ParameterRanges parameterRanges
```
      The object that specifies the ranges of hyperparameters that this tuning job searches.
- Class com.amazonaws.services.sagemaker.model.HyperParameterTuningJobObjective extends Object implements Serializable
  - Serialized Fields
    - type
```
String type
```
      Whether to minimize or maximize the objective metric.
    - metricName
```
String metricName
```
      The name of the metric to use for the objective metric.
- Class com.amazonaws.services.sagemaker.model.HyperParameterTuningJobSummary extends Object implements Serializable
  - Serialized Fields
    - hyperParameterTuningJobName
```
String hyperParameterTuningJobName
```
      The name of the tuning job.
    - hyperParameterTuningJobArn
```
String hyperParameterTuningJobArn
```
      The Amazon Resource Name (ARN) of the tuning job.
    - hyperParameterTuningJobStatus
```
String hyperParameterTuningJobStatus
```
      The status of the tuning job.
    - strategy
```
String strategy
```
      Specifies the search strategy hyperparameter tuning uses to choose which hyperparameters to use for each iteration. Currently, the only valid value is Bayesian.
    - creationTime
```
Date creationTime
```
      The date and time that the tuning job was created.
    - hyperParameterTuningEndTime
```
Date hyperParameterTuningEndTime
```
      The date and time that the tuning job ended.
    - lastModifiedTime
```
Date lastModifiedTime
```
      The date and time that the tuning job was modified.
    - trainingJobStatusCounters
```
TrainingJobStatusCounters trainingJobStatusCounters
```
      The object that specifies the numbers of training jobs, categorized by status, that this tuning job launched.
    - objectiveStatusCounters
```
ObjectiveStatusCounters objectiveStatusCounters
```
      The object that specifies the numbers of training jobs, categorized by objective metric status, that this tuning job launched.
    - resourceLimits
```
ResourceLimits resourceLimits
```
      The object that specifies the maximum number of training jobs and parallel training jobs allowed for this tuning job.
- Class com.amazonaws.services.sagemaker.model.IntegerParameterRange extends Object implements Serializable
  - Serialized Fields
    - name
```
String name
```
      The name of the hyperparameter to search.
    - minValue
```
String minValue
```
      The minimum value of the hyperparameter to search.
    - maxValue
```
String maxValue
```
      The maximum value of the hyperparameter to search.
- Class com.amazonaws.services.sagemaker.model.ListEndpointConfigsRequest extends AmazonWebServiceRequest implements Serializable
  - Serialized Fields
    - sortBy
```
String sortBy
```
      The field to sort results by. The default is CreationTime.
    - sortOrder
```
String sortOrder
```
      The sort order for results. The default is Ascending.
    - nextToken
```
String nextToken
```
      If the result of the previous ListEndpointConfig request was truncated, the response includes a NextToken. To retrieve the next set of endpoint configurations, use the token in the next request.
    - maxResults
```
Integer maxResults
```
      The maximum number of training jobs to return in the response.
    - nameContains
```
String nameContains
```
      A string in the endpoint configuration name. This filter returns only endpoint configurations whose name contains the specified string.
    - creationTimeBefore
```
Date creationTimeBefore
```
      A filter that returns only endpoint configurations created before the specified time (timestamp).
    - creationTimeAfter
```
Date creationTimeAfter
```
      A filter that returns only endpoint configurations created after the specified time (timestamp).
- Class com.amazonaws.services.sagemaker.model.ListEndpointConfigsResult extends AmazonWebServiceResult<ResponseMetadata> implements Serializable
  - Serialized Fields
    - endpointConfigs
```
List<E> endpointConfigs
```
      An array of endpoint configurations.
    - nextToken
```
String nextToken
```
      If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of endpoint configurations, use it in the subsequent request
- Class com.amazonaws.services.sagemaker.model.ListEndpointsRequest extends AmazonWebServiceRequest implements Serializable
  - Serialized Fields
    - sortBy
```
String sortBy
```
      Sorts the list of results. The default is CreationTime.
    - sortOrder
```
String sortOrder
```
      The sort order for results. The default is Ascending.
    - nextToken
```
String nextToken
```
      If the result of a ListEndpoints request was truncated, the response includes a NextToken. To retrieve the next set of endpoints, use the token in the next request.
    - maxResults
```
Integer maxResults
```
      The maximum number of endpoints to return in the response.
    - nameContains
```
String nameContains
```
      A string in endpoint names. This filter returns only endpoints whose name contains the specified string.
    - creationTimeBefore
```
Date creationTimeBefore
```
      A filter that returns only endpoints that were created before the specified time (timestamp).
    - creationTimeAfter
```
Date creationTimeAfter
```
      A filter that returns only endpoints that were created after the specified time (timestamp).
    - lastModifiedTimeBefore
```
Date lastModifiedTimeBefore
```
      A filter that returns only endpoints that were modified before the specified timestamp.
    - lastModifiedTimeAfter
```
Date lastModifiedTimeAfter
```
      A filter that returns only endpoints that were modified after the specified timestamp.
    - statusEquals
```
String statusEquals
```
      A filter that returns only endpoints with the specified status.
- Class com.amazonaws.services.sagemaker.model.ListEndpointsResult extends AmazonWebServiceResult<ResponseMetadata> implements Serializable
  - Serialized Fields
    - endpoints
```
List<E> endpoints
```
      An array or endpoint objects.
    - nextToken
```
String nextToken
```
      If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of training jobs, use it in the subsequent request.
- Class com.amazonaws.services.sagemaker.model.ListHyperParameterTuningJobsRequest extends AmazonWebServiceRequest implements Serializable
  - Serialized Fields
    - nextToken
```
String nextToken
```
      If the result of the previous ListHyperParameterTuningJobs request was truncated, the response includes a NextToken. To retrieve the next set of tuning jobs, use the token in the next request.
    - maxResults
```
Integer maxResults
```
      The maximum number of tuning jobs to return.
    - sortBy
```
String sortBy
```
      The field to sort results by. The default is Name.
    - sortOrder
```
String sortOrder
```
      The sort order for results. The default is Ascending.
    - nameContains
```
String nameContains
```
      A string in the tuning job name. This filter returns only tuning jobs whose name contains the specified string.
    - creationTimeAfter
```
Date creationTimeAfter
```
      A filter that returns only tuning jobs that were created after the specified time.
    - creationTimeBefore
```
Date creationTimeBefore
```
      A filter that returns only tuning jobs that were created before the specified time.
    - lastModifiedTimeAfter
```
Date lastModifiedTimeAfter
```
      A filter that returns only tuning jobs that were modified after the specified time.
    - lastModifiedTimeBefore
```
Date lastModifiedTimeBefore
```
      A filter that returns only tuning jobs that were modified before the specified time.
    - statusEquals
```
String statusEquals
```
      A filter that returns only tuning jobs with the specified status.
- Class com.amazonaws.services.sagemaker.model.ListHyperParameterTuningJobsResult extends AmazonWebServiceResult<ResponseMetadata> implements Serializable
  - Serialized Fields
    - hyperParameterTuningJobSummaries
```
List<E> hyperParameterTuningJobSummaries
```
      A list of objects that describe the tuning jobs that the ListHyperParameterTuningJobs request returned.
    - nextToken
```
String nextToken
```
      If the result of this ListHyperParameterTuningJobs request was truncated, the response includes a NextToken. To retrieve the next set of tuning jobs, use the token in the next request.
- Class com.amazonaws.services.sagemaker.model.ListModelsRequest extends AmazonWebServiceRequest implements Serializable
  - Serialized Fields
    - sortBy
```
String sortBy
```
      Sorts the list of results. The default is CreationTime.
    - sortOrder
```
String sortOrder
```
      The sort order for results. The default is Ascending.
    - nextToken
```
String nextToken
```
      If the response to a previous ListModels request was truncated, the response includes a NextToken. To retrieve the next set of models, use the token in the next request.
    - maxResults
```
Integer maxResults
```
      The maximum number of models to return in the response.
    - nameContains
```
String nameContains
```
      A string in the training job name. This filter returns only models in the training job whose name contains the specified string.
    - creationTimeBefore
```
Date creationTimeBefore
```
      A filter that returns only models created before the specified time (timestamp).
    - creationTimeAfter
```
Date creationTimeAfter
```
      A filter that returns only models created after the specified time (timestamp).
- Class com.amazonaws.services.sagemaker.model.ListModelsResult extends AmazonWebServiceResult<ResponseMetadata> implements Serializable
  - Serialized Fields
    - models
```
List<E> models
```
      An array of ModelSummary objects, each of which lists a model.
    - nextToken
```
String nextToken
```
      If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of models, use it in the subsequent request.
- Class com.amazonaws.services.sagemaker.model.ListNotebookInstanceLifecycleConfigsRequest extends AmazonWebServiceRequest implements Serializable
  - Serialized Fields
    - nextToken
```
String nextToken
```
      If the result of a ListNotebookInstanceLifecycleConfigs request was truncated, the response includes a NextToken. To get the next set of lifecycle configurations, use the token in the next request.
    - maxResults
```
Integer maxResults
```
      The maximum number of lifecycle configurations to return in the response.
    - sortBy
```
String sortBy
```
      Sorts the list of results. The default is CreationTime.
    - sortOrder
```
String sortOrder
```
      The sort order for results.
    - nameContains
```
String nameContains
```
      A string in the lifecycle configuration name. This filter returns only lifecycle configurations whose name contains the specified string.
    - creationTimeBefore
```
Date creationTimeBefore
```
      A filter that returns only lifecycle configurations that were created before the specified time (timestamp).
    - creationTimeAfter
```
Date creationTimeAfter
```
      A filter that returns only lifecycle configurations that were created after the specified time (timestamp).
    - lastModifiedTimeBefore
```
Date lastModifiedTimeBefore
```
      A filter that returns only lifecycle configurations that were modified before the specified time (timestamp).
    - lastModifiedTimeAfter
```
Date lastModifiedTimeAfter
```
      A filter that returns only lifecycle configurations that were modified after the specified time (timestamp).
- Class com.amazonaws.services.sagemaker.model.ListNotebookInstanceLifecycleConfigsResult extends AmazonWebServiceResult<ResponseMetadata> implements Serializable
  - Serialized Fields
    - nextToken
```
String nextToken
```
      If the response is truncated, Amazon SageMaker returns this token. To get the next set of lifecycle configurations, use it in the next request.
    - notebookInstanceLifecycleConfigs
```
List<E> notebookInstanceLifecycleConfigs
```
      An array of NotebookInstanceLifecycleConfiguration objects, each listing a lifecycle configuration.
- Class com.amazonaws.services.sagemaker.model.ListNotebookInstancesRequest extends AmazonWebServiceRequest implements Serializable
  - Serialized Fields
    - nextToken
```
String nextToken
```
      If the previous call to the ListNotebookInstances is truncated, the response includes a NextToken. You can use this token in your subsequent ListNotebookInstances request to fetch the next set of notebook instances.
      
      You might specify a filter or a sort order in your request. When response is truncated, you must use the same values for the filer and sort order in the next request.
    - maxResults
```
Integer maxResults
```
      The maximum number of notebook instances to return.
    - sortBy
```
String sortBy
```
      The field to sort results by. The default is Name.
    - sortOrder
```
String sortOrder
```
      The sort order for results.
    - nameContains
```
String nameContains
```
      A string in the notebook instances' name. This filter returns only notebook instances whose name contains the specified string.
    - creationTimeBefore
```
Date creationTimeBefore
```
      A filter that returns only notebook instances that were created before the specified time (timestamp).
    - creationTimeAfter
```
Date creationTimeAfter
```
      A filter that returns only notebook instances that were created after the specified time (timestamp).
    - lastModifiedTimeBefore
```
Date lastModifiedTimeBefore
```
      A filter that returns only notebook instances that were modified before the specified time (timestamp).
    - lastModifiedTimeAfter
```
Date lastModifiedTimeAfter
```
      A filter that returns only notebook instances that were modified after the specified time (timestamp).
    - statusEquals
```
String statusEquals
```
      A filter that returns only notebook instances with the specified status.
    - notebookInstanceLifecycleConfigNameContains
```
String notebookInstanceLifecycleConfigNameContains
```
      A string in the name of a notebook instances lifecycle configuration associated with this notebook instance. This filter returns only notebook instances associated with a lifecycle configuration with a name that contains the specified string.
- Class com.amazonaws.services.sagemaker.model.ListNotebookInstancesResult extends AmazonWebServiceResult<ResponseMetadata> implements Serializable
  - Serialized Fields
    - nextToken
```
String nextToken
```
      If the response to the previous ListNotebookInstances request was truncated, Amazon SageMaker returns this token. To retrieve the next set of notebook instances, use the token in the next request.
    - notebookInstances
```
List<E> notebookInstances
```
      An array of NotebookInstanceSummary objects, one for each notebook instance.
- Class com.amazonaws.services.sagemaker.model.ListTagsRequest extends AmazonWebServiceRequest implements Serializable
  - Serialized Fields
    - resourceArn
```
String resourceArn
```
      The Amazon Resource Name (ARN) of the resource whose tags you want to retrieve.
    - nextToken
```
String nextToken
```
      If the response to the previous ListTags request is truncated, Amazon SageMaker returns this token. To retrieve the next set of tags, use it in the subsequent request.
    - maxResults
```
Integer maxResults
```
      Maximum number of tags to return.
- Class com.amazonaws.services.sagemaker.model.ListTagsResult extends AmazonWebServiceResult<ResponseMetadata> implements Serializable
  - Serialized Fields
    - tags
```
List<E> tags
```
      An array of Tag objects, each with a tag key and a value.
    - nextToken
```
String nextToken
```
      If response is truncated, Amazon SageMaker includes a token in the response. You can use this token in your subsequent request to fetch next set of tokens.
- Class com.amazonaws.services.sagemaker.model.ListTrainingJobsForHyperParameterTuningJobRequest extends AmazonWebServiceRequest implements Serializable
  - Serialized Fields
    - hyperParameterTuningJobName
```
String hyperParameterTuningJobName
```
      The name of the tuning job whose training jobs you want to list.
    - nextToken
```
String nextToken
```
      If the result of the previous ListTrainingJobsForHyperParameterTuningJob request was truncated, the response includes a NextToken. To retrieve the next set of training jobs, use the token in the next request.
    - maxResults
```
Integer maxResults
```
      The maximum number of training jobs to return.
    - statusEquals
```
String statusEquals
```
      A filter that returns only training jobs with the specified status.
    - sortBy
```
String sortBy
```
      The field to sort results by. The default is Name.
    - sortOrder
```
String sortOrder
```
      The sort order for results. The default is Ascending.
- Class com.amazonaws.services.sagemaker.model.ListTrainingJobsForHyperParameterTuningJobResult extends AmazonWebServiceResult<ResponseMetadata> implements Serializable
  - Serialized Fields
    - trainingJobSummaries
```
List<E> trainingJobSummaries
```
      A list of objects that describe the training jobs that the ListTrainingJobsForHyperParameterTuningJob request returned.
    - nextToken
```
String nextToken
```
      If the result of this ListTrainingJobsForHyperParameterTuningJob request was truncated, the response includes a NextToken. To retrieve the next set of training jobs, use the token in the next request.
- Class com.amazonaws.services.sagemaker.model.ListTrainingJobsRequest extends AmazonWebServiceRequest implements Serializable
  - Serialized Fields
    - nextToken
```
String nextToken
```
      If the result of the previous ListTrainingJobs request was truncated, the response includes a NextToken. To retrieve the next set of training jobs, use the token in the next request.
    - maxResults
```
Integer maxResults
```
      The maximum number of training jobs to return in the response.
    - creationTimeAfter
```
Date creationTimeAfter
```
      A filter that only training jobs created after the specified time (timestamp).
    - creationTimeBefore
```
Date creationTimeBefore
```
      A filter that returns only training jobs created before the specified time (timestamp).
    - lastModifiedTimeAfter
```
Date lastModifiedTimeAfter
```
      A filter that returns only training jobs modified after the specified time (timestamp).
    - lastModifiedTimeBefore
```
Date lastModifiedTimeBefore
```
      A filter that returns only training jobs modified before the specified time (timestamp).
    - nameContains
```
String nameContains
```
      A string in the training job name. This filter returns only training jobs whose name contains the specified string.
    - statusEquals
```
String statusEquals
```
      A filter that retrieves only training jobs with a specific status.
    - sortBy
```
String sortBy
```
      The field to sort results by. The default is CreationTime.
    - sortOrder
```
String sortOrder
```
      The sort order for results. The default is Ascending.
- Class com.amazonaws.services.sagemaker.model.ListTrainingJobsResult extends AmazonWebServiceResult<ResponseMetadata> implements Serializable
  - Serialized Fields
    - trainingJobSummaries
```
List<E> trainingJobSummaries
```
      An array of TrainingJobSummary objects, each listing a training job.
    - nextToken
```
String nextToken
```
      If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of training jobs, use it in the subsequent request.
- Class com.amazonaws.services.sagemaker.model.MetricDefinition extends Object implements Serializable
  - Serialized Fields
    - name
```
String name
```
      The name of the metric.
    - regex
```
String regex
```
      A regular expression that searches the output of a training job and gets the value of the metric. For more information about using regular expressions to define metrics, see hpo-define-metrics.
- Class com.amazonaws.services.sagemaker.model.ModelArtifacts extends Object implements Serializable
  - Serialized Fields
    - s3ModelArtifacts
```
String s3ModelArtifacts
```
      The path of the S3 object that contains the model artifacts. For example, s3://bucket-name/keynameprefix/model.tar.gz.
- Class com.amazonaws.services.sagemaker.model.ModelSummary extends Object implements Serializable
  - Serialized Fields
    - modelName
```
String modelName
```
      The name of the model that you want a summary for.
    - modelArn
```
String modelArn
```
      The Amazon Resource Name (ARN) of the model.
    - creationTime
```
Date creationTime
```
      A timestamp that indicates when the model was created.
- Class com.amazonaws.services.sagemaker.model.NotebookInstanceLifecycleConfigSummary extends Object implements Serializable
  - Serialized Fields
    - notebookInstanceLifecycleConfigName
```
String notebookInstanceLifecycleConfigName
```
      The name of the lifecycle configuration.
    - notebookInstanceLifecycleConfigArn
```
String notebookInstanceLifecycleConfigArn
```
      The Amazon Resource Name (ARN) of the lifecycle configuration.
    - creationTime
```
Date creationTime
```
      A timestamp that tells when the lifecycle configuration was created.
    - lastModifiedTime
```
Date lastModifiedTime
```
      A timestamp that tells when the lifecycle configuration was last modified.
- Class com.amazonaws.services.sagemaker.model.NotebookInstanceLifecycleHook extends Object implements Serializable
  - Serialized Fields
    - content
```
String content
```
      A base64-encoded string that contains a shell script for a notebook instance lifecycle configuration.
- Class com.amazonaws.services.sagemaker.model.NotebookInstanceSummary extends Object implements Serializable
  - Serialized Fields
    - notebookInstanceName
```
String notebookInstanceName
```
      The name of the notebook instance that you want a summary for.
    - notebookInstanceArn
```
String notebookInstanceArn
```
      The Amazon Resource Name (ARN) of the notebook instance.
    - notebookInstanceStatus
```
String notebookInstanceStatus
```
      The status of the notebook instance.
    - url
```
String url
```
      The URL that you use to connect to the Jupyter instance running in your notebook instance.
    - instanceType
```
String instanceType
```
      The type of ML compute instance that the notebook instance is running on.
    - creationTime
```
Date creationTime
```
      A timestamp that shows when the notebook instance was created.
    - lastModifiedTime
```
Date lastModifiedTime
```
      A timestamp that shows when the notebook instance was last modified.
    - notebookInstanceLifecycleConfigName
```
String notebookInstanceLifecycleConfigName
```
      The name of a notebook instance lifecycle configuration associated with this notebook instance.
      
      For information about notebook instance lifestyle configurations, see notebook-lifecycle-config.
- Class com.amazonaws.services.sagemaker.model.ObjectiveStatusCounters extends Object implements Serializable
  - Serialized Fields
    - succeeded
```
Integer succeeded
```
      The number of training jobs whose final objective metric was evaluated by the hyperparameter tuning job and used in the hyperparameter tuning process.
    - pending
```
Integer pending
```
      The number of training jobs that are in progress and pending evaluation of their final objective metric.
    - failed
```
Integer failed
```
      The number of training jobs whose final objective metric was not evaluated and used in the hyperparameter tuning process. This typically occurs when the training job failed or did not emit an objective metric.
- Class com.amazonaws.services.sagemaker.model.OutputDataConfig extends Object implements Serializable
  - Serialized Fields
    - kmsKeyId
```
String kmsKeyId
```
      The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption.
      
      If you don't provide the KMS key ID, Amazon SageMaker uses the default KMS key for Amazon S3 for your role's account. For more information, see KMS-Managed Encryption Keys in Amazon Simple Storage Service developer guide.
      
      The KMS key policy must grant permission to the IAM role you specify in your CreateTrainingJob request. Using Key Policies in AWS KMS in the AWS Key Management Service Developer Guide.
    - s3OutputPath
```
String s3OutputPath
```
      Identifies the S3 path where you want Amazon SageMaker to store the model artifacts. For example, s3://bucket-name/key-name-prefix.
- Class com.amazonaws.services.sagemaker.model.ParameterRanges extends Object implements Serializable
  - Serialized Fields
    - integerParameterRanges
```
List<E> integerParameterRanges
```
      The array of IntegerParameterRange objects that specify ranges of integer hyperparameters that a hyperparameter tuning job searches.
    - continuousParameterRanges
```
List<E> continuousParameterRanges
```
      The array of ContinuousParameterRange objects that specify ranges of continuous hyperparameters that a hyperparameter tuning job searches.
    - categoricalParameterRanges
```
List<E> categoricalParameterRanges
```
      The array of CategoricalParameterRange objects that specify ranges of categorical hyperparameters that a hyperparameter tuning job searches.
- Class com.amazonaws.services.sagemaker.model.ProductionVariant extends Object implements Serializable
  - Serialized Fields
    - variantName
```
String variantName
```
      The name of the production variant.
    - modelName
```
String modelName
```
      The name of the model that you want to host. This is the name that you specified when creating the model.
    - initialInstanceCount
```
Integer initialInstanceCount
```
      Number of instances to launch initially.
    - instanceType
```
String instanceType
```
      The ML compute instance type.
    - initialVariantWeight
```
Float initialVariantWeight
```
      Determines initial traffic distribution among all of the models that you specify in the endpoint configuration. The traffic to a production variant is determined by the ratio of the VariantWeight to the sum of all VariantWeight values across all ProductionVariants. If unspecified, it defaults to 1.0.
- Class com.amazonaws.services.sagemaker.model.ProductionVariantSummary extends Object implements Serializable
  - Serialized Fields
    - variantName
```
String variantName
```
      The name of the variant.
    - currentWeight
```
Float currentWeight
```
      The weight associated with the variant.
    - desiredWeight
```
Float desiredWeight
```
      The requested weight, as specified in the UpdateEndpointWeightsAndCapacities request.
    - currentInstanceCount
```
Integer currentInstanceCount
```
      The number of instances associated with the variant.
    - desiredInstanceCount
```
Integer desiredInstanceCount
```
      The number of instances requested in the UpdateEndpointWeightsAndCapacities request.
- Class com.amazonaws.services.sagemaker.model.ResourceConfig extends Object implements Serializable
  - Serialized Fields
    - instanceType
```
String instanceType
```
      The ML compute instance type.
    - instanceCount
```
Integer instanceCount
```
      The number of ML compute instances to use. For distributed training, provide a value greater than 1.
    - volumeSizeInGB
```
Integer volumeSizeInGB
```
      The size of the ML storage volume that you want to provision.
      
      ML storage volumes store model artifacts and incremental states. Training algorithms might also use the ML storage volume for scratch space. If you want to store the training data in the ML storage volume, choose File as the TrainingInputMode in the algorithm specification.
      
      You must specify sufficient ML storage for your scenario.
      
      Amazon SageMaker supports only the General Purpose SSD (gp2) ML storage volume type.
    - volumeKmsKeyId
```
String volumeKmsKeyId
```
      The Amazon Resource Name (ARN) of a AWS Key Management Service key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the training job.
- Class com.amazonaws.services.sagemaker.model.ResourceInUseException extends AmazonSageMakerException implements Serializable
  
  serialVersionUID:
  
  1L
- Class com.amazonaws.services.sagemaker.model.ResourceLimitExceededException extends AmazonSageMakerException implements Serializable
  
  serialVersionUID:
  
  1L
- Class com.amazonaws.services.sagemaker.model.ResourceLimits extends Object implements Serializable
  - Serialized Fields
    - maxNumberOfTrainingJobs
```
Integer maxNumberOfTrainingJobs
```
      The maximum number of training jobs that a hyperparameter tuning job can launch.
    - maxParallelTrainingJobs
```
Integer maxParallelTrainingJobs
```
      The maximum number of concurrent training jobs that a hyperparameter tuning job can launch.
- Class com.amazonaws.services.sagemaker.model.ResourceNotFoundException extends AmazonSageMakerException implements Serializable
  
  serialVersionUID:
  
  1L
- Class com.amazonaws.services.sagemaker.model.S3DataSource extends Object implements Serializable
  - Serialized Fields
    - s3DataType
```
String s3DataType
```
      If you choose S3Prefix, S3Uri identifies a key name prefix. Amazon SageMaker uses all objects with the specified key name prefix for model training.
      
      If you choose ManifestFile, S3Uri identifies an object that is a manifest file containing a list of object keys that you want Amazon SageMaker to use for model training.
    - s3Uri
```
String s3Uri
```
      Depending on the value specified for the S3DataType, identifies either a key name prefix or a manifest. For example:
      
      A key name prefix might look like this: s3://bucketname/exampleprefix.
      
      A manifest might look like this: s3://bucketname/example.manifest
      
      The manifest is an S3 object which is a JSON file with the following format:
      
      [
      
      {"prefix": "s3://customer_bucket/some/prefix/"},
      
      "relative/path/to/custdata-1",
      
      "relative/path/custdata-2",
      
      ...
      
      ]
      
      The preceding JSON matches the following s3Uris:
      
      s3://customer_bucket/some/prefix/relative/path/to/custdata-1
      
      s3://customer_bucket/some/prefix/relative/path/custdata-1
      
      ...
      
      The complete set of s3uris in this manifest constitutes the input data for the channel for this datasource. The object that each s3uris points to must readable by the IAM role that Amazon SageMaker uses to perform tasks on your behalf.
    - s3DataDistributionType
```
String s3DataDistributionType
```
      If you want Amazon SageMaker to replicate the entire dataset on each ML compute instance that is launched for model training, specify FullyReplicated.
      
      If you want Amazon SageMaker to replicate a subset of data on each ML compute instance that is launched for model training, specify ShardedByS3Key. If there are n ML compute instances launched for a training job, each instance gets approximately 1/n of the number of S3 objects. In this case, model training on each machine uses only the subset of training data.
      
      Don't choose more ML compute instances for training than available S3 objects. If you do, some nodes won't get any data and you will pay for nodes that aren't getting any training data. This applies in both FILE and PIPE modes. Keep this in mind when developing algorithms.
      
      In distributed training, where you use multiple ML compute EC2 instances, you might choose ShardedByS3Key. If the algorithm requires copying training data to the ML storage volume (when TrainingInputMode is set to File), this copies 1/n of the number of objects.
- Class com.amazonaws.services.sagemaker.model.StartNotebookInstanceRequest extends AmazonWebServiceRequest implements Serializable
  - Serialized Fields
    - notebookInstanceName
```
String notebookInstanceName
```
      The name of the notebook instance to start.
- Class com.amazonaws.services.sagemaker.model.StartNotebookInstanceResult extends AmazonWebServiceResult<ResponseMetadata> implements Serializable
- Class com.amazonaws.services.sagemaker.model.StopHyperParameterTuningJobRequest extends AmazonWebServiceRequest implements Serializable
  - Serialized Fields
    - hyperParameterTuningJobName
```
String hyperParameterTuningJobName
```
      The name of the tuning job to stop.
- Class com.amazonaws.services.sagemaker.model.StopHyperParameterTuningJobResult extends AmazonWebServiceResult<ResponseMetadata> implements Serializable
- Class com.amazonaws.services.sagemaker.model.StopNotebookInstanceRequest extends AmazonWebServiceRequest implements Serializable
  - Serialized Fields
    - notebookInstanceName
```
String notebookInstanceName
```
      The name of the notebook instance to terminate.
- Class com.amazonaws.services.sagemaker.model.StopNotebookInstanceResult extends AmazonWebServiceResult<ResponseMetadata> implements Serializable
- Class com.amazonaws.services.sagemaker.model.StoppingCondition extends Object implements Serializable
  - Serialized Fields
    - maxRuntimeInSeconds
```
Integer maxRuntimeInSeconds
```
      The maximum length of time, in seconds, that the training job can run. If model training does not complete during this time, Amazon SageMaker ends the job. If value is not specified, default value is 1 day. Maximum value is 5 days.
- Class com.amazonaws.services.sagemaker.model.StopTrainingJobRequest extends AmazonWebServiceRequest implements Serializable
  - Serialized Fields
    - trainingJobName
```
String trainingJobName
```
      The name of the training job to stop.
- Class com.amazonaws.services.sagemaker.model.StopTrainingJobResult extends AmazonWebServiceResult<ResponseMetadata> implements Serializable
- Class com.amazonaws.services.sagemaker.model.Tag extends Object implements Serializable
  - Serialized Fields
    - key
```
String key
```
      The tag key.
    - value
```
String value
```
      The tag value.
- Class com.amazonaws.services.sagemaker.model.TrainingJobStatusCounters extends Object implements Serializable
  - Serialized Fields
    - completed
```
Integer completed
```
      The number of completed training jobs launched by a hyperparameter tuning job.
    - inProgress
```
Integer inProgress
```
      The number of in-progress training jobs launched by a hyperparameter tuning job.
    - retryableError
```
Integer retryableError
```
      The number of training jobs that failed, but can be retried. A failed training job can be retried only if it failed because an internal service error occurred.
    - nonRetryableError
```
Integer nonRetryableError
```
      The number of training jobs that failed and can't be retried. A failed training job can't be retried if it failed because a client error occurred.
    - stopped
```
Integer stopped
```
      The number of training jobs launched by a hyperparameter tuning job that were manually stopped.
- Class com.amazonaws.services.sagemaker.model.TrainingJobSummary extends Object implements Serializable
  - Serialized Fields
    - trainingJobName
```
String trainingJobName
```
      The name of the training job that you want a summary for.
    - trainingJobArn
```
String trainingJobArn
```
      The Amazon Resource Name (ARN) of the training job.
    - creationTime
```
Date creationTime
```
      A timestamp that shows when the training job was created.
    - trainingEndTime
```
Date trainingEndTime
```
      A timestamp that shows when the training job ended. This field is set only if the training job has one of the terminal statuses (Completed, Failed, or Stopped).
    - lastModifiedTime
```
Date lastModifiedTime
```
      Timestamp when the training job was last modified.
    - trainingJobStatus
```
String trainingJobStatus
```
      The status of the training job.
- Class com.amazonaws.services.sagemaker.model.UpdateEndpointRequest extends AmazonWebServiceRequest implements Serializable
  - Serialized Fields
    - endpointName
```
String endpointName
```
      The name of the endpoint whose configuration you want to update.
    - endpointConfigName
```
String endpointConfigName
```
      The name of the new endpoint configuration.
- Class com.amazonaws.services.sagemaker.model.UpdateEndpointResult extends AmazonWebServiceResult<ResponseMetadata> implements Serializable
  - Serialized Fields
    - endpointArn
```
String endpointArn
```
      The Amazon Resource Name (ARN) of the endpoint.
- Class com.amazonaws.services.sagemaker.model.UpdateEndpointWeightsAndCapacitiesRequest extends AmazonWebServiceRequest implements Serializable
  - Serialized Fields
    - endpointName
```
String endpointName
```
      The name of an existing Amazon SageMaker endpoint.
    - desiredWeightsAndCapacities
```
List<E> desiredWeightsAndCapacities
```
      An object that provides new capacity and weight values for a variant.
- Class com.amazonaws.services.sagemaker.model.UpdateEndpointWeightsAndCapacitiesResult extends AmazonWebServiceResult<ResponseMetadata> implements Serializable
  - Serialized Fields
    - endpointArn
```
String endpointArn
```
      The Amazon Resource Name (ARN) of the updated endpoint.
- Class com.amazonaws.services.sagemaker.model.UpdateNotebookInstanceLifecycleConfigRequest extends AmazonWebServiceRequest implements Serializable
  - Serialized Fields
    - notebookInstanceLifecycleConfigName
```
String notebookInstanceLifecycleConfigName
```
      The name of the lifecycle configuration.
    - onCreate
```
List<E> onCreate
```
      The shell script that runs only once, when you create a notebook instance
    - onStart
```
List<E> onStart
```
      The shell script that runs every time you start a notebook instance, including when you create the notebook instance.
- Class com.amazonaws.services.sagemaker.model.UpdateNotebookInstanceLifecycleConfigResult extends AmazonWebServiceResult<ResponseMetadata> implements Serializable
- Class com.amazonaws.services.sagemaker.model.UpdateNotebookInstanceRequest extends AmazonWebServiceRequest implements Serializable
  - Serialized Fields
    - notebookInstanceName
```
String notebookInstanceName
```
      The name of the notebook instance to update.
    - instanceType
```
String instanceType
```
      The Amazon ML compute instance type.
    - roleArn
```
String roleArn
```
      The Amazon Resource Name (ARN) of the IAM role that Amazon SageMaker can assume to access the notebook instance. For more information, see Amazon SageMaker Roles.
      
      To be able to pass this role to Amazon SageMaker, the caller of this API must have the iam:PassRole permission.
- Class com.amazonaws.services.sagemaker.model.UpdateNotebookInstanceResult extends AmazonWebServiceResult<ResponseMetadata> implements Serializable
- Class com.amazonaws.services.sagemaker.model.VpcConfig extends Object implements Serializable
  - Serialized Fields
    - securityGroupIds
```
List<E> securityGroupIds
```
      The VPC security group IDs, in the form sg-xxxxxxxx. Specify the security groups for the VPC that is specified in the Subnets field.
    - subnets
```
List<E> subnets
```
      The ID of the subnets in the VPC to which you want to connect your training job or model.

Serialized Form

Package com.amazonaws.services.sagemaker.model

Class com.amazonaws.services.sagemaker.model.AddTagsRequest extends AmazonWebServiceRequest implements Serializable

Serialized Fields

resourceArn

tags

Class com.amazonaws.services.sagemaker.model.AddTagsResult extends AmazonWebServiceResult<ResponseMetadata> implements Serializable

Serialized Fields

tags

Class com.amazonaws.services.sagemaker.model.AlgorithmSpecification extends Object implements Serializable

Serialized Fields

trainingImage

trainingInputMode

Class com.amazonaws.services.sagemaker.model.AmazonSageMakerException extends AmazonServiceException implements Serializable

Class com.amazonaws.services.sagemaker.model.CategoricalParameterRange extends Object implements Serializable

Serialized Fields

name

values

Class com.amazonaws.services.sagemaker.model.Channel extends Object implements Serializable

Serialized Fields

channelName

dataSource

contentType

compressionType

recordWrapperType

Class com.amazonaws.services.sagemaker.model.ContainerDefinition extends Object implements Serializable

Serialized Fields

containerHostname

image

modelDataUrl

environment

Class com.amazonaws.services.sagemaker.model.ContinuousParameterRange extends Object implements Serializable

Serialized Fields

name

minValue

maxValue

Class com.amazonaws.services.sagemaker.model.CreateEndpointConfigRequest extends AmazonWebServiceRequest implements Serializable

Serialized Fields

endpointConfigName

productionVariants

tags

kmsKeyId

Class com.amazonaws.services.sagemaker.model.CreateEndpointConfigResult extends AmazonWebServiceResult<ResponseMetadata> implements Serializable

Serialized Fields

endpointConfigArn

Class com.amazonaws.services.sagemaker.model.CreateEndpointRequest extends AmazonWebServiceRequest implements Serializable

Serialized Fields

endpointName

endpointConfigName

tags

Class com.amazonaws.services.sagemaker.model.CreateEndpointResult extends AmazonWebServiceResult<ResponseMetadata> implements Serializable

Serialized Fields

endpointArn

Class com.amazonaws.services.sagemaker.model.CreateHyperParameterTuningJobRequest extends AmazonWebServiceRequest implements Serializable

Serialized Fields

hyperParameterTuningJobName

hyperParameterTuningJobConfig

trainingJobDefinition

tags

Class com.amazonaws.services.sagemaker.model.CreateHyperParameterTuningJobResult extends AmazonWebServiceResult<ResponseMetadata> implements Serializable

Serialized Fields

hyperParameterTuningJobArn

Class com.amazonaws.services.sagemaker.model.CreateModelRequest extends AmazonWebServiceRequest implements Serializable

Serialized Fields

modelName

primaryContainer

executionRoleArn

tags

vpcConfig

Class com.amazonaws.services.sagemaker.model.CreateModelResult extends AmazonWebServiceResult<ResponseMetadata> implements Serializable

Serialized Fields

modelArn

Class com.amazonaws.services.sagemaker.model.CreateNotebookInstanceLifecycleConfigRequest extends AmazonWebServiceRequest implements Serializable

Serialized Fields

notebookInstanceLifecycleConfigName

onCreate

onStart

Class com.amazonaws.services.sagemaker.model.CreateNotebookInstanceLifecycleConfigResult extends AmazonWebServiceResult<ResponseMetadata> implements Serializable

Serialized Fields

notebookInstanceLifecycleConfigArn