Package software.amazon.awssdk.services.sagemaker.model

Interface DescribeTrainingJobResponse.Builder

    • Method Detail

      • trainingJobName

        DescribeTrainingJobResponse.Builder trainingJobName​(String trainingJobName)

        Name of the model training job.

        Parameters:
        trainingJobName - Name of the model training job.
        Returns:
        Returns a reference to this object so that method calls can be chained together.

      • trainingJobArn

        DescribeTrainingJobResponse.Builder trainingJobArn​(String trainingJobArn)

        The Amazon Resource Name (ARN) of the training job.

        Parameters:
        trainingJobArn - The Amazon Resource Name (ARN) of the training job.
        Returns:
        Returns a reference to this object so that method calls can be chained together.

      • tuningJobArn

        DescribeTrainingJobResponse.Builder 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.

        Parameters:
        tuningJobArn - The Amazon Resource Name (ARN) of the associated hyperparameter tuning job if the training job was launched by a hyperparameter tuning job.
        Returns:
        Returns a reference to this object so that method calls can be chained together.

      • labelingJobArn

        DescribeTrainingJobResponse.Builder labelingJobArn​(String labelingJobArn)

        The Amazon Resource Name (ARN) of the SageMaker Ground Truth labeling job that created the transform or training job.

        Parameters:
        labelingJobArn - The Amazon Resource Name (ARN) of the SageMaker Ground Truth labeling job that created the transform or training job.
        Returns:
        Returns a reference to this object so that method calls can be chained together.

      • autoMLJobArn

        DescribeTrainingJobResponse.Builder autoMLJobArn​(String autoMLJobArn)

        The Amazon Resource Name (ARN) of an AutoML job.

        Parameters:
        autoMLJobArn - The Amazon Resource Name (ARN) of an AutoML job.
        Returns:
        Returns a reference to this object so that method calls can be chained together.

      • modelArtifacts

        DescribeTrainingJobResponse.Builder modelArtifacts​(ModelArtifacts modelArtifacts)

        Information about the Amazon S3 location that is configured for storing model artifacts.

        Parameters:
        modelArtifacts - Information about the Amazon S3 location that is configured for storing model artifacts.
        Returns:
        Returns a reference to this object so that method calls can be chained together.

      • trainingJobStatus

        DescribeTrainingJobResponse.Builder trainingJobStatus​(String trainingJobStatus)

        The status of the training job.

        SageMaker provides the following training job statuses:

        • InProgress - The training is in progress.

        • Completed - The training job has completed.

        • Failed - The training job has failed. To see the reason for the failure, see the FailureReason field in the response to a DescribeTrainingJobResponse call.

        • Stopping - The training job is stopping.

        • Stopped - The training job has stopped.

        For more detailed information, see SecondaryStatus.

        Parameters:
        trainingJobStatus - The status of the training job.

        SageMaker provides the following training job statuses:

        • InProgress - The training is in progress.

        • Completed - The training job has completed.

        • Failed - The training job has failed. To see the reason for the failure, see the FailureReason field in the response to a DescribeTrainingJobResponse call.

        • Stopping - The training job is stopping.

        • Stopped - The training job has stopped.

        For more detailed information, see SecondaryStatus.

        Returns:
        Returns a reference to this object so that method calls can be chained together.
        See Also:
        TrainingJobStatus, TrainingJobStatus

      • trainingJobStatus

        DescribeTrainingJobResponse.Builder trainingJobStatus​(TrainingJobStatus trainingJobStatus)

        The status of the training job.

        SageMaker provides the following training job statuses:

        • InProgress - The training is in progress.

        • Completed - The training job has completed.

        • Failed - The training job has failed. To see the reason for the failure, see the FailureReason field in the response to a DescribeTrainingJobResponse call.

        • Stopping - The training job is stopping.

        • Stopped - The training job has stopped.

        For more detailed information, see SecondaryStatus.

        Parameters:
        trainingJobStatus - The status of the training job.

        SageMaker provides the following training job statuses:

        • InProgress - The training is in progress.

        • Completed - The training job has completed.

        • Failed - The training job has failed. To see the reason for the failure, see the FailureReason field in the response to a DescribeTrainingJobResponse call.

        • Stopping - The training job is stopping.

        • Stopped - The training job has stopped.

        For more detailed information, see SecondaryStatus.

        Returns:
        Returns a reference to this object so that method calls can be chained together.
        See Also:
        TrainingJobStatus, TrainingJobStatus

      • secondaryStatus

        DescribeTrainingJobResponse.Builder secondaryStatus​(String secondaryStatus)

        Provides detailed information about the state of the training job. For detailed information on the secondary status of the training job, see StatusMessage under SecondaryStatusTransition.

        SageMaker provides primary statuses and secondary statuses that apply to each of them:

        InProgress

        • Starting - Starting the training job.

        • Downloading - An optional stage for algorithms that support File training input mode. It indicates that data is being downloaded to the ML storage volumes.

        • Training - Training is in progress.

        • Interrupted - The job stopped because the managed spot training instances were interrupted.

        • Uploading - Training is complete and the model artifacts are being uploaded to the S3 location.

        Completed

        • Completed - The training job has completed.

        Failed

        • Failed - The training job has failed. The reason for the failure is returned in the FailureReason field of DescribeTrainingJobResponse.

        Stopped

        • MaxRuntimeExceeded - The job stopped because it exceeded the maximum allowed runtime.

        • MaxWaitTimeExceeded - The job stopped because it exceeded the maximum allowed wait time.

        • Stopped - The training job has stopped.

        Stopping

        • Stopping - Stopping the training job.

        Valid values for SecondaryStatus are subject to change.

        We no longer support the following secondary statuses:

        • LaunchingMLInstances

        • PreparingTraining

        • DownloadingTrainingImage

        Parameters:
        secondaryStatus - Provides detailed information about the state of the training job. For detailed information on the secondary status of the training job, see StatusMessage under SecondaryStatusTransition.

        SageMaker provides primary statuses and secondary statuses that apply to each of them:

        InProgress

        • Starting - Starting the training job.

        • Downloading - An optional stage for algorithms that support File training input mode. It indicates that data is being downloaded to the ML storage volumes.

        • Training - Training is in progress.

        • Interrupted - The job stopped because the managed spot training instances were interrupted.

        • Uploading - Training is complete and the model artifacts are being uploaded to the S3 location.

        Completed

        • Completed - The training job has completed.

        Failed

        • Failed - The training job has failed. The reason for the failure is returned in the FailureReason field of DescribeTrainingJobResponse.

        Stopped

        • MaxRuntimeExceeded - The job stopped because it exceeded the maximum allowed runtime.

        • MaxWaitTimeExceeded - The job stopped because it exceeded the maximum allowed wait time.

        • Stopped - The training job has stopped.

        Stopping

        • Stopping - Stopping the training job.

        Valid values for SecondaryStatus are subject to change.

        We no longer support the following secondary statuses:

        • LaunchingMLInstances

        • PreparingTraining

        • DownloadingTrainingImage

        Returns:
        Returns a reference to this object so that method calls can be chained together.
        See Also:
        SecondaryStatus, SecondaryStatus

      • secondaryStatus

        DescribeTrainingJobResponse.Builder secondaryStatus​(SecondaryStatus secondaryStatus)

        Provides detailed information about the state of the training job. For detailed information on the secondary status of the training job, see StatusMessage under SecondaryStatusTransition.

        SageMaker provides primary statuses and secondary statuses that apply to each of them:

        InProgress

        • Starting - Starting the training job.

        • Downloading - An optional stage for algorithms that support File training input mode. It indicates that data is being downloaded to the ML storage volumes.

        • Training - Training is in progress.

        • Interrupted - The job stopped because the managed spot training instances were interrupted.

        • Uploading - Training is complete and the model artifacts are being uploaded to the S3 location.

        Completed

        • Completed - The training job has completed.

        Failed

        • Failed - The training job has failed. The reason for the failure is returned in the FailureReason field of DescribeTrainingJobResponse.

        Stopped

        • MaxRuntimeExceeded - The job stopped because it exceeded the maximum allowed runtime.

        • MaxWaitTimeExceeded - The job stopped because it exceeded the maximum allowed wait time.

        • Stopped - The training job has stopped.

        Stopping

        • Stopping - Stopping the training job.

        Valid values for SecondaryStatus are subject to change.

        We no longer support the following secondary statuses:

        • LaunchingMLInstances

        • PreparingTraining

        • DownloadingTrainingImage

        Parameters:
        secondaryStatus - Provides detailed information about the state of the training job. For detailed information on the secondary status of the training job, see StatusMessage under SecondaryStatusTransition.

        SageMaker provides primary statuses and secondary statuses that apply to each of them:

        InProgress

        • Starting - Starting the training job.

        • Downloading - An optional stage for algorithms that support File training input mode. It indicates that data is being downloaded to the ML storage volumes.

        • Training - Training is in progress.

        • Interrupted - The job stopped because the managed spot training instances were interrupted.

        • Uploading - Training is complete and the model artifacts are being uploaded to the S3 location.

        Completed

        • Completed - The training job has completed.

        Failed

        • Failed - The training job has failed. The reason for the failure is returned in the FailureReason field of DescribeTrainingJobResponse.

        Stopped

        • MaxRuntimeExceeded - The job stopped because it exceeded the maximum allowed runtime.

        • MaxWaitTimeExceeded - The job stopped because it exceeded the maximum allowed wait time.

        • Stopped - The training job has stopped.

        Stopping

        • Stopping - Stopping the training job.

        Valid values for SecondaryStatus are subject to change.

        We no longer support the following secondary statuses:

        • LaunchingMLInstances

        • PreparingTraining

        • DownloadingTrainingImage

        Returns:
        Returns a reference to this object so that method calls can be chained together.
        See Also:
        SecondaryStatus, SecondaryStatus

      • failureReason

        DescribeTrainingJobResponse.Builder failureReason​(String failureReason)

        If the training job failed, the reason it failed.

        Parameters:
        failureReason - If the training job failed, the reason it failed.
        Returns:
        Returns a reference to this object so that method calls can be chained together.

      • hyperParameters

        DescribeTrainingJobResponse.Builder hyperParameters​(Map<String,​String> hyperParameters)

        Algorithm-specific parameters.

        Parameters:
        hyperParameters - Algorithm-specific parameters.
        Returns:
        Returns a reference to this object so that method calls can be chained together.

      • algorithmSpecification

        DescribeTrainingJobResponse.Builder algorithmSpecification​(AlgorithmSpecification algorithmSpecification)

        Information about the algorithm used for training, and algorithm metadata.

        Parameters:
        algorithmSpecification - Information about the algorithm used for training, and algorithm metadata.
        Returns:
        Returns a reference to this object so that method calls can be chained together.

      • roleArn

        DescribeTrainingJobResponse.Builder roleArn​(String roleArn)

        The Amazon Web Services Identity and Access Management (IAM) role configured for the training job.

        Parameters:
        roleArn - The Amazon Web Services Identity and Access Management (IAM) role configured for the training job.
        Returns:
        Returns a reference to this object so that method calls can be chained together.

      • inputDataConfig

        DescribeTrainingJobResponse.Builder inputDataConfig​(Collection<Channel> inputDataConfig)

        An array of Channel objects that describes each data input channel.

        Parameters:
        inputDataConfig - An array of Channel objects that describes each data input channel.
        Returns:
        Returns a reference to this object so that method calls can be chained together.

      • inputDataConfig

        DescribeTrainingJobResponse.Builder inputDataConfig​(Channel... inputDataConfig)

        An array of Channel objects that describes each data input channel.

        Parameters:
        inputDataConfig - An array of Channel objects that describes each data input channel.
        Returns:
        Returns a reference to this object so that method calls can be chained together.

      • inputDataConfig

        DescribeTrainingJobResponse.Builder inputDataConfig​(Consumer<Channel.Builder>... inputDataConfig)

        An array of Channel objects that describes each data input channel.

        This is a convenience method that creates an instance of the Channel.Builder avoiding the need to create one manually via Channel.builder().

        When the Consumer completes, SdkBuilder.build() is called immediately and its result is passed to #inputDataConfig(List).

        Parameters:
        inputDataConfig - a consumer that will call methods on Channel.Builder
        Returns:
        Returns a reference to this object so that method calls can be chained together.
        See Also:
        #inputDataConfig(java.util.Collection)

      • outputDataConfig

        DescribeTrainingJobResponse.Builder outputDataConfig​(OutputDataConfig outputDataConfig)

        The S3 path where model artifacts that you configured when creating the job are stored. SageMaker creates subfolders for model artifacts.

        Parameters:
        outputDataConfig - The S3 path where model artifacts that you configured when creating the job are stored. SageMaker creates subfolders for model artifacts.
        Returns:
        Returns a reference to this object so that method calls can be chained together.

      • resourceConfig

        DescribeTrainingJobResponse.Builder resourceConfig​(ResourceConfig resourceConfig)

        Resources, including ML compute instances and ML storage volumes, that are configured for model training.

        Parameters:
        resourceConfig - Resources, including ML compute instances and ML storage volumes, that are configured for model training.
        Returns:
        Returns a reference to this object so that method calls can be chained together.

      • warmPoolStatus

        DescribeTrainingJobResponse.Builder warmPoolStatus​(WarmPoolStatus warmPoolStatus)

        The status of the warm pool associated with the training job.

        Parameters:
        warmPoolStatus - The status of the warm pool associated with the training job.
        Returns:
        Returns a reference to this object so that method calls can be chained together.

      • stoppingCondition

        DescribeTrainingJobResponse.Builder stoppingCondition​(StoppingCondition stoppingCondition)

        Specifies a limit to how long a model training job can run. It also specifies how long a managed Spot training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this API to cap model training costs.

        To stop a job, SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of training are not lost.

        Parameters:
        stoppingCondition - Specifies a limit to how long a model training job can run. It also specifies how long a managed Spot training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this API to cap model training costs.

        To stop a job, SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of training are not lost.

        Returns:
        Returns a reference to this object so that method calls can be chained together.

      • creationTime

        DescribeTrainingJobResponse.Builder creationTime​(Instant creationTime)

        A timestamp that indicates when the training job was created.

        Parameters:
        creationTime - A timestamp that indicates when the training job was created.
        Returns:
        Returns a reference to this object so that method calls can be chained together.

      • trainingStartTime

        DescribeTrainingJobResponse.Builder trainingStartTime​(Instant 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.

        Parameters:
        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.
        Returns:
        Returns a reference to this object so that method calls can be chained together.

      • trainingEndTime

        DescribeTrainingJobResponse.Builder trainingEndTime​(Instant 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 SageMaker detects a job failure.

        Parameters:
        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 SageMaker detects a job failure.
        Returns:
        Returns a reference to this object so that method calls can be chained together.

      • lastModifiedTime

        DescribeTrainingJobResponse.Builder lastModifiedTime​(Instant lastModifiedTime)

        A timestamp that indicates when the status of the training job was last modified.

        Parameters:
        lastModifiedTime - A timestamp that indicates when the status of the training job was last modified.
        Returns:
        Returns a reference to this object so that method calls can be chained together.

      • secondaryStatusTransitions

        DescribeTrainingJobResponse.Builder secondaryStatusTransitions​(Collection<SecondaryStatusTransition> secondaryStatusTransitions)

        A history of all of the secondary statuses that the training job has transitioned through.

        Parameters:
        secondaryStatusTransitions - A history of all of the secondary statuses that the training job has transitioned through.
        Returns:
        Returns a reference to this object so that method calls can be chained together.

      • secondaryStatusTransitions

        DescribeTrainingJobResponse.Builder secondaryStatusTransitions​(SecondaryStatusTransition... secondaryStatusTransitions)

        A history of all of the secondary statuses that the training job has transitioned through.

        Parameters:
        secondaryStatusTransitions - A history of all of the secondary statuses that the training job has transitioned through.
        Returns:
        Returns a reference to this object so that method calls can be chained together.

      • finalMetricDataList

        DescribeTrainingJobResponse.Builder finalMetricDataList​(Collection<MetricData> finalMetricDataList)

        A collection of MetricData objects that specify the names, values, and dates and times that the training algorithm emitted to Amazon CloudWatch.

        Parameters:
        finalMetricDataList - A collection of MetricData objects that specify the names, values, and dates and times that the training algorithm emitted to Amazon CloudWatch.
        Returns:
        Returns a reference to this object so that method calls can be chained together.

      • finalMetricDataList

        DescribeTrainingJobResponse.Builder finalMetricDataList​(MetricData... finalMetricDataList)

        A collection of MetricData objects that specify the names, values, and dates and times that the training algorithm emitted to Amazon CloudWatch.

        Parameters:
        finalMetricDataList - A collection of MetricData objects that specify the names, values, and dates and times that the training algorithm emitted to Amazon CloudWatch.
        Returns:
        Returns a reference to this object so that method calls can be chained together.

      • finalMetricDataList

        DescribeTrainingJobResponse.Builder finalMetricDataList​(Consumer<MetricData.Builder>... finalMetricDataList)

        A collection of MetricData objects that specify the names, values, and dates and times that the training algorithm emitted to Amazon CloudWatch.

        This is a convenience method that creates an instance of the MetricData.Builder avoiding the need to create one manually via MetricData.builder().

        When the Consumer completes, SdkBuilder.build() is called immediately and its result is passed to #finalMetricDataList(List).

        Parameters:
        finalMetricDataList - a consumer that will call methods on MetricData.Builder
        Returns:
        Returns a reference to this object so that method calls can be chained together.
        See Also:
        #finalMetricDataList(java.util.Collection)

      • enableNetworkIsolation

        DescribeTrainingJobResponse.Builder enableNetworkIsolation​(Boolean enableNetworkIsolation)

        If you want to allow inbound or outbound network calls, except for calls between peers within a training cluster for distributed training, choose True. If you enable network isolation for training jobs that are configured to use a VPC, SageMaker downloads and uploads customer data and model artifacts through the specified VPC, but the training container does not have network access.

        Parameters:
        enableNetworkIsolation - If you want to allow inbound or outbound network calls, except for calls between peers within a training cluster for distributed training, choose True. If you enable network isolation for training jobs that are configured to use a VPC, SageMaker downloads and uploads customer data and model artifacts through the specified VPC, but the training container does not have network access.
        Returns:
        Returns a reference to this object so that method calls can be chained together.

      • enableInterContainerTrafficEncryption

        DescribeTrainingJobResponse.Builder enableInterContainerTrafficEncryption​(Boolean enableInterContainerTrafficEncryption)

        To encrypt all communications between ML compute instances in distributed training, choose True. Encryption provides greater security for distributed training, but training might take longer. How long it takes depends on the amount of communication between compute instances, especially if you use a deep learning algorithms in distributed training.

        Parameters:
        enableInterContainerTrafficEncryption - To encrypt all communications between ML compute instances in distributed training, choose True. Encryption provides greater security for distributed training, but training might take longer. How long it takes depends on the amount of communication between compute instances, especially if you use a deep learning algorithms in distributed training.
        Returns:
        Returns a reference to this object so that method calls can be chained together.

      • enableManagedSpotTraining

        DescribeTrainingJobResponse.Builder enableManagedSpotTraining​(Boolean enableManagedSpotTraining)

        A Boolean indicating whether managed spot training is enabled (True) or not (False ).

        Parameters:
        enableManagedSpotTraining - A Boolean indicating whether managed spot training is enabled (True) or not ( False).
        Returns:
        Returns a reference to this object so that method calls can be chained together.

      • checkpointConfig

        DescribeTrainingJobResponse.Builder checkpointConfig​(CheckpointConfig checkpointConfig)
        Sets the value of the CheckpointConfig property for this object.
        Parameters:
        checkpointConfig - The new value for the CheckpointConfig property for this object.
        Returns:
        Returns a reference to this object so that method calls can be chained together.

      • trainingTimeInSeconds

        DescribeTrainingJobResponse.Builder trainingTimeInSeconds​(Integer trainingTimeInSeconds)

        The training time in seconds.

        Parameters:
        trainingTimeInSeconds - The training time in seconds.
        Returns:
        Returns a reference to this object so that method calls can be chained together.

      • billableTimeInSeconds

        DescribeTrainingJobResponse.Builder billableTimeInSeconds​(Integer billableTimeInSeconds)

        The billable time in seconds. Billable time refers to the absolute wall-clock time.

        Multiply BillableTimeInSeconds by the number of instances (InstanceCount) in your training cluster to get the total compute time SageMaker bills you if you run distributed training. The formula is as follows: BillableTimeInSeconds * InstanceCount .

        You can calculate the savings from using managed spot training using the formula (1 - BillableTimeInSeconds / TrainingTimeInSeconds) * 100. For example, if BillableTimeInSeconds is 100 and TrainingTimeInSeconds is 500, the savings is 80%.

        Parameters:
        billableTimeInSeconds - The billable time in seconds. Billable time refers to the absolute wall-clock time.

        Multiply BillableTimeInSeconds by the number of instances (InstanceCount) in your training cluster to get the total compute time SageMaker bills you if you run distributed training. The formula is as follows: BillableTimeInSeconds * InstanceCount .

        You can calculate the savings from using managed spot training using the formula (1 - BillableTimeInSeconds / TrainingTimeInSeconds) * 100. For example, if BillableTimeInSeconds is 100 and TrainingTimeInSeconds is 500, the savings is 80%.

        Returns:
        Returns a reference to this object so that method calls can be chained together.

      • debugHookConfig

        DescribeTrainingJobResponse.Builder debugHookConfig​(DebugHookConfig debugHookConfig)
        Sets the value of the DebugHookConfig property for this object.
        Parameters:
        debugHookConfig - The new value for the DebugHookConfig property for this object.
        Returns:
        Returns a reference to this object so that method calls can be chained together.

      • experimentConfig

        DescribeTrainingJobResponse.Builder experimentConfig​(ExperimentConfig experimentConfig)
        Sets the value of the ExperimentConfig property for this object.
        Parameters:
        experimentConfig - The new value for the ExperimentConfig property for this object.
        Returns:
        Returns a reference to this object so that method calls can be chained together.

      • debugRuleConfigurations

        DescribeTrainingJobResponse.Builder debugRuleConfigurations​(Collection<DebugRuleConfiguration> debugRuleConfigurations)

        Configuration information for Amazon SageMaker Debugger rules for debugging output tensors.

        Parameters:
        debugRuleConfigurations - Configuration information for Amazon SageMaker Debugger rules for debugging output tensors.
        Returns:
        Returns a reference to this object so that method calls can be chained together.

      • debugRuleConfigurations

        DescribeTrainingJobResponse.Builder debugRuleConfigurations​(DebugRuleConfiguration... debugRuleConfigurations)

        Configuration information for Amazon SageMaker Debugger rules for debugging output tensors.

        Parameters:
        debugRuleConfigurations - Configuration information for Amazon SageMaker Debugger rules for debugging output tensors.
        Returns:
        Returns a reference to this object so that method calls can be chained together.

      • tensorBoardOutputConfig

        DescribeTrainingJobResponse.Builder tensorBoardOutputConfig​(TensorBoardOutputConfig tensorBoardOutputConfig)
        Sets the value of the TensorBoardOutputConfig property for this object.
        Parameters:
        tensorBoardOutputConfig - The new value for the TensorBoardOutputConfig property for this object.
        Returns:
        Returns a reference to this object so that method calls can be chained together.

      • debugRuleEvaluationStatuses

        DescribeTrainingJobResponse.Builder debugRuleEvaluationStatuses​(Collection<DebugRuleEvaluationStatus> debugRuleEvaluationStatuses)

        Evaluation status of Amazon SageMaker Debugger rules for debugging on a training job.

        Parameters:
        debugRuleEvaluationStatuses - Evaluation status of Amazon SageMaker Debugger rules for debugging on a training job.
        Returns:
        Returns a reference to this object so that method calls can be chained together.

      • debugRuleEvaluationStatuses

        DescribeTrainingJobResponse.Builder debugRuleEvaluationStatuses​(DebugRuleEvaluationStatus... debugRuleEvaluationStatuses)

        Evaluation status of Amazon SageMaker Debugger rules for debugging on a training job.

        Parameters:
        debugRuleEvaluationStatuses - Evaluation status of Amazon SageMaker Debugger rules for debugging on a training job.
        Returns:
        Returns a reference to this object so that method calls can be chained together.

      • profilerConfig

        DescribeTrainingJobResponse.Builder profilerConfig​(ProfilerConfig profilerConfig)
        Sets the value of the ProfilerConfig property for this object.
        Parameters:
        profilerConfig - The new value for the ProfilerConfig property for this object.
        Returns:
        Returns a reference to this object so that method calls can be chained together.

      • profilerRuleConfigurations

        DescribeTrainingJobResponse.Builder profilerRuleConfigurations​(Collection<ProfilerRuleConfiguration> profilerRuleConfigurations)

        Configuration information for Amazon SageMaker Debugger rules for profiling system and framework metrics.

        Parameters:
        profilerRuleConfigurations - Configuration information for Amazon SageMaker Debugger rules for profiling system and framework metrics.
        Returns:
        Returns a reference to this object so that method calls can be chained together.

      • profilerRuleConfigurations

        DescribeTrainingJobResponse.Builder profilerRuleConfigurations​(ProfilerRuleConfiguration... profilerRuleConfigurations)

        Configuration information for Amazon SageMaker Debugger rules for profiling system and framework metrics.

        Parameters:
        profilerRuleConfigurations - Configuration information for Amazon SageMaker Debugger rules for profiling system and framework metrics.
        Returns:
        Returns a reference to this object so that method calls can be chained together.

      • profilerRuleEvaluationStatuses

        DescribeTrainingJobResponse.Builder profilerRuleEvaluationStatuses​(Collection<ProfilerRuleEvaluationStatus> profilerRuleEvaluationStatuses)

        Evaluation status of Amazon SageMaker Debugger rules for profiling on a training job.

        Parameters:
        profilerRuleEvaluationStatuses - Evaluation status of Amazon SageMaker Debugger rules for profiling on a training job.
        Returns:
        Returns a reference to this object so that method calls can be chained together.

      • profilerRuleEvaluationStatuses

        DescribeTrainingJobResponse.Builder profilerRuleEvaluationStatuses​(ProfilerRuleEvaluationStatus... profilerRuleEvaluationStatuses)

        Evaluation status of Amazon SageMaker Debugger rules for profiling on a training job.

        Parameters:
        profilerRuleEvaluationStatuses - Evaluation status of Amazon SageMaker Debugger rules for profiling on a training job.
        Returns:
        Returns a reference to this object so that method calls can be chained together.

      • environment

        DescribeTrainingJobResponse.Builder environment​(Map<String,​String> environment)

        The environment variables to set in the Docker container.

        Parameters:
        environment - The environment variables to set in the Docker container.
        Returns:
        Returns a reference to this object so that method calls can be chained together.

      • retryStrategy

        DescribeTrainingJobResponse.Builder retryStrategy​(RetryStrategy retryStrategy)

        The number of times to retry the job when the job fails due to an InternalServerError.

        Parameters:
        retryStrategy - The number of times to retry the job when the job fails due to an InternalServerError.
        Returns:
        Returns a reference to this object so that method calls can be chained together.

      • infraCheckConfig

        DescribeTrainingJobResponse.Builder infraCheckConfig​(InfraCheckConfig infraCheckConfig)

        Contains information about the infrastructure health check configuration for the training job.

        Parameters:
        infraCheckConfig - Contains information about the infrastructure health check configuration for the training job.
        Returns:
        Returns a reference to this object so that method calls can be chained together.