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[ aws . sagemaker ]

describe-auto-ml-job

Description

Returns information about an Amazon SageMaker job.

See also: AWS API Documentation

See 'aws help' for descriptions of global parameters.

Synopsis

  describe-auto-ml-job
--auto-ml-job-name <value>
[--cli-input-json <value>]
[--generate-cli-skeleton <value>]

Options

--auto-ml-job-name (string)

Request information about a job using that job's unique name.

--cli-input-json (string) Performs service operation based on the JSON string provided. The JSON string follows the format provided by --generate-cli-skeleton. If other arguments are provided on the command line, the CLI values will override the JSON-provided values. It is not possible to pass arbitrary binary values using a JSON-provided value as the string will be taken literally.

--generate-cli-skeleton (string) Prints a JSON skeleton to standard output without sending an API request. If provided with no value or the value input, prints a sample input JSON that can be used as an argument for --cli-input-json. If provided with the value output, it validates the command inputs and returns a sample output JSON for that command.

See 'aws help' for descriptions of global parameters.

Output

AutoMLJobName -> (string)

Returns the name of a job.

AutoMLJobArn -> (string)

Returns the job's ARN.

InputDataConfig -> (list)

Returns the job's input data config.

(structure)

Similar to Channel. A channel is a named input source that training algorithms can consume. Refer to Channel for detailed descriptions.

DataSource -> (structure)

The data source.

S3DataSource -> (structure)

The Amazon S3 location of the input data.

Note

The input data must be in CSV format and contain at least 1000 rows.

S3DataType -> (string)

The data type.

S3Uri -> (string)

The URL to the Amazon S3 data source.

CompressionType -> (string)

You can use Gzip or None. The default value is None.

TargetAttributeName -> (string)

The name of the target variable in supervised learning, a.k.a. 'y'.

OutputDataConfig -> (structure)

Returns the job's output data config.

KmsKeyId -> (string)

The AWS KMS encryption key ID.

S3OutputPath -> (string)

The Amazon S3 output path. Must be 128 characters or less.

RoleArn -> (string)

The Amazon Resource Name (ARN) of the AWS Identity and Access Management (IAM) role that has read permission to the input data location and write permission to the output data location in Amazon S3.

AutoMLJobObjective -> (structure)

Returns the job's objective.

MetricName -> (string)

The name of the metric.

ProblemType -> (string)

Returns the job's problem type.

AutoMLJobConfig -> (structure)

Returns the job's config.

CompletionCriteria -> (structure)

How long a job is allowed to run, or how many candidates a job is allowed to generate.

MaxCandidates -> (integer)

The maximum number of times a training job is allowed to run.

MaxRuntimePerTrainingJobInSeconds -> (integer)

The maximum time, in seconds, a job is allowed to run.

MaxAutoMLJobRuntimeInSeconds -> (integer)

The maximum time, in seconds, an AutoML job is allowed to wait for a trial to complete. It must be equal to or greater than MaxRuntimePerTrainingJobInSeconds.

SecurityConfig -> (structure)

Security configuration for traffic encryption or Amazon VPC settings.

VolumeKmsKeyId -> (string)

The key used to encrypt stored data.

EnableInterContainerTrafficEncryption -> (boolean)

Whether to use traffic encryption between the container layers.

VpcConfig -> (structure)

VPC configuration.

SecurityGroupIds -> (list)

The VPC security group IDs, in the form sg-xxxxxxxx. Specify the security groups for the VPC that is specified in the Subnets field.

(string)

Subnets -> (list)

The ID of the subnets in the VPC to which you want to connect your training job or model. For information about the availability of specific instance types, see Supported Instance Types and Availability Zones .

(string)

CreationTime -> (timestamp)

Returns the job's creation time.

EndTime -> (timestamp)

Returns the job's end time.

LastModifiedTime -> (timestamp)

Returns the job's last modified time.

FailureReason -> (string)

Returns the job's FailureReason.

BestCandidate -> (structure)

Returns the job's BestCandidate.

CandidateName -> (string)

The candidate name.

FinalAutoMLJobObjectiveMetric -> (structure)

The candidate result from a job.

Type -> (string)

The metric type used.

MetricName -> (string)

The name of the metric.

Value -> (float)

The value of the metric.

ObjectiveStatus -> (string)

The objective status.

CandidateSteps -> (list)

The candidate's steps.

(structure)

Information about the steps for a Candidate, and what step it is working on.

CandidateStepType -> (string)

Whether the Candidate is at the transform, training, or processing step.

CandidateStepArn -> (string)

The ARN for the Candidate's step.

CandidateStepName -> (string)

The name for the Candidate's step.

CandidateStatus -> (string)

The candidate's status.

InferenceContainers -> (list)

The inference containers.

(structure)

A list of container definitions that describe the different containers that make up one AutoML candidate. Refer to ContainerDefinition for more details.

Image -> (string)

The ECR path of the container. Refer to ContainerDefinition for more details.

ModelDataUrl -> (string)

The location of the model artifacts. Refer to ContainerDefinition for more details.

Environment -> (map)

Environment variables to set in the container. Refer to ContainerDefinition for more details.

key -> (string)

value -> (string)

CreationTime -> (timestamp)

The creation time.

EndTime -> (timestamp)

The end time.

LastModifiedTime -> (timestamp)

The last modified time.

FailureReason -> (string)

The failure reason.

AutoMLJobStatus -> (string)

Returns the job's AutoMLJobStatus.

AutoMLJobSecondaryStatus -> (string)

Returns the job's AutoMLJobSecondaryStatus.

GenerateCandidateDefinitionsOnly -> (boolean)

Returns the job's output from GenerateCandidateDefinitionsOnly.

AutoMLJobArtifacts -> (structure)

Returns information on the job's artifacts found in AutoMLJobArtifacts.

CandidateDefinitionNotebookLocation -> (string)

The URL to the notebook location.

DataExplorationNotebookLocation -> (string)

The URL to the notebook location.

ResolvedAttributes -> (structure)

This contains ProblemType, AutoMLJobObjective and CompletionCriteria. They're auto-inferred values, if not provided by you. If you do provide them, then they'll be the same as provided.

AutoMLJobObjective -> (structure)

Applies a metric to minimize or maximize for the job's objective.

MetricName -> (string)

The name of the metric.

ProblemType -> (string)

The problem type.

CompletionCriteria -> (structure)

How long a job is allowed to run, or how many candidates a job is allowed to generate.

MaxCandidates -> (integer)

The maximum number of times a training job is allowed to run.

MaxRuntimePerTrainingJobInSeconds -> (integer)

The maximum time, in seconds, a job is allowed to run.

MaxAutoMLJobRuntimeInSeconds -> (integer)

The maximum time, in seconds, an AutoML job is allowed to wait for a trial to complete. It must be equal to or greater than MaxRuntimePerTrainingJobInSeconds.