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 / 
Paws-0.40
River stage two • 9 direct dependents • 11 total dependents
57 ++
/ Paws::SageMaker::TrainingJobDefinition

NAME

Paws::SageMaker::TrainingJobDefinition

USAGE

This class represents one of two things:

Arguments in a call to a service

Use the attributes of this class as arguments to methods. You shouldn't make instances of this class. Each attribute should be used as a named argument in the calls that expect this type of object.

As an example, if Att1 is expected to be a Paws::SageMaker::TrainingJobDefinition object:

  $service_obj->Method(Att1 => { HyperParameters => $value, ..., TrainingInputMode => $value  });

Results returned from an API call

Use accessors for each attribute. If Att1 is expected to be an Paws::SageMaker::TrainingJobDefinition object:

  $result = $service_obj->Method(...);
  $result->Att1->HyperParameters

DESCRIPTION

Defines the input needed to run a training job using the algorithm.

ATTRIBUTES

HyperParameters => Paws::SageMaker::HyperParameters

  The hyperparameters used for the training job.

REQUIRED InputDataConfig => ArrayRef[Paws::SageMaker::Channel]

  An array of C<Channel> objects, each of which specifies an input
source.

REQUIRED OutputDataConfig => Paws::SageMaker::OutputDataConfig

  the path to the S3 bucket where you want to store model artifacts.
Amazon SageMaker creates subfolders for the artifacts.

REQUIRED ResourceConfig => Paws::SageMaker::ResourceConfig

  The resources, including the ML compute instances and ML storage
volumes, to use for model training.

REQUIRED StoppingCondition => Paws::SageMaker::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.

REQUIRED TrainingInputMode => Str

  The input mode used by the algorithm for the training job. For the
input modes that Amazon SageMaker algorithms support, see Algorithms
(http://docs.aws.amazon.com/sagemaker/latest/dg/algos.html).

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.

SEE ALSO

This class forms part of Paws, describing an object used in Paws::SageMaker

BUGS and CONTRIBUTIONS

The source code is located here: https://github.com/pplu/aws-sdk-perl

Please report bugs to: https://github.com/pplu/aws-sdk-perl/issues