Class: Aws::SageMaker::Types::ProcessingResources

Inherits:
Struct
  • Object
show all
Includes:
Aws::Structure
Defined in:
lib/aws-sdk-sagemaker/types.rb

Overview

Note:

When making an API call, you may pass ProcessingResources data as a hash:

{
  cluster_config: { # required
    instance_count: 1, # required
    instance_type: "ml.t3.medium", # required, accepts ml.t3.medium, ml.t3.large, ml.t3.xlarge, ml.t3.2xlarge, ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, ml.c4.xlarge, ml.c4.2xlarge, ml.c4.4xlarge, ml.c4.8xlarge, ml.p2.xlarge, ml.p2.8xlarge, ml.p2.16xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.12xlarge, ml.m5.24xlarge, ml.r5.large, ml.r5.xlarge, ml.r5.2xlarge, ml.r5.4xlarge, ml.r5.8xlarge, ml.r5.12xlarge, ml.r5.16xlarge, ml.r5.24xlarge
    volume_size_in_gb: 1, # required
    volume_kms_key_id: "KmsKeyId",
  },
}

Identifies the resources, ML compute instances, and ML storage volumes to deploy for a processing job. In distributed training, you specify more than one instance.

See Also:

Instance Attribute Summary collapse

Instance Attribute Details

#cluster_config ⇒ Types::ProcessingClusterConfig

The configuration for the resources in a cluster used to run the processing job.



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# File 'lib/aws-sdk-sagemaker/types.rb', line 16062

class ProcessingResources < Struct.new(
  :cluster_config)
  include Aws::Structure
end