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Class: Aws::SageMaker::Types::ProcessingResources
- Inherits:
-
Struct
- Object
- Struct
- Aws::SageMaker::Types::ProcessingResources
- Defined in:
- (unknown)
Overview
Note:
When passing ProcessingResources as input to an Aws::Client method, you can use a vanilla 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.
Returned by:
Instance Attribute Summary collapse
-
#cluster_config ⇒ Types::ProcessingClusterConfig
The configuration for the resources in a cluster used to run the processing job.
Instance Attribute Details
#cluster_config ⇒ Types::ProcessingClusterConfig
The configuration for the resources in a cluster used to run the processing job.