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Describes the resources, including ML compute instances and ML storage volumes, to use for model training.
InstanceCount The number of ML compute instances to use. For distributed training, provide a value greater than 1.
Type: Integer
Valid Range: Minimum value of 1.
Required: Yes
InstanceType The ML compute instance type.
Type: String
Valid Values:ml.m4.xlarge | ml.m4.2xlarge | ml.m4.4xlarge | ml.m4.10xlarge | ml.m4.16xlarge | ml.m5.large | ml.m5.xlarge | ml.m5.2xlarge | ml.m5.4xlarge | ml.m5.12xlarge | ml.m5.24xlarge | 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
Required: Yes
VolumeKmsKeyId The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the training job. The VolumeKmsKeyId can be any of the following formats:
+ // KMS Key ID
"1234abcd-12ab-34cd-56ef-1234567890ab" + // Amazon Resource Name (ARN) of a KMS Key
"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab" Type: String
Length Constraints: Maximum length of 2048.
Pattern: .*
Required: No
VolumeSizeInGB The size of the ML storage volume that you want to provision.
ML storage volumes store model artifacts and incremental states. Training algorithms might also use the ML storage volume for scratch space. If you want to store the training data in the ML storage volume, choose File as the TrainingInputMode in the algorithm specification.
You must specify sufficient ML storage for your scenario.
Amazon SageMaker supports only the General Purpose SSD (gp2) ML storage volume type. Type: Integer
Valid Range: Minimum value of 1.
Required: Yes
For more information about using this API in one of the language-specific AWS SDKs, see the following: + AWS SDK for C++ + AWS SDK for Go + AWS SDK for Go - Pilot + AWS SDK for Java + AWS SDK for Ruby V2