TrainingSpecification - Amazon SageMaker


Defines how the algorithm is used for a training job.



A list of the instance types that this algorithm can use for training.

Type: Array of strings

Valid Values: ml.m4.xlarge | ml.m4.2xlarge | ml.m4.4xlarge | ml.m4.10xlarge | ml.m4.16xlarge | ml.g4dn.xlarge | ml.g4dn.2xlarge | ml.g4dn.4xlarge | ml.g4dn.8xlarge | ml.g4dn.12xlarge | ml.g4dn.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.p3dn.24xlarge | ml.p4d.24xlarge | ml.p4de.24xlarge | ml.p5.48xlarge | ml.c5.xlarge | ml.c5.2xlarge | ml.c5.4xlarge | ml.c5.9xlarge | ml.c5.18xlarge | ml.c5n.xlarge | ml.c5n.2xlarge | ml.c5n.4xlarge | ml.c5n.9xlarge | ml.c5n.18xlarge | ml.g5.xlarge | ml.g5.2xlarge | ml.g5.4xlarge | ml.g5.8xlarge | ml.g5.16xlarge | ml.g5.12xlarge | ml.g5.24xlarge | ml.g5.48xlarge | ml.trn1.2xlarge | ml.trn1.32xlarge | ml.trn1n.32xlarge | ml.m6i.large | ml.m6i.xlarge | ml.m6i.2xlarge | ml.m6i.4xlarge | ml.m6i.8xlarge | ml.m6i.12xlarge | ml.m6i.16xlarge | ml.m6i.24xlarge | ml.m6i.32xlarge | ml.c6i.xlarge | ml.c6i.2xlarge | ml.c6i.8xlarge | ml.c6i.4xlarge | ml.c6i.12xlarge | ml.c6i.16xlarge | ml.c6i.24xlarge | ml.c6i.32xlarge

Required: Yes


A list of ChannelSpecification objects, which specify the input sources to be used by the algorithm.

Type: Array of ChannelSpecification objects

Array Members: Minimum number of 1 item. Maximum number of 8 items.

Required: Yes


The Amazon ECR registry path of the Docker image that contains the training algorithm.

Type: String

Length Constraints: Maximum length of 255.

Pattern: [\S]+

Required: Yes


The additional data source used during the training job.

Type: AdditionalS3DataSource object

Required: No


A list of MetricDefinition objects, which are used for parsing metrics generated by the algorithm.

Type: Array of MetricDefinition objects

Array Members: Minimum number of 0 items. Maximum number of 40 items.

Required: No


A list of the HyperParameterSpecification objects, that define the supported hyperparameters. This is required if the algorithm supports automatic model tuning.>

Type: Array of HyperParameterSpecification objects

Array Members: Minimum number of 0 items. Maximum number of 100 items.

Required: No


A list of the metrics that the algorithm emits that can be used as the objective metric in a hyperparameter tuning job.

Type: Array of HyperParameterTuningJobObjective objects

Required: No


Indicates whether the algorithm supports distributed training. If set to false, buyers can't request more than one instance during training.

Type: Boolean

Required: No


An MD5 hash of the training algorithm that identifies the Docker image used for training.

Type: String

Length Constraints: Maximum length of 72.

Pattern: ^[Ss][Hh][Aa]256:[0-9a-fA-F]{64}$

Required: No

See Also

For more information about using this API in one of the language-specific AWS SDKs, see the following: