Hyperparameters¶
Accessors to retrieve hyperparameters for training jobs.
-
sagemaker.hyperparameters.
retrieve_default
(region=None, model_id=None, model_version=None, include_container_hyperparameters=False) → Dict[str, str]¶ Retrieves the default training hyperparameters for the model matching the given arguments.
- Parameters
region (str) – The AWS Region for which to retrieve the default hyperparameters. Defaults to
None
.model_id (str) – The model ID of the model for which to retrieve the default hyperparameters. (Default: None).
model_version (str) – The version of the model for which to retrieve the default hyperparameters. (Default: None).
include_container_hyperparameters (bool) –
True
if the container hyperparameters should be returned. Container hyperparameters are not used to tune the specific algorithm. They are used by SageMaker Training jobs to set up the training container environment. For example, there is a container hyperparameter that indicates the entrypoint script to use. These hyperparameters may be required when creating a training job with boto3, however theEstimator
classes add required container hyperparameters to the job. (Default: False).
- Returns
The hyperparameters to use for the model.
- Return type
- Raises
ValueError – If the combination of arguments specified is not supported.
-
sagemaker.hyperparameters.
validate
(region: Optional[str] = None, model_id: Optional[str] = None, model_version: Optional[str] = None, hyperparameters: Optional[dict] = None, validation_mode: Optional[sagemaker.jumpstart.enums.HyperparameterValidationMode] = None) → None¶ Validates hyperparameters for models.
- Parameters
region (str) – The AWS Region for which to validate hyperparameters. (Default: None).
model_id (str) – The model ID of the model for which to validate hyperparameters. (Default: None).
model_version (str) – The version of the model for which to validate hyperparameters. (Default: None).
hyperparameters (dict) – Hyperparameters to validate. (Default: None).
validation_mode (HyperparameterValidationMode) – Method of validation to use with hyperparameters. If set to
VALIDATE_PROVIDED
, only hyperparameters provided to this function will be validated, the missing hyperparameters will be ignored. If set to``VALIDATE_ALGORITHM``, all algorithm hyperparameters will be validated. If set toVALIDATE_ALL
, all hyperparameters for the model will be validated. (Default: None).
- Raises
JumpStartHyperparametersError – If the hyperparameter is not formatted correctly, according to its specs in the model metadata.
ValueError – If the combination of arguments specified is not supported.