Amazon SageMaker Python SDK now supports setting default values for parameters
Amazon SageMaker Python SDK is an open source library for training and deploying machine-learning models on Amazon SageMaker. Amazon SageMaker Python SDK users can now configure default values for parameters such as IAM roles, VPC, and KMS keys. For the full list of supported parameters and APIs, see the SageMaker SDK defaults documentation page.
Amazon SageMaker Python SDK is an open source library for training and deploying machine-learning models on Amazon SageMaker. Amazon SageMaker Python SDK users can now configure default values for parameters such as IAM roles, VPC, and KMS keys. For the full list of supported parameters and APIs, see the SageMaker SDK defaults documentation page.
With this update, administrators and end users can initialize AWS infrastructure primitives with defaults specified in a configuration file. We support multiple configuration files, one at the admin level, and another at the user level that can be stored in S3, EFS, or local file system. Once configured, the defaults from these configuration files will be merged and inherited as inputs to the SDK with no additional actions needed. For example, users who may not be familiar with VPC and encryption settings don't need to specify these inputs each time they use a SageMaker API. This saves time for users and admins, eliminates the burden of repetitively specifying parameters, and results in leaner and more manageable code.
This feature is now is available in all regions where Amazon SageMaker Python SDK is available. To learn more, see SageMaker SDK defaults in the Amazon SageMaker Python SDK guide.