PyTorch Cifar10 SageMaker Sweep
This example uses AWS SageMaker to launch a hyperparameter sweep.
train.py uses the AWS SageMaker api to launch a sweep.
If you run this script outside of a SageMaker notebook instance, you'll need to download the aws cli and run aws configure and then set the SAGEMAKER_ROLE environment variable to an AWS role name that has access to SageMaker, you can find your roles here.
To authenticate with W&B, we call
train.py. This will look for W&B credentials in the current environment and pass them to sagemaker. Calling
wandb login MY_API_KEY on the machine you're running from will ensure credentials get passed.