Technical requirements
In this chapter, we will provide code samples so that you can develop practical skills. The full code examples are available here: https://github.com/PacktPublishing/Accelerate-Deep-Learning-Workloads-with-Amazon-SageMaker/blob/main/chapter7/.
To follow along with this code, you will need the following:
- An AWS account and IAM user with permission to manage Amazon SageMaker resources.
- Have a SageMaker notebook, SageMaker Studio notebook, or local SageMaker compatible environment established.
- Access to GPU training instances in your AWS account. Each example in this chapter will provide recommended instance types to use. You may need to increase your compute quota for SageMaker Training Job to have GPU instances enabled. In this case, please follow the instructions at https://docs.aws.amazon.com/sagemaker/latest/dg/regions-quotas.html.
- You must install the required Python libraries by running
pip install -r requirements.txt
. The file that...