TensorBoard in Amazon SageMaker

Amazon SageMaker with TensorBoard is a capability of Amazon SageMaker that brings the TensorBoard visualization tools to SageMaker and integrated with SageMaker Training and domain. It provides options to administer your AWS account and users belonging to the account through SageMaker domain, to give the domain users access to the TensorBoard data with appropriate permissions to Amazon S3, and help the domain users perform model debugging tasks using the TensorBoard visualization plugins. SageMaker with TensorBoard is extended with the SageMaker Data Manager plugin, with which domain users can access a number of training jobs in one place within the TensorBoard application.

For data scientists

Training large models can have scientific problems that require data scientists to debug and resolve them in order to improve model convergence and stabilize gradient descent processes.

When you encounter model training issues, such as loss not converging, or vanishing or exploding weights and gradients, you need to access tensor data to dive deep and analyze the model parameters, scalars, and any custom metrics. Using SageMaker with TensorBoard, you can visualize model output tensors extracted from training jobs. As you experiment with different models, multiple training runs, and model hyperparameters, you can select multiple training jobs in TensorBoard and compare them in one place.

For administrators

Through the TensorBoard landing page in the SageMaker console or SageMaker domain, you can manage TensorBoard application users if you are an administrator of an AWS account or SageMaker domain. Each domain user can access their own TensorBoard application given the granted permissions. As a SageMaker domain administrator and domain user, you can create and delete the TensorBoard application given the permission level you have.

Supported frameworks and AWS Regions

The TensorBoard application in SageMaker is available for the following machine learning frameworks and AWS Regions.