Amazon SageMaker Debugger is designed to be a debugger for machine learning
models. It lets you go beyond just looking at scalars like losses and
accuracies during training and gives you full visibility into all tensors
'flowing through the graph' during training or inference.
Amazon SageMaker Debugger RulesConfig provides a mapping of builtin rules with
default configurations. These configurations will affect both DebugHookConfig
and DebugRuleConfigurations in the Amazon SageMaker Python SDK.
This library, intended to be used with Amazon SageMaker Python SDK, helps you
specify builtin rules without worrying about any details or tweak the
configuration of builtin rules. These builtin rules are available in Amazon
SageMaker.
NOTE: If this package has multiple flavors (see below), then use one of them instead of the name specified above. NOTE: This is a Python port. Instead of py312-smdebug-rulesconfig listed in the above command, you can pick from the names under the Packages section.