# Use Debugger built-in rules with custom parameter values
<a name="debugger-built-in-rules-configuration-param-change"></a>

**Note**  
Amazon SageMaker Debugger is no longer open to new customers. Existing customers can continue to use the service as normal. AWS continues to invest in security and availability improvements for Debugger, but we do not plan to introduce new features. For more information, see [Debugger availability change](debugger-availability-change.md). 

If you want to adjust the built-in rule parameter values and customize tensor collection regex, configure the `base_config` and `rule_parameters` parameters for the `ProfilerRule.sagemaker` and `Rule.sagemaker` classmethods. In case of the `Rule.sagemaker` class methods, you can also customize tensor collections through the `collections_to_save` parameter. The instruction of how to use the `CollectionConfig` class is provided at [Configure tensor collections using the `CollectionConfig` API](debugger-configure-tensor-collections.md). 

Use the following configuration template for built-in rules to customize parameter values. By changing the rule parameters as you want, you can adjust the sensitivity of the rules to be triggered. 
+ The `base_config` argument is where you call the built-in rule methods.
+ The `rule_parameters` argument is to adjust the default key values of the built-in rules listed in [List of Debugger built-in rules](debugger-built-in-rules.md).
+ The `collections_to_save` argument takes in a tensor configuration through the `CollectionConfig` API, which requires `name` and `parameters` arguments. 
  + To find available tensor collections for `name`, see [ Debugger Built-in Tensor Collections ](https://github.com/awslabs/sagemaker-debugger/blob/master/docs/api.md#built-in-collections). 
  + For a full list of adjustable `parameters`, see [ Debugger CollectionConfig API](https://github.com/awslabs/sagemaker-debugger/blob/master/docs/api.md#configuring-collection-using-sagemaker-python-sdk).

For more information about the Debugger rule class, methods, and parameters, see [SageMaker AI Debugger Rule class](https://sagemaker.readthedocs.io/en/stable/api/training/debugger.html) in the [Amazon SageMaker Python SDK](https://sagemaker.readthedocs.io/en/stable).

```
from sagemaker.core.debugger import Rule, ProfilerRule, rule_configs, CollectionConfig

rules=[
    Rule.sagemaker(
        base_config=rule_configs.{{built_in_rule_name}}(),
        rule_parameters={
                "{{key}}": "{{value}}"
        },
        collections_to_save=[ 
            CollectionConfig(
                name="{{tensor_collection_name}}", 
                parameters={
                    "{{key}}": "{{value}}"
                } 
            )
        ]
    )
]
```

The parameter descriptions and value customization examples are provided for each rule at [List of Debugger built-in rules](debugger-built-in-rules.md).