# Use Debugger built-in rules with custom parameter values
Configure Debugger Built-in Rules with Custom Parameter Values

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.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).