# Configure tensor collections using the `CollectionConfig` API
<a name="debugger-configure-tensor-collections"></a>

Use the `CollectionConfig` API operation to configure tensor collections. Debugger provides pre-built tensor collections that cover a variety of regular expressions (regex) of parameters if using Debugger-supported deep learning frameworks and machine learning algorithms. As shown in the following example code, add the built-in tensor collections you want to debug.

```
from sagemaker.debugger import CollectionConfig

collection_configs=[
    CollectionConfig(name="weights"),
    CollectionConfig(name="gradients")
]
```

The preceding collections set up the Debugger hook to save the tensors every 500 steps based on the default `"save_interval"` value.

For a full list of available Debugger built-in collections, see [Debugger Built-in Collections](https://github.com/awslabs/sagemaker-debugger/blob/master/docs/api.md#collection).

If you want to customize the built-in collections, such as changing the save intervals and tensor regex, use the following `CollectionConfig` template to adjust parameters.

```
from sagemaker.debugger import CollectionConfig

collection_configs=[
    CollectionConfig(
        name="tensor_collection",
        parameters={
            "key_1": "value_1",
            "key_2": "value_2",
            ...
            "key_n": "value_n"
        }
    )
]
```

For more information about available parameter keys, see [CollectionConfig](https://sagemaker.readthedocs.io/en/stable/api/training/debugger.html#sagemaker.debugger.CollectionConfig) in the [Amazon SageMaker Python SDK](https://sagemaker.readthedocs.io/en/stable). For example, the following code example shows how you can adjust the save intervals of the "losses" tensor collection at different phases of training: save loss every 100 steps in training phase and validation loss every 10 steps in validation phase. 

```
from sagemaker.debugger import CollectionConfig

collection_configs=[
    CollectionConfig(
        name="losses",
        parameters={
            "train.save_interval": "100",
            "eval.save_interval": "10"
        }
    )
]
```

**Tip**  
This tensor collection configuration object can be used for both [DebuggerHookConfig](https://docs.aws.amazon.com/sagemaker/latest/dg/debugger-configure-hook.html#debugger-configure-tensor-hook) and [Rule](https://docs.aws.amazon.com/sagemaker/latest/dg/use-debugger-built-in-rules.html#debugger-built-in-rules-configuration-param-change) API operations.