# Configure the `DebuggerHookConfig` API to save tensors
<a name="debugger-configure-tensor-hook"></a>

Use the [DebuggerHookConfig](https://sagemaker.readthedocs.io/en/stable/api/training/debugger.html                 #sagemaker.debugger.DebuggerHookConfig) API to create a `debugger_hook_config` object using the `collection_configs` object you created in the previous step.

```
from sagemaker.debugger import DebuggerHookConfig

debugger_hook_config=DebuggerHookConfig(
    collection_configs=collection_configs
)
```

Debugger saves the model training output tensors into the default S3 bucket. The format of the default S3 bucket URI is `s3://amzn-s3-demo-bucket-sagemaker-<region>-<12digit_account_id>/<training-job-name>/debug-output/.`

If you want to specify an exact S3 bucket URI, use the following code example:

```
from sagemaker.debugger import DebuggerHookConfig

debugger_hook_config=DebuggerHookConfig(
    s3_output_path="specify-uri"
    collection_configs=collection_configs
)
```

For more information, see [DebuggerHookConfig](https://sagemaker.readthedocs.io/en/stable/api/training/debugger.html#sagemaker.debugger.DebuggerHookConfig) in the [Amazon SageMaker Python SDK](https://sagemaker.readthedocs.io/en/stable).