> ## Documentation Index
> Fetch the complete documentation index at: https://rasa.com/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Nlu-meta-intent-featurizer

> Nlu-meta-intent-featurizer reference documentation for the Rasa Platform.

```python theme={null}
from rasa.engine.recipes.default_recipe import DefaultV1Recipe
from rasa.shared.nlu.training_data.training_data import TrainingData
from rasa.nlu.classifiers.diet_classifier import DIETClassifier

@DefaultV1Recipe.register(
    [DefaultV1Recipe.ComponentType.INTENT_CLASSIFIER,
     DefaultV1Recipe.ComponentType.ENTITY_EXTRACTOR,
     DefaultV1Recipe.ComponentType.MESSAGE_FEATURIZER], is_trainable=True
)
class DIETFeaturizer(DIETClassifier):

    def process_training_data(self, training_data: TrainingData) -> TrainingData:
        # classify and add the attributes to the messages on the training data
        return training_data
```


## Related topics

- [NLU Components](/docs/reference/config/components/nlu-components.md)
- [Intents and Entities](/docs/reference/primitives/intents-and-entities.md)
- [Nlu-meta-fallback](/docs/reference/config/components/example-components/custom-graph-components/nlu-meta-fallback.md)
- [Rasa Pro Version Migration Guide](/docs/reference/changelogs/rasa-pro-migration-guide.md)
- [Training Data Format](/docs/reference/primitives/training-data-format.md)