Add interfaces for MLModel, MLModel.ModelInput, MLModel.ModelOutput generated classes

**Is your feature request related to a problem? Please describe.**
I have multiple models trained on a dataset that have multiple labels. I disable all of them and enable one of them at a time, do the training, and then enable only the next one, do the training etc.
I end up with multiple trained models and their respective generated classes for consumption.

**Describe the solution you'd like**
It would be great to have a common interface for the MLModel, MLModel.ModelInput and MLModel.ModelOutput classes, because when I need to consume them that would simplify my code significantly.

**Describe alternatives you've considered**
I can still use them separately, but this causes code duplication and code management difficulties.

**Additional context**
I would only need a definition on the interface of the MLModel for the `IModelOutput Predict(IModelInput input)` method, and the `Score` property on the interface of the `ModelOutput`.

Comienza localizando cómo se generan las clases MLModel, MLModel.ModelInput y MLModel.ModelOutput generadas; después, inspecciona los puntos de entrada relacionados con la generación. El trabajo estará terminado cuando los modelos generados expongan las interfaces comunes solicitadas, incluidas Predict(IModelInput input) y la propiedad Score de ModelOutput, sin duplicar código específico del consumidor.

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