Inducing index points initializers

The initializers module contains work-in-progress algorithms for more intelligently initializing the locations of inducing index points for the variational Gaussian process (VGP). As per the TensorFlow documentation, VGPs are highly sensitive to the location of these points, so improving the initializer could substantially increase performance.

So far, only one custom initializer has been implemented and it does not seem to offer any performance improvement over the default initializer:

class unlocknn.initializers.SampleInitializer(train_structs: List[Structure], meg_model: MEGNetModel, num_inducing_points: Optional[int] = None, latent_layer: int = - 2, batch_size: int = 128, scrub_failed_structs: bool = False)

Initializer that samples index points from training data.