V0.3.0

[sdatkinson]

Version 0.3.0

Changes breaking backward compatibility:

• GPR, VFE, SVGP: training inputs order is changed from (y, x) to (x, y) on model __init__()s.
• .predict() functions return the same type as the inputs provided (numpy.ndarray->numpy.ndarray, torch.Tensor->torch.Tensor)
• Remove util.as_variable()
• Remove util.tensor_type()
• Remove util.KL_Gaussian()
• Remove util.gammaln()
• GPModel method .loss() generally replaces .compute_loss().
• .compute_loss() methods in models generally renamed to .log_likelihood() and signs flipped to reflect the fact that the loss is generally the negative LL.

Changes not breaking backward compatibility

• GPR, VFE: Allow specifying training set on .compute_loss() with x, y kwargs
• GPR, VFE: Allow specifying training inputs on ._predict() with x kwarg
• GPU supported with .cuda()
• Remove GPModel.evaluate()
• Don't print inducing inputs on sparse GP initialization
• Suport for priors in gptorch.model.Models

[sdatkinson]

Continue to increase code coverage, but this is definitely useful.