Models for Exact GP Inference¶
ExactGP(train_inputs, train_targets, likelihood)¶
get_fantasy_model(inputs, targets, **kwargs)¶
Returns a new GP model that incorporates the specified inputs and targets as new training data.
Using this method is more efficient than updating with set_train_data when the number of inputs is relatively small, because any computed test-time caches will be updated in linear time rather than computed from scratch.
If targets is a batch (e.g. b x m), then the GP returned from this method will be a batch mode GP.
inputs(Tensor m x d or b x m x d): Locations of fantasy observations.
targets(Tensor m or b x m): Labels of fantasy observations.
- An ExactGP model with n + m training examples, where the m fantasy examples have been added and all test-time caches have been updated.
set_train_data(inputs=None, targets=None, strict=True)¶
Set training data (does not re-fit model hyper-parameters).
inputsthe new training inputs
targetsthe new training targets
- if True, the new inputs and targets must have the same shape, dtype, and device as the current inputs and targets. Otherwise, any shape/dtype/device are allowed.