gpytorchwrapper.src.models.gp_models

Classes

BIMultitaskRBF(train_x, train_y, likelihood)	Multi-output GP with RBF kernel
SingleGPRBF(train_x, train_y, likelihood)	Simple isotropic GP with RBF kernel
SingleGPRBFARD(train_x, train_y, likelihood)	Learn different lengthscales for each feature
TestModel(train_x, train_y, likelihood)	Test model for debugging
TestMultitaskGPModel(train_x, train_y, ...)

class gpytorchwrapper.src.models.gp_models.BIMultitaskRBF(train_x, train_y, likelihood)

Bases: ExactGP

Multi-output GP with RBF kernel

forward(x)

Define the computation performed at every call.

Should be overridden by all subclasses.

Note

Although the recipe for forward pass needs to be defined within this function, one should call the Module instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.

class gpytorchwrapper.src.models.gp_models.SingleGPRBF(train_x, train_y, likelihood)

Bases: ExactGP

Simple isotropic GP with RBF kernel

forward(x)

Define the computation performed at every call.

Should be overridden by all subclasses.

Note

Although the recipe for forward pass needs to be defined within this function, one should call the Module instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.

class gpytorchwrapper.src.models.gp_models.SingleGPRBFARD(train_x, train_y, likelihood)

Bases: ExactGP

Learn different lengthscales for each feature

forward(x)

Define the computation performed at every call.

Should be overridden by all subclasses.

Note

Although the recipe for forward pass needs to be defined within this function, one should call the Module instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.

class gpytorchwrapper.src.models.gp_models.TestModel(train_x, train_y, likelihood)

Bases: ExactGP

Test model for debugging

forward(x)

Define the computation performed at every call.

Should be overridden by all subclasses.

Note

Although the recipe for forward pass needs to be defined within this function, one should call the Module instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.

class gpytorchwrapper.src.models.gp_models.TestMultitaskGPModel(train_x, train_y, likelihood)

Bases: ExactGP

forward(x)

Define the computation performed at every call.

Should be overridden by all subclasses.

Note

Although the recipe for forward pass needs to be defined within this function, one should call the Module instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.