Fix spectrak mixture kernel example.
Fixes
@@ -51,19 +51,15 @@ class SpectralMixtureKernel(Kernel):
The mixture weight parameters (`b x k`).
Example:
+ >>> # Non-batch
>>> x = torch.randn(10, 5)
- >>> # Non-batch: Simple option
- >>> covar_module = gpytorch.kernels.ScaleKernel(gpytorch.kernels.RBFKernel())
- >>> # Non-batch: ARD (different lengthscale for each input dimension)
- >>> covar_module = gpytorch.kernels.ScaleKernel(gpytorch.kernels.RBFKernel(ard_num_dims=5))
+ >>> covar_module = gpytorch.kernels.SpectralMixtureKernel(num_mixtures=4, ard_dum_dims=5)
>>> covar = covar_module(x) # Output: LazyVariable of size (10 x 10)
>>>
+ >>> # Batch
>>> batch_x = torch.randn(2, 10, 5)
- >>> # Batch: Simple option
- >>> covar_module = gpytorch.kernels.ScaleKernel(gpytorch.kernels.RBFKernel())
- >>> # Batch: different lengthscale for each batch
- >>> covar_module = gpytorch.kernels.ScaleKernel(gpytorch.kernels.RBFKernel(batch_size=2))
- >>> covar = covar_module(x) # Output: LazyVariable of size (2 x 10 x 10)
+ >>> covar_module = gpytorch.kernels.SpectralMixtureKernel(num_mixtures=4, batch_size=2, ard_dum_dims=5)
+ >>> covar = covar_module(x) # Output: LazyVariable of size (10 x 10)
.. _Gaussian Process Kernels for Pattern Discovery and Extrapolation:
