gpflow.models.gplvm#
Functions#
gpflow.models.gplvm.data_input_to_tensor#
- gpflow.models.gplvm.data_input_to_tensor(structure)[source]#
Converts non-tensor elements of a structure to TensorFlow tensors retaining the structure itself.
The function doesn’t keep original element’s dtype and forcefully converts them to GPflow’s default float type.
- Parameters
structure (
Any) –- Return type
Any
gpflow.models.gplvm.inducingpoint_wrapper#
- gpflow.models.gplvm.inducingpoint_wrapper(inducing_variable)[source]#
This wrapper allows transparently passing either an InducingVariables object or an array specifying InducingPoints positions.
- Parameters
inducing_variable (
Union[InducingVariables,Tensor,ndarray[Any,Any]]) –- Return type
gpflow.models.gplvm.pca_reduce#
- gpflow.models.gplvm.pca_reduce(X, latent_dim)[source]#
A helpful function for linearly reducing the dimensionality of the input points X to latent_dim dimensions.
- Parameters
X (
Tensor) – data array of size N (number of points) x D (dimensions)latent_dim (
Tensor) – Number of latent dimensions Q < D
- Return type
Tensor- Returns
PCA projection array of size [N, Q].