syne_tune.optimizer.schedulers.searchers.bayesopt.gpautograd.kernel.range_kernel module

class syne_tune.optimizer.schedulers.searchers.bayesopt.gpautograd.kernel.range_kernel.RangeKernelFunction(dimension, kernel, start, **kwargs)[source]

Bases: KernelFunction

Given kernel function K and range R, this class represents

\[(x, y) \mapsto K(x_R, y_R)\]
forward(X1, X2)[source]

Overrides to implement forward computation using NDArray. Only accepts positional arguments. Parameters ———- *args : list of NDArray

Input tensors.

diagonal(X)[source]
Parameters:

X – Input data, shape (n, d)

Returns:

Diagonal of \(k(X, X)\), shape (n,)

diagonal_depends_on_X()[source]

For stationary kernels, diagonal does not depend on X

Returns:

Does diagonal() depend on X?

param_encoding_pairs()[source]

Note: We assume that K1 and K2 have disjoint parameters, otherwise there will be a redundancy here.

get_params()[source]
Return type:

Dict[str, Any]

Returns:

Dictionary with hyperparameter values

set_params(param_dict)[source]
Parameters:

param_dict (Dict[str, Any]) – Dictionary with new hyperparameter values

Returns: