class_docstr: Base class for Priors in GPyTorch.
  In GPyTorch, a parameter can be assigned a prior by passing it as the `prior` argument to
  :func:`~gpytorch.module.register_parameter`. GPyTorch performs internal bookkeeping of priors,
  and for each parameter with a registered prior includes the log probability of the parameter under its
  respective prior in computing the Marginal Log-Likelihood.
code: def transform(self, x):
      return self._transform(x) if self._transform is not None else x
  
file_path: gpytorch/gpytorch/priors/prior.py
imports: from abc import ABC
  from torch.nn import Module
  from ..distributions import Distribution
label_desc: Use image node_id 1 for calling the Prior obj's underlying member method code with example usage: obj.transform(x) and returns: unknown