class_docstr: Abstract base class for all Variational Distributions.
  
  :ivar torch.dtype dtype: The dtype of the VariationalDistribution parameters
  :ivar torch.dtype device: The device of the VariationalDistribution parameters
class_docstr_tok: ["Abstract","base","class","for","all","Variational","Distributions",".",":","ivar","torch.dtype","dtype",":","The","dtype","of","the","VariationalDistribution","parameters",":","ivar","torch.dtype","device",":","The","device","of","the","VariationalDistribution","parameters"]
code: def device(self) -> torch.device:
      return next(self.parameters()).device
  
file_path: gpytorch/gpytorch/variational/_variational_distribution.py
imports: from abc import ABC, abstractmethod
  import torch
  from ..distributions import Distribution, MultivariateNormal
  from ..module import Module
label_desc: Use image node_id 2 for calling the _VariationalDistribution obj's underlying member method code with example usage: obj.device() and returns: next