class_docstr: A container module to build a DSPP
  This module should contain :obj:`~gpytorch.models.deep_gps.DSPPLayer`
  modules, and can also contain other modules as well.
  
  This Module contains an additional set of parameters, `raw_quad_weights`, that represent the mixture weights for
  the output distribution.
class_docstr_tok: ["A","container","module","to","build","a","DSPP","This","module","should","contain",":","obj",":","`","~gpytorch.models.deep_gps.DSPPLayer","`","modules",",","and","can","also","contain","other","modules","as","well",".","This","Module","contains","an","additional","set","of","parameters",",","`","raw_quad_weights","`",",","that","represent","the","mixture","weights","for","the","output","distribution","."]
code: def quad_weights(self):
      qwd = self.raw_quad_weights
      return qwd - qwd.logsumexp(dim=-1)
  
file_path: gpytorch/gpytorch/models/deep_gps/dspp.py
imports: import torch
  from linear_operator.operators import BlockDiagLinearOperator
  from ...None import settings
  from ...distributions import MultitaskMultivariateNormal
  from ..approximate_gp import ApproximateGP
  from .deep_gp import DeepGP, DeepGPLayer
label_desc: Use image node_id 2 for calling the DSPP obj's underlying member method code with example usage: obj.quad_weights() and returns: unknown