class_docstr: Create a relaxed one hot categorical distribution object.
  
  Parameters
  ----------
  T : scalar, default None
      Relaxation temperature
  num_events : Int
      Number of events.
  prob : Tensor
      Probabilities of each event.
  logit : Tensor
      The log-odds of each event
class_docstr_tok: ["Create","a","relaxed","one","hot","categorical","distribution","object",".","Parameters","--","--","--","--","--","T",":","scalar",",","default","None","Relaxation","temperature","num_events",":","Int","Number","of","events",".","prob",":","Tensor","Probabilities","of","each","event",".","logit",":","Tensor","The","log-odds","of","each","event"]
code: def logit(self):
      return self._base_dist.logit
  
file_path: mxnet/python/mxnet/gluon/probability/distributions/relaxed_one_hot_categorical.py
imports: from math import lgamma
  from .distribution import Distribution
  from .transformed_distribution import TransformedDistribution
  from ..transformation import ExpTransform
  from .utils import prob2logit, logit2prob, cached_property
  from .constraint import Real, Simplex
  from ....None import np, npx
label_desc: Use image node_id 4 for calling the RelaxedOneHotCategorical obj's underlying member method code with example usage: obj.logit() and returns: self