class_docstr: Bernoulli distribution.
  
  The Bernoulli distribution with `probs` parameter, i.e., the probability of a
  `1` outcome (vs a `0` outcome).
class_docstr_tok: ["Bernoulli","distribution",".","The","Bernoulli","distribution","with","`","probs","`","parameter",",","i.e.",",","the","probability","of","a","`","1","`","outcome","(","vs","a","`","0","`","outcome",")","."]
docstr: Log-odds of a `1` outcome (vs `0`).
docstr_tok: ["Log-odds","of","a","`","1","`","outcome","(","vs","`","0","`",")","."]
code: def logits(self):
      """Log-odds of a `1` outcome (vs `0`)."""
      return self._logits
  
imports: from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import nn
  from tensorflow.python.ops import random_ops
  from tensorflow.python.ops.distributions import distribution
  from tensorflow.python.ops.distributions import kullback_leibler
  from tensorflow.python.ops.distributions import util
  from tensorflow.python.util import deprecation
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 3 for calling the Bernoulli obj's underlying member method code with example usage: obj.logits() and returns: self