class_docstr: A mixture of a point-mass and another distribution.
  
  Under the hood, this is implemented as a mixture.Mixture, and so
  supports all of the methods of that class.
  
  ### Examples:
  
  ```python
  zinb = Inflated(
           tfd.NegativeBinomial(5.0, probs=0.1), inflated_loc_prob=0.2)
  sample = zinb.sample(seed=jax.random.PRNGKey(0))
  ```
docstr: The log-odds for the point mass part of the distribution.
docstr_tok: ["The","log-odds","for","the","point","mass","part","of","the","distribution","."]
code: def inflated_loc_logits(self):
      """The log-odds for the point mass part of the distribution."""
      return self._inflated_loc_logits
  
imports: import inspect
  import warnings
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import sigmoid
  from tensorflow_probability.python.distributions import categorical
  from tensorflow_probability.python.distributions import deterministic
  from tensorflow_probability.python.distributions import distribution
  from tensorflow_probability.python.distributions import mixture
  from tensorflow_probability.python.distributions import negative_binomial
  from tensorflow_probability.python.internal import auto_composite_tensor
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import parameter_properties
  from tensorflow_probability.python.internal import prefer_static
  from tensorflow_probability.python.internal import samplers
  from tensorflow_probability.python.internal import tensor_util
  from tensorflow_probability.python.util.deferred_tensor import DeferredTensor
label_desc: Use image node_id 6 for calling the _Inflated obj's underlying member method code with example usage: obj.inflated_loc_logits() and returns: self