class_docstr: The log-logistic distribution.
class_docstr_tok: ["The","log-logistic","distribution","."]
docstr: Returns log of the standardized input.
docstr_tok: ["Returns","log","of","the","standardized","input","."]
code: def _log_z(self, x, loc=None, scale=None):
      """Returns log of the standardized input."""
      loc = self.loc if loc is None else loc
      scale = self.scale if scale is None else scale
      with tf.name_scope("log_standardize"):
          return (tf.math.log(x) - self.loc) / self.scale
  
imports: import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import exp
  from tensorflow_probability.python.bijectors import softplus
  from tensorflow_probability.python.distributions import logistic
  from tensorflow_probability.python.distributions import transformed_distribution
  from tensorflow_probability.python.internal import assert_util
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import parameter_properties
label_desc: Use image node_id 9 for calling the LogLogistic obj's underlying member method code with example usage: obj._log_z(x, loc, scale) and returns: unknown