class_docstr: The log-normal distribution.
class_docstr_tok: ["The","log-normal","distribution","."]
docstr: Distribution parameter for the pre-transformed standard deviation.
docstr_tok: ["Distribution","parameter","for","the","pre-transformed","standard","deviation","."]
code: def scale(self):
      """Distribution parameter for the pre-transformed standard deviation."""
      return self.distribution.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 kullback_leibler
  from tensorflow_probability.python.distributions import normal
  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
  from tensorflow_probability.python.internal import tensor_util
  from tensorflow_probability.python.util.deferred_tensor import DeferredTensor
label_desc: Use image node_id 4 for calling the LogNormal obj's underlying member method code with example usage: obj.scale() and returns: self