class_docstr: The Laplace distribution with location `loc` and `scale` parameters.
  
  #### Mathematical details
  
  The probability density function (pdf) of this distribution is,
  
  ```none
  pdf(x; mu, sigma) = exp(-|x - mu| / sigma) / Z
  Z = 2 sigma
  ```
  
  where `loc = mu`, `scale = sigma`, and `Z` is the normalization constant.
  
  Note that the Laplace distribution can be thought of two exponential
  distributions spliced together "back-to-back."
  
  The Lpalce distribution is a member of the [location-scale family](
  https://en.wikipedia.org/wiki/Location-scale_family), i.e., it can be
  constructed as,
  
  ```none
  X ~ Laplace(loc=0, scale=1)
  Y = loc + scale * X
  ```
code: def _stddev(self):
      return math.sqrt(2.0) * self.scale + array_ops.zeros_like(
          self.loc
      )
  
imports: import math
  import numpy
  from tensorflow.python.framework import constant_op
  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 check_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 special_math
  from tensorflow.python.util import deprecation
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 19 for calling the Laplace obj's underlying member method code with example usage: obj._stddev() and returns: unknown