class_docstr: Base class for a family of isotropic covariance kernels which are functions of the
  distance :math:`|x-z|/l`, where :math:`l` is the length-scale parameter.
  
  By default, the parameter ``lengthscale`` has size 1. To use the isotropic version
  (different lengthscale for each dimension), make sure that ``lengthscale`` has size
  equal to ``input_dim``.
  
  :param torch.Tensor lengthscale: Length-scale parameter of this kernel.
docstr: Returns :math:`\|\frac{X-Z}{l}\|`.
docstr_tok: ["Returns",":","math",":","`","\\|\\frac","{","X-Z","}","{","l","}","\\|","`","."]
code: def _scaled_dist(self, X, Z=None):
      r"""
      Returns :math:`\|\frac{X-Z}{l}\|`.
      """
      return _torch_sqrt(self._square_scaled_dist(X, Z))
  
imports: import torch
  from torch.distributions import constraints
  from pyro.contrib.gp.kernels.kernel import Kernel
  from pyro.nn.module import PyroParam
label_desc: Use image node_id 3 for calling the Isotropy obj's underlying member method code with example usage: obj._scaled_dist(X, Z) and returns: _torch_sqrt