class_docstr: Create a laplace distribution object.
  
  Parameters
  ----------
  loc : Tensor or scalar, default 0
      mean of the distribution.
  scale : Tensor or scalar, default 1
      scale of the distribution
class_docstr_tok: ["Create","a","laplace","distribution","object",".","Parameters","--","--","--","--","--","loc",":","Tensor","or","scalar",",","default","0","mean","of","the","distribution",".","scale",":","Tensor","or","scalar",",","default","1","scale","of","the","distribution"]
code: def __init__(self, loc=0.0, scale=1.0, validate_args=None):
      self.loc = loc
      self.scale = scale
      super(Laplace, self).__init__(
          event_dim=0, validate_args=validate_args
      )
  
file_path: mxnet/python/mxnet/gluon/probability/distributions/laplace.py
imports: from .constraint import Real, Positive
  from .distribution import Distribution
  from .utils import sample_n_shape_converter
  from ....None import np
label_desc: Use image node_id 1 to create a new Laplace object from inherited base classes: Distribution with example: obj = Laplace(loc, scale, validate_args)