class_docstr: Create a Poisson distribution object.
  
  Parameters
  ----------
  rate : Tensor or scalar, default 1
      rate parameter of the distribution.
code: def variance(self):
      return self.rate
  
file_path: mxnet/python/mxnet/gluon/probability/distributions/poisson.py
imports: from numbers import Number
  from .exp_family import ExponentialFamily
  from .constraint import Positive, NonNegativeInteger
  from .utils import gammaln
  from ....None import np, npx
label_desc: Use image node_id 3 for calling the Poisson obj's underlying member method code with example usage: obj.variance() and returns: self