class_docstr: Creates a Chi-squared distribution parameterized by shape parameter :attr:`df`.
  This is exactly equivalent to ``Gamma(alpha=0.5*df, beta=0.5)``
  
  Example::
  
      >>> # xdoctest: +IGNORE_WANT("non-deterministic")
      >>> m = Chi2(torch.tensor([1.0]))
      >>> m.sample()  # Chi2 distributed with shape df=1
      tensor([ 0.1046])
  
  Args:
      df (float or Tensor): shape parameter of the distribution
code: def expand(self, batch_shape, _instance=None):
      new = self._get_checked_instance(Chi2, _instance)
      return super().expand(batch_shape, new)
  
imports: from torch.distributions import constraints
  from torch.distributions.gamma import Gamma
label_desc: Use image node_id 2 for calling the Chi2 obj's underlying member method code with example usage: obj.expand(batch_shape, _instance) and returns: super