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 __init__(self, df, validate_args=None):
      super().__init__(0.5 * df, 0.5, validate_args=validate_args)
  
imports: from torch.distributions import constraints
  from torch.distributions.gamma import Gamma
label_desc: Use image node_id 1 to create a new Chi2 object from inherited base classes: Gamma with example: obj = Chi2(df, validate_args)