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# Source code for torch.distributions.chi2

    from torch.distributions import constraints
    from torch.distributions.gamma import Gamma

    __all__ = ["Chi2"]

    class Chi2(Gamma):
        r"""
        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-deterinistic")
            >>> 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
        """
        arg_constraints = {"df": constraints.positive}

        def __init__(self, df, validate_args=None):
            super().__init__(0.5 * df, 0.5, validate_args=validate_args)

        def expand(self, batch_shape, _instance=None):
            new = self._get_checked_instance(Chi2, _instance)
            return super().expand(batch_shape, new)

        @property
        def df(self):
            return self.concentration * 2

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