ó
    IÐ¦iê  ã                   ó8   • S SK Jr  S SKJr  S/r " S S\5      rg)é    )Úconstraints)ÚGammaÚChi2c                   ól   ^ • \ rS rSrSrS\R                  0rSU 4S jjrSU 4S jjr	\
S 5       rSrU =r$ )	r   é	   a‹  
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
Údfc                 ó*   >• [         TU ]  SU-  SUS9  g )Ng      à?)Úvalidate_args)ÚsuperÚ__init__)Úselfr   r
   Ú	__class__s      €ÚW/var/www/html/ai-image-ml/venv/lib/python3.13/site-packages/torch/distributions/chi2.pyr   ÚChi2.__init__   s   ø€ Ü‰Ñ˜˜r™ 3°mÐÒDó    c                 óN   >• U R                  [        U5      n[        TU ]  X5      $ ©N)Ú_get_checked_instancer   r   Úexpand)r   Úbatch_shapeÚ	_instanceÚnewr   s       €r   r   ÚChi2.expand   s$   ø€ Ø×(Ñ(¬¨yÓ9ˆÜ‰w‰~˜kÓ/Ð/r   c                 ó    • U R                   S-  $ )Né   )Úconcentration)r   s    r   r   ÚChi2.df!   s   € à×!Ñ! AÑ%Ð%r   © r   )Ú__name__Ú
__module__Ú__qualname__Ú__firstlineno__Ú__doc__r   ÚpositiveÚarg_constraintsr   r   Úpropertyr   Ú__static_attributes__Ú__classcell__)r   s   @r   r   r   	   s9   ø† ñð ˜[×1Ñ1Ð2€O÷E÷0ð ñ&ó ö&r   N)Útorch.distributionsr   Útorch.distributions.gammar   Ú__all__r   r   r   r   Ú<module>r,      s    ðå +Ý +ð ˆ(€ô&ˆ5õ &r   