+
    –°³jW  ã                   óz   € ^ RI t ^ RIt^ RIHtHtHt ^ RIHt ^ RIHt ^ RI	H
t
 ^ RIHtHt R.t ! R R]4      tR# )	é    N)ÚinfÚnanÚTensor)Úconstraints)ÚDistribution)Úbroadcast_all)Ú_NumberÚ_sizeÚCauchyc                   óH  a a€ ] tR t^t oRtR]P                  R]P                  /t]P                  t	Rt
RV3R lV 3R llltRV 3R llt]V3R lR	 l4       t]V3R
 lR l4       t]V3R lR l4       t]P$                  ! 4       3V3R lR lltR tR tR tR tRtVtV ;t# )r   a  
Samples from a Cauchy (Lorentz) distribution. The distribution of the ratio of
independent normally distributed random variables with means `0` follows a
Cauchy distribution.

Example::

    >>> # xdoctest: +IGNORE_WANT("non-deterministic")
    >>> m = Cauchy(torch.tensor([0.0]), torch.tensor([1.0]))
    >>> m.sample()  # sample from a Cauchy distribution with loc=0 and scale=1
    tensor([ 2.3214])

Args:
    loc (float or Tensor): mode or median of the distribution.
    scale (float or Tensor): half width at half maximum.
ÚlocÚscaleTc                ó^   <€ V ^8„  d   QhRS[ S[,          RS[ S[,          RS[R,          RR/# )é   r   r   Úvalidate_argsNÚreturn)r   ÚfloatÚbool)ÚformatÚ__classdict__s   "€Ú[/home/luca/screen-checking/.venv/lib/python3.14/site-packages/torch/distributions/cauchy.pyÚ__annotate__ÚCauchy.__annotate__&   sE   ø€ ÷ Cñ Cá‘e�^ðCñ ™�~ðCñ ˜d•{ð	Cð
 
ñCó    c                ó  <€ \        W4      w  V n        V n        \        V\        4      '       d-   \        V\        4      '       d   \
        P                  ! 4       pMV P                  P                  4       p\        SV `%  WCR 7       R# )©r   N)
r   r   r   Ú
isinstancer	   ÚtorchÚSizeÚsizeÚsuperÚ__init__)Úselfr   r   r   Úbatch_shapeÚ	__class__s   &&&& €r   r"   ÚCauchy.__init__&   s[   ø€ ô  -¨SÓ8ÑˆŒ�$”*Ü�cœ7×#Ò#¬
°5¼'×(BÒ(BÜŸ*š*›,‰KàŸ(™(Ÿ-™-›/ˆKÜ‰Ñ˜ÐÖBr   c                ó,  <€ V P                  \        V4      p\        P                  ! V4      pV P                  P                  V4      Vn        V P                  P                  V4      Vn        \        \        V`#  VR R7       V P                  Vn	        V# )Fr   )
Ú_get_checked_instancer   r   r   r   Úexpandr   r!   r"   Ú_validate_args)r#   r$   Ú	_instanceÚnewr%   s   &&& €r   r)   ÚCauchy.expand3   st   ø€ Ø×(Ñ(¬°Ó;ˆÜ—j’j Ó-ˆØ—(‘(—/‘/ +Ó.ˆŒØ—J‘J×%Ñ% kÓ2ˆŒ	ÜŒf�cÑ# K¸uÐ#ÔEØ!×0Ñ0ˆÔØˆ
r   c                ó    <€ V ^8„  d   QhRS[ /# ©r   r   ©r   )r   r   s   "€r   r   r   =   s   ø€ ÷ 
ñ 
‘fñ 
r   c                óª   € \         P                  ! V P                  4       \        V P                  P
                  V P                  P                  R 7      # ©)ÚdtypeÚdevice)r   ÚfullÚ_extended_shaper   r   r3   r4   ©r#   s   &r   ÚmeanÚCauchy.mean<   ó5   € ä�zŠzØ× Ñ Ó"¤C¨t¯x©x¯~©~ÀdÇhÁhÇoÁoô
ð 	
r   c                ó    <€ V ^8„  d   QhRS[ /# r/   r0   )r   r   s   "€r   r   r   C   s   ø€ ÷ ñ ‘fñ r   c                ó   € V P                   # ©N)r   r7   s   &r   ÚmodeÚCauchy.modeB   s   € à�x‰xˆr   c                ó    <€ V ^8„  d   QhRS[ /# r/   r0   )r   r   s   "€r   r   r   G   s   ø€ ÷ 
ñ 
™&ñ 
r   c                óª   € \         P                  ! V P                  4       \        V P                  P
                  V P                  P                  R 7      # r2   )r   r5   r6   r   r   r3   r4   r7   s   &r   ÚvarianceÚCauchy.varianceF   r:   r   c                ó&   <€ V ^8„  d   QhRS[ RS[/# )r   Úsample_shaper   )r
   r   )r   r   s   "€r   r   r   L   s   ø€ ÷ +ñ +¡Eð +¹Vñ +r   c                ó¼   € V P                  V4      pV P                  P                  V4      P                  4       pV P                  W0P                  ,          ,           # r=   )r6   r   r,   Úcauchy_r   )r#   rE   ÚshapeÚepss   &&  r   ÚrsampleÚCauchy.rsampleL   sC   € Ø×$Ñ$ \Ó2ˆØ�h‰h�l‰l˜5Ó!×)Ñ)Ó+ˆØ�x‰x˜#§
¡
Õ*Õ*Ð*r   c                óJ  € V P                   '       d   V P                  V4       \        P                  ! \        P                  4      ) V P
                  P                  4       ,
          WP                  ,
          V P
                  ,          ^,          P                  4       ,
          # )r   )r*   Ú_validate_sampleÚmathÚlogÚpir   r   Úlog1p©r#   Úvalues   &&r   Úlog_probÚCauchy.log_probQ   sm   € Ø××ÐØ×!Ñ! %Ô(ä�XŠX”d—g‘gÓÐØ�j‰j�n‰nÓõàŸ™Õ! T§Z¡ZÕ/°AÕ5×<Ñ<Ó>õ?ð	
r   c                óî   € V P                   '       d   V P                  V4       \        P                  ! WP                  ,
          V P
                  ,          4      \        P                  ,          R ,           # ©g      à?)r*   rM   r   Úatanr   r   rN   rP   rR   s   &&r   ÚcdfÚ
Cauchy.cdfZ   sI   € Ø××ÐØ×!Ñ! %Ô(Ü�zŠz˜5§8¡8Õ+¨t¯z©zÕ9Ó:¼T¿W¹WÕDÀsÕJÐJr   c                óª   € \         P                  ! \        P                  VR ,
          ,          4      V P                  ,          V P
                  ,           # rW   )r   ÚtanrN   rP   r   r   rR   s   &&r   ÚicdfÚCauchy.icdf_   s0   € Ü�yŠyœŸ™ E¨C¥KÕ0Ó1°D·J±JÕ>ÀÇÁÕIÐIr   c                ó–   € \         P                  ! ^\         P                  ,          4      V P                  P                  4       ,           # )é   )rN   rO   rP   r   r7   s   &r   ÚentropyÚCauchy.entropyb   s)   € Ü�xŠx˜œDŸG™G�Ó$ t§z¡z§~¡~Ó'7Õ7Ð7r   )r   r   r=   )Ú__name__Ú
__module__Ú__qualname__Ú__firstlineno__Ú__doc__r   ÚrealÚpositiveÚarg_constraintsÚsupportÚhas_rsampler"   r)   Úpropertyr8   r>   rB   r   r   rJ   rT   rY   r]   ra   Ú__static_attributes__Ú__classdictcell__Ú__classcell__)r%   r   s   @@r   r   r      s³   ù‡ € ñð$ ˜k×.Ñ.°¸×9MÑ9MÐN€OØ×Ñ€GØ€K÷Cõ C÷ð ÷
ó ð
ð
 ÷ó ðð ÷
ó ð
ð
 -2¯JªJ«L÷ +ò +ò

òKò
J÷8ò 8r   )rN   r   r   r   r   Útorch.distributionsr   Ú torch.distributions.distributionr   Útorch.distributions.utilsr   Útorch.typesr	   r
   Ú__all__r   © r   r   Ú<module>rw      s4   ðã ã ß "Ñ "Ý +Ý 9Ý 3ß &ð ˆ*€ôT8ˆ\ö T8r   