ó
    EñiW  ã                   óx   • S SK r S SKrS SKJrJrJr  S SKJr  S SKJr  S SK	J
r
  S SKJrJr  S/r " S S\5      rg)	é    N)ÚinfÚnanÚTensor)Úconstraints)ÚDistribution)Úbroadcast_all)Ú_NumberÚ_sizeÚCauchyc            	       óL  ^ • \ rS rSrSr\R                  \R                  S.r\R                  r	Sr
 SS\\-  S\\-  S\S-  S	S4U 4S
 jjjrSU 4S jjr\S	\4S j5       r\S	\4S j5       r\S	\4S j5       r\R*                  " 5       4S\S	\4S jjrS rS rS rS rSrU =r$ )r   é   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scaleTNr   r   Úvalidate_argsÚreturnc                 ó  >• [        X5      u  U l        U l        [        U[        5      (       a+  [        U[        5      (       a  [
        R                  " 5       nOU R                  R                  5       n[        TU ]%  XCS9  g )N©r   )
r   r   r   Ú
isinstancer	   ÚtorchÚSizeÚsizeÚsuperÚ__init__)Úselfr   r   r   Úbatch_shapeÚ	__class__s        €ÚW/home/mande/repo/quber/.venv/lib/python3.13/site-packages/torch/distributions/cauchy.pyr   ÚCauchy.__init__&   s[   ø€ ô  -¨SÓ8ÑˆŒ�$”*Ü�cœ7×#Ñ#¬
°5¼'×(BÑ(BÜŸ*š*›,‰KàŸ(™(Ÿ-™-›/ˆKÜ‰Ñ˜ÐÒBó    c                 ó&  >• U R                  [        U5      n[        R                  " U5      nU R                  R                  U5      Ul        U R                  R                  U5      Ul        [        [        U]#  USS9  U R                  Ul	        U$ )NFr   )
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#ÑEØ!×0Ñ0ˆÔØˆ
r   c                 ó¤   • [         R                  " U R                  5       [        U R                  R
                  U R                  R                  S9$ ©N)ÚdtypeÚdevice)r   ÚfullÚ_extended_shaper   r   r)   r*   ©r   s    r   ÚmeanÚCauchy.mean<   ó5   € ä�zŠzØ× Ñ Ó"¤C¨t¯x©x¯~©~ÀdÇhÁhÇoÁoñ
ð 	
r   c                 ó   • U R                   $ ©N)r   r-   s    r   ÚmodeÚCauchy.modeB   s   € à�x‰xˆr   c                 ó¤   • [         R                  " U R                  5       [        U R                  R
                  U R                  R                  S9$ r(   )r   r+   r,   r   r   r)   r*   r-   s    r   ÚvarianceÚCauchy.varianceF   r0   r   Úsample_shapec                 ó¬   • U R                  U5      nU R                  R                  U5      R                  5       nU R                  X0R                  -  -   $ r2   )r,   r   r%   Úcauchy_r   )r   r8   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˜#§
¡
Ñ*Ñ*Ð*r   c                 ó   • U R                   (       a  U R                  U5        [        R                  " [        R                  5      * U R
                  R                  5       -
  XR                  -
  U R
                  -  S-  R                  5       -
  $ )Né   )r#   Ú_validate_sampleÚmathÚlogÚpir   r   Úlog1p©r   Úvalues     r   Úlog_probÚCauchy.log_probQ   sj   € Ø××Ø×!Ñ! %Ô(ä�XŠX”d—g‘gÓÐØ�j‰j�n‰nÓñàŸ™Ñ! T§Z¡ZÑ/°AÑ5×<Ñ<Ó>ñ?ð	
r   c                 óÌ   • U R                   (       a  U R                  U5        [        R                  " XR                  -
  U R
                  -  5      [        R                  -  S-   $ ©Ng      à?)r#   rA   r   Úatanr   r   rB   rD   rF   s     r   ÚcdfÚ
Cauchy.cdfZ   sF   € Ø××Ø×!Ñ! %Ô(Ü�zŠz˜5§8¡8Ñ+¨t¯z©zÑ9Ó:¼T¿W¹WÑDÀsÑJÐJr   c                 óŠ   • [         R                  " [        R                  US-
  -  5      U R                  -  U R
                  -   $ rK   )r   ÚtanrB   rD   r   r   rF   s     r   ÚicdfÚCauchy.icdf_   s0   € Ü�yŠyœŸ™ E¨C¡KÑ0Ó1°D·J±JÑ>ÀÇÁÑIÐIr   c                 ó†   • [         R                  " S[         R                  -  5      U R                  R                  5       -   $ )Né   )rB   rC   rD   r   r-   s    r   ÚentropyÚCauchy.entropyb   s)   € Ü�xŠx˜œDŸG™G™Ó$ t§z¡z§~¡~Ó'7Ñ7Ð7r   r2   )Ú__name__Ú
__module__Ú__qualname__Ú__firstlineno__Ú__doc__r   ÚrealÚpositiveÚarg_constraintsÚsupportÚhas_rsampler   ÚfloatÚboolr   r"   Úpropertyr.   r3   r6   r   r   r
   r=   rH   rM   rQ   rU   Ú__static_attributes__Ú__classcell__)r   s   @r   r   r      s  ø† ñð$ *×.Ñ.¸×9MÑ9MÑN€OØ×Ñ€GØ€Kð &*ñ	Cà�e‰^ðCð ˜‰~ðCð ˜d‘{ð	Cð
 
÷Cð C÷ð ð
�fó 
ó ð
ð
 ð�fó ó ðð ð
˜&ó 
ó ð
ð
 -2¯JªJ«Lñ + Eð +¸Võ +ò

òKò
J÷8ð 8r   )rB   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>rl      s4   ðã ã ß "Ñ "Ý +Ý 9Ý 3ß &ð ˆ*€ôT8ˆ\õ T8r   