+
    É&jÚ	  ã                   ó†   € ^ RI Ht ^ RIHt ^ RIHt ^ RIHt ^ RIH	t	 ^ RI
HtHt ^ RIHt ^ RIHt R	.t ! R
 R	]	4      tR# )é    )ÚOptional©ÚTensor)Úconstraints)ÚExponential)ÚTransformedDistribution)ÚAffineTransformÚExpTransform)Úbroadcast_all)Ú_sizeÚParetoc                   ó<  a a€ ] tR t^t oRtR]P                  R]P                  /tRV3R lV 3R llltRV3R lV 3R l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                  ! R^ R7      V3R lR l4       tV3R lR ltRtVtV ;t# )r   a›  
Samples from a Pareto Type 1 distribution.

Example::

    >>> # xdoctest: +IGNORE_WANT("non-deterministic")
    >>> m = Pareto(torch.tensor([1.0]), torch.tensor([1.0]))
    >>> m.sample()  # sample from a Pareto distribution with scale=1 and alpha=1
    tensor([ 1.5623])

Args:
    scale (float or Tensor): Scale parameter of the distribution
    alpha (float or Tensor): Shape parameter of the distribution
ÚalphaÚscalec                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   "€Úr/Users/jameslopez/projects/CWCArchive/cwc-podcast/.venv/lib/python3.14/site-packages/torch/distributions/pareto.pyÚ__annotate__ÚPareto.__annotate__!   sE   ø€ ÷ 
Mñ 
Má™~ð
Mñ ™~ð
Mñ ˜d•{ð	
Mð
 
ñ
Mó    c                óÊ   <€ \        W4      w  V n        V n        \        V P                  VR 7      p\	        4       \        ^ V P                  R7      .p\        SV `  WEVR 7       R# ))r   )Úlocr   N)r   r   r   r   r
   r	   ÚsuperÚ__init__)Úselfr   r   r   Ú	base_distÚ
transformsÚ	__class__s   &&&&  €r   r    ÚPareto.__init__!   sQ   ø€ ô "/¨uÓ!<ÑˆŒ
D”JÜ §
¡
¸-ÔHˆ	Ü"“n¤o¸!À4Ç:Á:Ô&NÐOˆ
ä‰Ñ˜¸mÐÖLr   c                ó8   <€ V ^8„  d   QhRS[ RS[R,          RR/# )r   Úbatch_shapeÚ	_instancer   r   )r   r   )r   r   s   "€r   r   r   -   s*   ø€ ÷ :ñ :Ù ð:Ù-5°hÕ-?ð:à	ñ:r   c                óÐ   <€ V P                  \        V4      pV P                  P                  V4      Vn        V P                  P                  V4      Vn        \
        SV `  WR 7      # ))r(   )Ú_get_checked_instancer   r   Úexpandr   r   )r!   r'   r(   Únewr$   s   &&& €r   r+   ÚPareto.expand-   sT   ø€ ð ×(Ñ(¬°Ó;ˆØ—J‘J×%Ñ% kÓ2ˆŒ	Ø—J‘J×%Ñ% kÓ2ˆŒ	Ü‰w‰~˜kˆ~Ó9Ð9r   c                ó    <€ V ^8„  d   QhRS[ /# ©r   r   r   )r   r   s   "€r   r   r   6   s   ø€ ÷ (ñ (‘fñ (r   c                óz   € V P                   P                  ^R7      pWP                  ,          V^,
          ,          # )é   ©Úmin)r   Úclampr   ©r!   Úas   & r   ÚmeanÚPareto.mean5   s0   € ð J‰J×Ñ ÐÓ#ˆØ—:‘:~  Q¥Õ'Ð'r   c                ó    <€ V ^8„  d   QhRS[ /# r/   r   )r   r   s   "€r   r   r   <   s   ø€ ÷ ñ ‘fñ r   c                ó   € V P                   # ©N)r   ©r!   s   &r   ÚmodeÚPareto.mode;   s   € àz‰zÐr   c                ó    <€ V ^8„  d   QhRS[ /# r/   r   )r   r   s   "€r   r   r   @   s   ø€ ÷ Bñ B™&ñ Br   c                óÔ   € V P                   P                  ^R7      pV P                  P                  ^4      V,          V^,
          P                  ^4      V^,
          ,          ,          # )r   r2   )r   r4   r   Úpowr5   s   & r   ÚvarianceÚPareto.variance?   sM   € ð J‰J×Ñ ÐÓ#ˆØz‰z~‰~˜aÓ  1Õ$¨¨Q­¯©°A«¸!¸a½%Õ(@ÕAÐAr   F)Úis_discreteÚ	event_dimc                ó4   <€ V ^8„  d   QhRS[ P                  /# r/   )r   Ú
Constraint)r   r   s   "€r   r   r   F   s   ø€ ÷ 7ñ 7™×/Ñ/ñ 7r   c                óB   € \         P                  ! V P                  4      # r;   )r   Úgreater_than_eqr   r<   s   &r   ÚsupportÚPareto.supportE   s   € ä×*Ò*¨4¯:©:Ó6Ð6r   c                ó    <€ V ^8„  d   QhRS[ /# r/   r   )r   r   s   "€r   r   r   I   s   ø€ ÷ Oñ O™ñ Or   c                ó¤   € V P                   V P                  ,          P                  4       ^V P                  P                  4       ,           ,           # )r1   )r   r   ÚlogÚ
reciprocalr<   s   &r   ÚentropyÚPareto.entropyI   s5   € Ø—
‘
˜TŸZ™ZÕ'×,Ñ,Ó.°!°d·j±j×6KÑ6KÓ6MÕ2MÕNÐNr   )r   r   r;   )Ú__name__Ú
__module__Ú__qualname__Ú__firstlineno__Ú__doc__r   ÚpositiveÚarg_constraintsr    r+   Úpropertyr7   r=   rB   Údependent_propertyrJ   rP   Ú__static_attributes__Ú__classdictcell__Ú__classcell__)r$   r   s   @@r   r   r      s®   ù‡ € ñð  × 4Ñ 4°g¸{×?SÑ?SÐT€O÷
Mõ 
M÷:õ :ð ÷(ó ð(ð
 ÷ó ðð ÷Bó ðBð
 ×#Ò#°ÀÔC÷7ó Dð7÷O÷ Oð Or   N)Útypingr   Útorchr   Útorch.distributionsr   Útorch.distributions.exponentialr   Ú,torch.distributions.transformed_distributionr   Útorch.distributions.transformsr	   r
   Útorch.distributions.utilsr   Útorch.typesr   Ú__all__r   © r   r   Ú<module>rh      s5   ðÝ å Ý +Ý 7Ý Pß HÝ 3Ý ð ˆ*€ô;OÐ$ö ;Or   