Ë
    *êñiº  ã                   óŒ   — d dl Z d dlZd dlmZ d dlmZ d dlmZ d dlmZm	Z	 d dl
mZ d dlmZmZ d dlmZ d	gZ G d
„ d	e«      Zy)é    N)ÚTensor)Úconstraints)ÚTransformedDistribution)ÚAffineTransformÚExpTransform)ÚUniform)Úbroadcast_allÚeuler_constant)Ú_NumberÚGumbelc            	       ó  ‡ — e Zd ZdZej
                  ej                  dœZej
                  Z	 dde	e
z  de	e
z  dedz  ddfˆ fd„Zdˆ fd	„	Zd
„ Zede	fd„«       Zede	fd„«       Zede	fd„«       Zede	fd„«       Zd„ Zˆ xZS )r   a·  
    Samples from a Gumbel Distribution.

    Examples::

        >>> # xdoctest: +IGNORE_WANT("non-deterministic")
        >>> m = Gumbel(torch.tensor([1.0]), torch.tensor([2.0]))
        >>> m.sample()  # sample from Gumbel distribution with loc=1, scale=2
        tensor([ 1.0124])

    Args:
        loc (float or Tensor): Location parameter of the distribution
        scale (float or Tensor): Scale parameter of the distribution
    ©ÚlocÚscaleNr   r   Úvalidate_argsÚreturnc                 óÎ  •— t        ||«      \  | _        | _        t        j                  | j                  j
                  «      }t        |t        «      r6t        |t        «      r&t        |j                  d|j                  z
  |¬«      }nat        t        j                  | j                  |j                  «      t        j                  | j                  d|j                  z
  «      |¬«      }t        «       j                  t        dt        j                  | j                  «       ¬«      t        «       j                  t        || j                   ¬«      g}t         ‰| �E  |||¬«       y )Né   )r   r   r   )r	   r   r   ÚtorchÚfinfoÚdtypeÚ
isinstancer   r   ÚtinyÚepsÚ	full_liker   Úinvr   Ú	ones_likeÚsuperÚ__init__)Úselfr   r   r   r   Ú	base_distÚ
transformsÚ	__class__s          €ú\/var/www/pod-logistic/pod-ai/venv/lib/python3.12/site-packages/torch/distributions/gumbel.pyr   zGumbel.__init__%   sù   ø€ ô  -¨S°%Ó8ÑˆŒ�$”*Ü—‘˜DŸH™HŸN™NÓ+ˆÜ�cœ7Ô#¬
°5¼'Ô(BÜ §
¡
¨A°·	±	©MÈÔW‰IäÜ—‘ §¡¨%¯*©*Ó5Ü—‘ §¡¨!¨e¯i©i©-Ó8Ø+ôˆIô ‹N×ÑÜ ¬%¯/©/¸$¿*¹*Ó*EÐ)EÔFÜ‹N×ÑÜ ¨D¯J©J¨;Ô7ð	
ˆ
ô 	‰Ñ˜ J¸mÐÕLó    c                 óÒ   •— | j                  t        |«      }| j                  j                  |«      |_        | j                  j                  |«      |_        t
        ‰| �  ||¬«      S )N)Ú	_instance)Ú_get_checked_instancer   r   Úexpandr   r   )r    Úbatch_shaper'   Únewr#   s       €r$   r)   zGumbel.expand=   sR   ø€ Ø×(Ñ(¬°Ó;ˆØ—(‘(—/‘/ +Ó.ˆŒØ—J‘J×%Ñ% kÓ2ˆŒ	Ü‰w‰~˜k°Sˆ~Ó9Ð9r%   c                 óÐ   — | j                   r| j                  |«       | j                  |z
  | j                  z  }||j	                  «       z
  | j                  j                  «       z
  S ©N)Ú_validate_argsÚ_validate_sampler   r   ÚexpÚlog)r    ÚvalueÚys      r$   Úlog_probzGumbel.log_probD   sP   € Ø×ÒØ×!Ñ! %Ô(Ø�X‰X˜Ñ §¡Ñ+ˆØ�A—E‘E“G‘˜tŸz™zŸ~™~Ó/Ñ/Ð/r%   c                 óB   — | j                   | j                  t        z  z   S r-   )r   r   r
   ©r    s    r$   ÚmeanzGumbel.meanJ   s   € à�x‰x˜$Ÿ*™*¤~Ñ5Ñ5Ð5r%   c                 ó   — | j                   S r-   )r   r6   s    r$   ÚmodezGumbel.modeN   s   € à�x‰xˆr%   c                 óh   — t         j                  t        j                  d«      z  | j                  z  S )Né   )ÚmathÚpiÚsqrtr   r6   s    r$   ÚstddevzGumbel.stddevR   s"   € ä—‘œ$Ÿ)™) A›,Ñ&¨$¯*©*Ñ4Ð4r%   c                 ó8   — | j                   j                  d«      S )Né   )r?   Úpowr6   s    r$   ÚvariancezGumbel.varianceV   s   € à�{‰{�‰˜qÓ!Ð!r%   c                 óJ   — | j                   j                  «       dt        z   z   S )Nr   )r   r1   r
   r6   s    r$   ÚentropyzGumbel.entropyZ   s   € Ø�z‰z�~‰~Ó 1¤~Ñ#5Ñ6Ð6r%   r-   )Ú__name__Ú
__module__Ú__qualname__Ú__doc__r   ÚrealÚpositiveÚarg_constraintsÚsupportr   ÚfloatÚboolr   r)   r4   Úpropertyr7   r9   r?   rC   rE   Ú__classcell__)r#   s   @r$   r   r      sç   ø„ ñð *×.Ñ.¸×9MÑ9MÑN€Oà×Ñ€Gð &*ñ	Mà�e‰^ðMð ˜‰~ðMð ˜d‘{ð	Mð
 
õMõ0:ò0ð ð6�fò 6ó ð6ð ð�fò ó ðð ð5˜ò 5ó ð5ð ð"˜&ò "ó ð"ö7r%   )r<   r   r   Útorch.distributionsr   Ú,torch.distributions.transformed_distributionr   Útorch.distributions.transformsr   r   Útorch.distributions.uniformr   Útorch.distributions.utilsr	   r
   Útorch.typesr   Ú__all__r   © r%   r$   ú<module>rZ      s8   ðã ã Ý Ý +Ý Pß HÝ /ß CÝ ð ˆ*€ôJ7Ð$õ J7r%   