Ë
    P/æjc  ã                   óx   — d dl Z d dlZd dlmZ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infÚnan)ÚChi2Úconstraints)ÚDistribution)Ú_standard_normalÚbroadcast_all)Ú_sizeÚStudentTc                   ó  ‡ — e Zd ZdZej
                  ej                  ej
                  dœZej                  ZdZ	e
d„ «       Ze
d„ «       Ze
d„ «       Zdˆ fd„	Zdˆ fd„	Z ej"                  «       fd	ed
ej&                  fd„Zd„ Zd„ Zˆ xZS )r   a  
    Creates a Student's t-distribution parameterized by degree of
    freedom :attr:`df`, mean :attr:`loc` and scale :attr:`scale`.

    Example::

        >>> # xdoctest: +IGNORE_WANT("non-deterministic")
        >>> m = StudentT(torch.tensor([2.0]))
        >>> m.sample()  # Student's t-distributed with degrees of freedom=2
        tensor([ 0.1046])

    Args:
        df (float or Tensor): degrees of freedom
        loc (float or Tensor): mean of the distribution
        scale (float or Tensor): scale of the distribution
    )ÚdfÚlocÚscaleTc                 ó†   — | j                   j                  t        j                  ¬«      }t        || j
                  dk  <   |S )N©Úmemory_formaté   )r   ÚcloneÚtorchÚcontiguous_formatr   r   ©ÚselfÚms     ú_/root/repos/pocs/video-evals/.venv/lib/python3.12/site-packages/torch/distributions/studentT.pyÚmeanzStudentT.mean(   s2   € à�H‰H�N‰N¬×)@Ñ)@ˆNÓAˆÜˆˆ$�'‰'�Q‰,‰Øˆó    c                 ó   — | j                   S ©N)r   )r   s    r   ÚmodezStudentT.mode.   s   € à�x‰xˆr   c                 óÂ  — | j                   j                  t        j                  ¬«      }| j                  | j                   dkD     j                  d«      | j                   | j                   dkD     z  | j                   | j                   dkD     dz
  z  || j                   dkD  <   t        || j                   dk  | j                   dkD  z  <   t        || j                   dk  <   |S )Nr   é   r   )r   r   r   r   r   Úpowr   r   r   s     r   ÚvariancezStudentT.variance2   sº   € à�G‰G�M‰M¬×(?Ñ(?ˆMÓ@ˆà�J‰J�t—w‘w ‘{Ñ#×'Ñ'¨Ó*Ø�g‰g�d—g‘g ‘kÑ"ñ#à�w‰w�t—w‘w ‘{Ñ# aÑ'ñ)ð 	
ˆ$�'‰'�A‰+‰ô
 -0ˆˆ4�7‰7�a‰<˜DŸG™G a™KÑ
(Ñ)Üˆˆ$�'‰'�Q‰,‰Øˆr   c                 óÐ   •— t        |||«      \  | _        | _        | _        t	        | j                  «      | _        | j                  j                  «       }t        ‰| �!  ||¬«       y )N©Úvalidate_args)	r	   r   r   r   r   Ú_chi2ÚsizeÚsuperÚ__init__)r   r   r   r   r&   Úbatch_shapeÚ	__class__s         €r   r*   zStudentT.__init__>   sN   ø€ Ü(5°b¸#¸uÓ(EÑ%ˆŒ�”˜4œ:Ü˜$Ÿ'™'“]ˆŒ
Ø—g‘g—l‘l“nˆÜ‰Ñ˜°MÐÕBr   c                 óª  •— | j                  t        |«      }t        j                  |«      }| j                  j                  |«      |_        | j                  j                  |«      |_        | j                  j                  |«      |_        | j                  j                  |«      |_        t        t        |�+  |d¬«       | j                  |_        |S )NFr%   )Ú_get_checked_instancer   r   ÚSizer   Úexpandr   r   r'   r)   r*   Ú_validate_args)r   r+   Ú	_instanceÚnewr,   s       €r   r0   zStudentT.expandD   sž   ø€ Ø×(Ñ(¬°9Ó=ˆÜ—j‘j Ó-ˆØ—‘—‘ Ó,ˆŒØ—(‘(—/‘/ +Ó.ˆŒØ—J‘J×%Ñ% kÓ2ˆŒ	Ø—J‘J×%Ñ% kÓ2ˆŒ	ÜŒh˜Ñ% kÀÐ%ÔGØ!×0Ñ0ˆÔØˆ
r   Úsample_shapeÚreturnc                 óH  — | j                  |«      }t        || j                  j                  | j                  j                  ¬«      }| j
                  j                  |«      }|t        j                  || j                  z  «      z  }| j                  | j                  |z  z   S )N)ÚdtypeÚdevice)Ú_extended_shaper   r   r7   r8   r'   Úrsampler   Úrsqrtr   r   )r   r4   ÚshapeÚXÚZÚYs         r   r:   zStudentT.rsampleO   sx   € ð ×$Ñ$ \Ó2ˆÜ˜U¨$¯'©'¯-©-ÀÇÁÇÁÔOˆØ�J‰J×Ñ˜|Ó,ˆØ”—‘˜A §¡™KÓ(Ñ(ˆØ�x‰x˜$Ÿ*™* q™.Ñ(Ð(r   c                 ó:  — | j                   r| j                  |«       || j                  z
  | j                  z  }| j                  j	                  «       d| j
                  j	                  «       z  z   dt        j                  t        j                  «      z  z   t        j                  d| j
                  z  «      z   t        j                  d| j
                  dz   z  «      z
  }d| j
                  dz   z  t        j                  |dz  | j
                  z  «      z  |z
  S )Nç      à?ç      ð?g      à¿g       @)r1   Ú_validate_sampler   r   Úlogr   ÚmathÚpir   ÚlgammaÚlog1p)r   ÚvalueÚyr>   s       r   Úlog_probzStudentT.log_prob]   sä   € Ø×ÒØ×!Ñ! %Ô(Ø�T—X‘XÑ §¡Ñ+ˆà�J‰J�N‰NÓØ�D—G‘G—K‘K“MÑ!ñ"à”D—H‘HœTŸW™WÓ%Ñ%ñ&ô �l‰l˜3 §¡™=Ó)ñ*ô �l‰l˜3 $§'¡'¨C¡-Ñ0Ó1ñ	2ð 	
ð �t—w‘w ‘}Ñ%¬¯©°A°s±F¸T¿W¹WÑ4DÓ(EÑEÈÑIÐIr   c                 óì  — t        j                  d| j                  z  «      t        j                  d«      z   t        j                  d| j                  dz   z  «      z
  }| j                  j                  «       d| j                  dz   z  t        j                  d| j                  dz   z  «      t        j                  d| j                  z  «      z
  z  z   d| j                  j                  «       z  z   |z   S )NrA   r   )r   rG   r   rE   r   rD   Údigamma)r   Úlbetas     r   ÚentropyzStudentT.entropyj   sÐ   € ä�L‰L˜˜tŸw™w™Ó'Ü�k‰k˜#Óñä�l‰l˜3 $§'¡'¨A¡+Ñ.Ó/ñ0ð 	ð �J‰J�N‰NÓØØ�w‰w˜‰{ñä�}‰}˜S D§G¡G¨a¡KÑ0Ó1´E·M±MÀ#ÈÏÉÁ-Ó4PÑPñRñRð �D—G‘G—K‘K“MÑ!ñ	"ð
 ñð	
r   )g        rB   Nr   )Ú__name__Ú
__module__Ú__qualname__Ú__doc__r   ÚpositiveÚrealÚarg_constraintsÚsupportÚhas_rsampleÚpropertyr   r   r#   r*   r0   r   r/   r
   ÚTensorr:   rK   rO   Ú__classcell__)r,   s   @r   r   r      s²   ø„ ñð" ×"Ñ"Ø×ÑØ×%Ñ%ñ€Oð
 ×Ñ€GØ€Kàñó ðð
 ñó ðð ñ	ó ð	õCõ	ð -7¨E¯J©J«Lñ ) Eð )¸U¿\¹\ó )òJö
r   )rE   r   r   r   Útorch.distributionsr   r   Ú torch.distributions.distributionr   Útorch.distributions.utilsr   r	   Útorch.typesr
   Ú__all__r   © r   r   ú<module>rb      s1   ðã ã ß ß 1Ý 9ß EÝ ð ˆ,€ôh
ˆ|õ h
r   