
    IЦiw	                     l    S SK r S SKrS SKJr  S SKJr  S SKJr  S SKJr  S SK	J
r
  S/r " S S\5      rg)	    N)inf)constraints)Cauchy)TransformedDistribution)AbsTransform
HalfCauchyc                      ^  \ rS rSrSrS\R                  0r\R                  r	Sr
SU 4S jjrSU 4S jjr\S 5       r\S 5       r\S	 5       r\S
 5       rS rS rS rS rSrU =r$ )r      a  
Creates a half-Cauchy distribution parameterized by `scale` where::

    X ~ Cauchy(0, scale)
    Y = |X| ~ HalfCauchy(scale)

Example::

    >>> # xdoctest: +IGNORE_WANT("non-deterministic")
    >>> m = HalfCauchy(torch.tensor([1.0]))
    >>> m.sample()  # half-cauchy distributed with scale=1
    tensor([ 2.3214])

Args:
    scale (float or Tensor): scale of the full Cauchy distribution
scaleTc                 J   > [        SUSS9n[        TU ]	  U[        5       US9  g )Nr   F)validate_args)r   super__init__r   )selfr   r   	base_dist	__class__s       ^/var/www/html/ai-image-ml/venv/lib/python3.13/site-packages/torch/distributions/half_cauchy.pyr   HalfCauchy.__init__$   s'    1e59	LN-P    c                 J   > U R                  [        U5      n[        TU ]  XS9$ )N)	_instance)_get_checked_instancer   r   expand)r   batch_shaper   newr   s       r   r   HalfCauchy.expand(   s&    ((Y?w~k~99r   c                 .    U R                   R                  $ N)r   r   r   s    r   r   HalfCauchy.scale,   s    ~~###r   c                     [         R                  " U R                  5       [        R                  U R
                  R                  U R
                  R                  S9$ )Ndtypedevice)torchfull_extended_shapemathr   r   r#   r$   r   s    r   meanHalfCauchy.mean0   s@    zz  "HH**""::$$	
 	
r   c                 B    [         R                  " U R                  5      $ r   )r%   
zeros_liker   r   s    r   modeHalfCauchy.mode9   s    

++r   c                 .    U R                   R                  $ r   )r   variancer   s    r   r0   HalfCauchy.variance=   s    ~~&&&r   c                    U R                   (       a  U R                  U5        [        R                  " XR                  R
                  R                  U R                  R
                  R                  S9nU R                  R                  U5      [        R                  " S5      -   n[        R                  " US:  U[        * 5      nU$ )Nr"      r   )_validate_args_validate_sampler%   	as_tensorr   r   r#   r$   log_probr(   logwherer   )r   valuer7   s      r   r7   HalfCauchy.log_probA   s    !!%(--33DNN<P<P<W<W
 >>**51DHHQK?;;uz8cT:r   c                     U R                   (       a  U R                  U5        SU R                  R                  U5      -  S-
  $ )Nr3      )r4   r5   r   cdf)r   r:   s     r   r>   HalfCauchy.cdfK   s8    !!%(4>>%%e,,q00r   c                 D    U R                   R                  US-   S-  5      $ )Nr=   r3   )r   icdf)r   probs     r   rA   HalfCauchy.icdfP   s    ~~""D1H>22r   c                 d    U R                   R                  5       [        R                  " S5      -
  $ )Nr3   )r   entropyr(   r8   r   s    r   rE   HalfCauchy.entropyS   s"    ~~%%'$((1+55r    r   )__name__
__module____qualname____firstlineno____doc__r   positivearg_constraintsnonnegativesupporthas_rsampler   r   propertyr   r)   r-   r0   r7   r>   rA   rE   __static_attributes____classcell__)r   s   @r   r   r      s       4 45O%%GKQ: $ $ 
 
 , , ' '1
36 6r   )r(   r%   r   torch.distributionsr   torch.distributions.cauchyr   ,torch.distributions.transformed_distributionr   torch.distributions.transformsr   __all__r   rG   r   r   <module>rZ      s2       + - P 7 .E6( E6r   