
    }Yh0
                         d dl Z d dlmZmZ d dlZd dlmZmZ d dlmZ d dl	m
Z
 d dlmZ d dlmZ dgZ G d	 de          ZdS )
    N)OptionalUnion)infTensor)constraints)Cauchy)TransformedDistribution)AbsTransform
HalfCauchyc                       e Zd ZU dZdej        iZej        ZdZ	e
ed<   	 ddeeef         dee         ddf fdZd f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d Zd Zd Z xZS )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
    scaleT	base_distNvalidate_argsreturnc                     t          d|d          }t                                          |t                      |           d S )Nr   F)r   )r   super__init__r
   )selfr   r   r   	__class__s       q/var/www/tools.fuzzalab.pt/emblema-extractor/venv/lib/python3.11/site-packages/torch/distributions/half_cauchy.pyr   zHalfCauchy.__init__'   sB    
 1e5999	LNN-PPPPP    c                     |                      t          |          }t                                          ||          S )N)	_instance)_get_checked_instancer   r   expand)r   batch_shaper   newr   s       r   r   zHalfCauchy.expand/   s2    ((Y??ww~~kS~999r   c                     | j         j        S N)r   r   r   s    r   r   zHalfCauchy.scale3   s    ~##r   c                     t          j        |                                 t          j        | j        j        | j        j                  S )Ndtypedevice)torchfull_extended_shapemathr   r   r#   r$   r    s    r   meanzHalfCauchy.mean7   s?    z  ""H*":$	
 
 
 	
r   c                 4    t          j        | j                  S r   )r%   
zeros_liker   r    s    r   modezHalfCauchy.mode@   s    
+++r   c                     | j         j        S r   )r   variancer    s    r   r.   zHalfCauchy.varianceD   s    ~&&r   c                 F   | j         r|                     |           t          j        || j        j        j        | j        j        j                  }| j                            |          t          j
        d          z   }t          j        |dk    |t                     }|S )Nr"      r   )_validate_args_validate_sampler%   	as_tensorr   r   r#   r$   log_probr(   logwherer   )r   valuer4   s      r   r4   zHalfCauchy.log_probH   s     	)!!%(((-3DN<P<W
 
 
 >**511DHQKK?;uz8cT::r   c                 z    | j         r|                     |           d| j                            |          z  dz
  S )Nr0      )r1   r2   r   cdf)r   r7   s     r   r:   zHalfCauchy.cdfR   sA     	)!!%(((4>%%e,,,q00r   c                 B    | j                             |dz   dz            S )Nr9   r0   )r   icdf)r   probs     r   r<   zHalfCauchy.icdfW   s     ~""D1H>222r   c                 ^    | j                                         t          j        d          z
  S )Nr0   )r   entropyr(   r5   r    s    r   r?   zHalfCauchy.entropyZ   s#    ~%%''$(1++55r   r   )__name__
__module____qualname____doc__r   positivearg_constraintsnonnegativesupporthas_rsampler   __annotations__r   r   floatr   boolr   r   propertyr   r)   r,   r.   r4   r:   r<   r?   __classcell__)r   s   @r   r   r      s         "  45O%GK
 )-Q QVU]#Q  ~Q 
	Q Q Q Q Q Q: : : : : : $v $ $ $ X$ 
f 
 
 
 X
 ,f , , , X, '& ' ' ' X'  1 1 1
3 3 36 6 6 6 6 6 6r   )r(   typingr   r   r%   r   r   torch.distributionsr   torch.distributions.cauchyr   ,torch.distributions.transformed_distributionr	   torch.distributions.transformsr
   __all__r    r   r   <module>rU      s     " " " " " " " "          + + + + + + - - - - - - P P P P P P 7 7 7 7 7 7 .K6 K6 K6 K6 K6( K6 K6 K6 K6 K6r   