
    rh                     x    d dl mZm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
 d dlmZmZ dgZ G d	 de      Zy)
    )OptionalUnionN)Tensor)constraints)Distribution)broadcast_all)_Number_sizeLaplacec            	       N    e Zd ZdZej
                  ej                  dZej
                  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d
eeef   deeef   dee   dd	f fdZd fd	Z ej.                         fdedefdZd Zd Zd Zd Z xZS )r   a  
    Creates a Laplace distribution parameterized by :attr:`loc` and :attr:`scale`.

    Example::

        >>> # xdoctest: +IGNORE_WANT("non-deterministic")
        >>> m = Laplace(torch.tensor([0.0]), torch.tensor([1.0]))
        >>> m.sample()  # Laplace distributed with loc=0, scale=1
        tensor([ 0.1046])

    Args:
        loc (float or Tensor): mean of the distribution
        scale (float or Tensor): scale of the distribution
    )locscaleTreturnc                     | j                   S Nr   selfs    n/var/www/html/ai-insurance-compliance-backend/venv/lib/python3.12/site-packages/torch/distributions/laplace.pymeanzLaplace.mean#       xx    c                     | j                   S r   r   r   s    r   modezLaplace.mode'   r   r   c                 >    d| j                   j                  d      z  S N   )r   powr   s    r   variancezLaplace.variance+   s    4::>>!$$$r   c                      d| j                   z  S )Ng;f?)r   r   s    r   stddevzLaplace.stddev/   s    $**$$r   Nr   r   validate_argsc                     t        ||      \  | _        | _        t        |t              r%t        |t              rt        j                         }n| j                  j                         }t        | %  ||       y )Nr"   )
r   r   r   
isinstancer	   torchSizesizesuper__init__)r   r   r   r"   batch_shape	__class__s        r   r*   zLaplace.__init__3   sY      -S%8$*c7#
5'(B**,K((--/KMBr   c                 *   | j                  t        |      }t        j                  |      }| j                  j                  |      |_        | j                  j                  |      |_        t        t        |#  |d       | j                  |_	        |S )NFr$   )
_get_checked_instancer   r&   r'   r   expandr   r)   r*   _validate_args)r   r+   	_instancenewr,   s       r   r/   zLaplace.expand@   st    (()<jj-((//+.JJ%%k2	gs$[$F!00
r   sample_shapec                    | j                  |      }t        j                  | j                  j                        }t        j
                  j                         rt        j                  || j                  j                  | j                  j                        dz  dz
  }| j                  | j                  |j                         z  t        j                  |j                         j                  |j                               z  z
  S | j                  j                  |      j!                  |j"                  dz
  d      }| j                  | j                  |j                         z  t        j                  |j                                z  z
  S )N)dtypedevicer      )min)_extended_shaper&   finfor   r5   _C_get_tracing_staterandr6   r   signlog1pabsclamptinyr2   uniform_eps)r   r3   shaper:   us        r   rsamplezLaplace.rsampleI   s   $$\2DHHNN+88&&(

5txxORSSVWWA88djj16683ekk5::..7    HHLL((Q: xx$**qvvx/%++quuwh2GGGGr   c                     | j                   r| j                  |       t        j                  d| j                  z         t        j
                  || j                  z
        | j                  z  z
  S r   )r0   _validate_sampler&   logr   r@   r   r   values     r   log_probzLaplace.log_probW   sS    !!%(		!djj.))EIIedhh6F,G$**,TTTr   c                     | j                   r| j                  |       dd|| j                  z
  j                         z  t	        j
                  || j                  z
  j                          | j                  z        z  z
  S )N      ?)r0   rI   r   r>   r&   expm1r@   r   rK   s     r   cdfzLaplace.cdf\   sp    !!%(SEDHH,2244u{{dhh##%%

28
 
 
 	
r   c                     |dz
  }| j                   | j                  |j                         z  t        j                  d|j                         z        z  z
  S )NrO   )r   r   r>   r&   r?   r@   )r   rL   terms      r   icdfzLaplace.icdfc   sA    s{xx$**{{}4u{{2
?7SSSSr   c                 L    dt        j                  d| j                  z        z   S )Nr7   r   )r&   rJ   r   r   s    r   entropyzLaplace.entropyg   s    599Q^,,,r   r   )__name__
__module____qualname____doc__r   realpositivearg_constraintssupporthas_rsamplepropertyr   r   r   r   r!   r   floatr   boolr*   r/   r&   r'   r
   rG   rM   rQ   rU   rW   __classcell__)r,   s   @r   r   r      s#    *..9M9MNOGKf   f   %& % % % % % )-	C65=!C VU]#C  ~	C
 
C -7EJJL HE HV HU

T-r   )typingr   r   r&   r   torch.distributionsr    torch.distributions.distributionr   torch.distributions.utilsr   torch.typesr	   r
   __all__r    r   r   <module>rl      s1    "   + 9 3 & +Y-l Y-r   