o
    h                     @   sr   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 deZdS )
    )OptionalUnionN)Tensor)constraints)Distribution)broadcast_all)_Number_sizeLaplacec                	       s   e Zd ZdZejejdZejZdZ	e
defddZe
defddZe
defd	d
Ze
defddZ	d deeef deeef dee ddf fddZd  fdd	Ze fdedefddZdd Zdd Zdd Zdd Z  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                 C      | j S Nr   self r   a/home/www/facesmatcher.com/frenv_anti/lib/python3.10/site-packages/torch/distributions/laplace.pymean#      zLaplace.meanc                 C   r   r   r   r   r   r   r   mode'   r   zLaplace.modec                 C   s   d| j d S N   )r   powr   r   r   r   variance+   s   zLaplace.variancec                 C   s
   d| j  S )Ng;f?)r   r   r   r   r   stddev/   s   
zLaplace.stddevNr   r   validate_argsc                    sN   t ||\| _| _t|trt|trt }n| j }t j	||d d S )Nr   )
r   r   r   
isinstancer   torchSizesizesuper__init__)r   r   r   r   batch_shape	__class__r   r   r$   3   s
   

zLaplace.__init__c                    sR   |  t|}t|}| j||_| j||_tt|j|dd | j	|_	|S )NFr   )
Z_get_checked_instancer
   r    r!   r   expandr   r#   r$   _validate_args)r   r%   Z	_instancenewr&   r   r   r(   @   s   
zLaplace.expandsample_shapec                 C   s   |  |}t| jj}tj r8tj|| jj| jjdd d }| j| j	|
  t| j|jd   S | j||jd d}| j| j	|
  t|    S )N)dtypedevicer      )min)Z_extended_shaper    finfor   r,   Z_CZ_get_tracing_stateZrandr-   r   signlog1pabsclampZtinyr*   Zuniform_eps)r   r+   shaper0   ur   r   r   rsampleI   s   

 $zLaplace.rsamplec                 C   s8   | j r| | td| j  t|| j | j  S r   )r)   _validate_sampler    logr   r3   r   r   valuer   r   r   log_probW   s   
(zLaplace.log_probc                 C   sB   | j r| | dd|| j   t|| j   | j   S )N      ?)r)   r9   r   r1   r    expm1r3   r   r;   r   r   r   cdf\   s
   
zLaplace.cdfc                 C   s.   |d }| j | j|  td|    S )Nr>   )r   r   r1   r    r2   r3   )r   r<   termr   r   r   icdfc   s   &zLaplace.icdfc                 C   s   dt d| j  S )Nr.   r   )r    r:   r   r   r   r   r   entropyg   s   zLaplace.entropyr   )__name__
__module____qualname____doc__r   realZpositiveZarg_constraintsZsupportZhas_rsamplepropertyr   r   r   r   r   r   floatr   boolr$   r(   r    r!   r	   r8   r=   r@   rC   rD   __classcell__r   r   r&   r   r
      s:    

	)typingr   r   r    r   Ztorch.distributionsr   Z torch.distributions.distributionr   Ztorch.distributions.utilsr   Ztorch.typesr   r	   __all__r
   r   r   r   r   <module>   s   