o
    Zh                     @   sr   d dl Z d dlZd dlmZmZ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 )	    N)infnanTensor)constraints)Distribution)broadcast_all)_Number_sizeCauchyc                       s   e Zd ZdZejejdZejZdZ	d fdd	Z
d 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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
   aC  
    Samples from a Cauchy (Lorentz) distribution. The distribution of the ratio of
    independent normally distributed random variables with means `0` follows a
    Cauchy distribution.

    Example::

        >>> # xdoctest: +IGNORE_WANT("non-deterministic")
        >>> m = Cauchy(torch.tensor([0.0]), torch.tensor([1.0]))
        >>> m.sample()  # sample from a Cauchy distribution with loc=0 and scale=1
        tensor([ 2.3214])

    Args:
        loc (float or Tensor): mode or median of the distribution.
        scale (float or Tensor): half width at half maximum.
    )locscaleTNc                    sN   t ||\| _| _t|trt|trt }n| j }t j	||d d S )Nvalidate_args)
r   r   r   
isinstancer   torchSizesizesuper__init__)selfr   r   r   batch_shape	__class__ I/var/www/auris/lib/python3.10/site-packages/torch/distributions/cauchy.pyr   %   s
   

zCauchy.__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Cauchy.expandreturnc                 C      t j|  t| jj| jjdS N)dtypedevice)r   full_extended_shaper   r   r!   r"   r   r   r   r   mean6      zCauchy.meanc                 C   s   | j S N)r   r%   r   r   r   mode<   s   zCauchy.modec                 C   r   r    )r   r#   r$   r   r   r!   r"   r%   r   r   r   variance@   r'   zCauchy.variancesample_shapec                 C   s*   |  |}| j| }| j|| j  S r(   )r$   r   r   Zcauchy_r   )r   r+   shapeZepsr   r   r   rsampleF   s   
zCauchy.rsamplec                 C   s@   | j r| | ttj | j  || j | j d   S )N   )r   _validate_samplemathlogpir   r   log1pr   valuer   r   r   log_probK   s   
zCauchy.log_probc                 C   s0   | j r| | t|| j | j tj d S Ng      ?)r   r/   r   atanr   r   r0   r2   r4   r   r   r   cdfT   s   
 z
Cauchy.cdfc                 C   s    t tj|d  | j | j S r7   )r   tanr0   r2   r   r   r4   r   r   r   icdfY   s    zCauchy.icdfc                 C   s   t dt j | j  S )N   )r0   r1   r2   r   r%   r   r   r   entropy\   s   zCauchy.entropyr(   )__name__
__module____qualname____doc__r   realZpositiveZarg_constraintsZsupportZhas_rsampler   r   propertyr   r&   r)   r*   r   r   r	   r-   r6   r9   r;   r=   __classcell__r   r   r   r   r
      s$    		)r0   r   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   