a
    h	                     @   s   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 dlmZmZ d dlmZ d dlmZ d	gZG d
d	 d	e
ZdS )    )OptionalUnion)Tensor)constraints)Exponential)TransformedDistribution)AffineTransformExpTransform)broadcast_all)_sizeParetoc                       s   e Zd ZdZejejdZdeee	f eee	f e
e dd fddZdee
d  d d fdd	Zeed
ddZeed
ddZeed
ddZejdddejd
ddZed
ddZ  ZS )r   a  
    Samples from a Pareto Type 1 distribution.

    Example::

        >>> # xdoctest: +IGNORE_WANT("non-deterministic")
        >>> m = Pareto(torch.tensor([1.0]), torch.tensor([1.0]))
        >>> m.sample()  # sample from a Pareto distribution with scale=1 and alpha=1
        tensor([ 1.5623])

    Args:
        scale (float or Tensor): Scale parameter of the distribution
        alpha (float or Tensor): Shape parameter of the distribution
    )alphascaleN)r   r   validate_argsreturnc                    sJ   t ||\| _| _t| j|d}t td| jdg}t j|||d d S )N)r   r   )locr   )r
   r   r   r   r	   r   super__init__)selfr   r   r   Z	base_distZ
transforms	__class__ H/var/www/auris/lib/python3.9/site-packages/torch/distributions/pareto.pyr   !   s    zPareto.__init__)batch_shape	_instancer   c                    s8   |  t|}| j||_| j||_t j||dS )N)r   )Z_get_checked_instancer   r   expandr   r   )r   r   r   newr   r   r   r   ,   s    zPareto.expand)r   c                 C   s    | j jdd}|| j |d  S )N   min)r   clampr   r   ar   r   r   mean4   s    zPareto.meanc                 C   s   | j S N)r   r   r   r   r   mode:   s    zPareto.modec                 C   s4   | j jdd}| jd| |d d|d   S )N   r   r   )r   r    r   powr!   r   r   r   variance>   s    zPareto.varianceFr   )Zis_discreteZ	event_dimc                 C   s   t | jS r$   )r   Zgreater_than_eqr   r%   r   r   r   supportD   s    zPareto.supportc                 C   s   | j | j  d| j   S )Nr   )r   r   logZ
reciprocalr%   r   r   r   entropyH   s    zPareto.entropy)N)N)__name__
__module____qualname____doc__r   ZpositiveZarg_constraintsr   r   floatr   boolr   r   r   propertyr#   r&   r)   Zdependent_property
Constraintr*   r,   __classcell__r   r   r   r   r      s.    

 N)typingr   r   Ztorchr   Ztorch.distributionsr   Ztorch.distributions.exponentialr   Z,torch.distributions.transformed_distributionr   Ztorch.distributions.transformsr   r	   Ztorch.distributions.utilsr
   Ztorch.typesr   __all__r   r   r   r   r   <module>   s   