o
    ,h                     @   s   d dl Z 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mZ d dlmZ d dlmZmZ d d	lmZ d
gZG dd
 d
e	ZdS )    N)OptionalUnion)Tensor)constraints)TransformedDistribution)AffineTransformExpTransform)Uniform)broadcast_alleuler_constant)_NumberGumbelc                	       s   e Zd ZdZejejdZej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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de
fddZdd Z  ZS )r   a  
    Samples from a Gumbel Distribution.

    Examples::

        >>> # xdoctest: +IGNORE_WANT("non-deterministic")
        >>> m = Gumbel(torch.tensor([1.0]), torch.tensor([2.0]))
        >>> m.sample()  # sample from Gumbel distribution with loc=1, scale=2
        tensor([ 1.0124])

    Args:
        loc (float or Tensor): Location parameter of the distribution
        scale (float or Tensor): Scale parameter of the distribution
    locscaleNr   r   validate_argsreturnc                    s   t ||\| _| _t| jj}t|tr&t|tr&t|j	d|j
 |d}ntt| j|j	t| jd|j
 |d}t jtdt| j dt jt|| j dg}t j|||d d S )N   )r   r   r   )r
   r   r   torchfinfodtype
isinstancer   r	   tinyeps	full_liker   invr   	ones_likesuper__init__)selfr   r   r   r   	base_dist
transforms	__class__ U/var/www/html/scripts/venv/lib/python3.10/site-packages/torch/distributions/gumbel.pyr   %   s   zGumbel.__init__c                    s8   |  t|}| j||_| j||_t j||dS )N)	_instance)_get_checked_instancer   r   expandr   r   )r   batch_shaper&   newr"   r$   r%   r(   =   s   zGumbel.expandc                 C   s6   | j r| | | j| | j }||  | j  S N)_validate_args_validate_sampler   r   explog)r   valueyr$   r$   r%   log_probD   s   
zGumbel.log_probc                 C   s   | j | jt  S r+   )r   r   r   r   r$   r$   r%   meanJ   s   zGumbel.meanc                 C   s   | j S r+   )r   r3   r$   r$   r%   modeN   s   zGumbel.modec                 C   s   t jt d | j S )N   )mathpisqrtr   r3   r$   r$   r%   stddevR   s   zGumbel.stddevc                 C   s   | j dS )N   )r:   powr3   r$   r$   r%   varianceV   s   zGumbel.variancec                 C   s   | j  dt  S )Nr   )r   r/   r   r3   r$   r$   r%   entropyZ   s   zGumbel.entropyr+   )__name__
__module____qualname____doc__r   realpositivearg_constraintssupportr   r   floatr   boolr   r(   r2   propertyr4   r5   r:   r=   r>   __classcell__r$   r$   r"   r%   r      s2    

)r7   typingr   r   r   r   torch.distributionsr   ,torch.distributions.transformed_distributionr   torch.distributions.transformsr   r   torch.distributions.uniformr	   torch.distributions.utilsr
   r   torch.typesr   __all__r   r$   r$   r$   r%   <module>   s   