a
    hE	                     @   sz   d dl Z d dlmZmZ d dlZ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gZG d	d deZdS )
    N)OptionalUnion)infTensor)constraints)Normal)TransformedDistribution)AbsTransform
HalfNormalc                       s   e Zd ZU dZdejiZejZdZ	e
ed< deeef ee dd fddZd fd	d
	ZeedddZeedddZeedddZeedddZdd Zdd Zdd Zdd Z  ZS )r
   a  
    Creates a half-normal distribution parameterized by `scale` where::

        X ~ Normal(0, scale)
        Y = |X| ~ HalfNormal(scale)

    Example::

        >>> # xdoctest: +IGNORE_WANT("non-deterministic")
        >>> m = HalfNormal(torch.tensor([1.0]))
        >>> m.sample()  # half-normal distributed with scale=1
        tensor([ 0.1046])

    Args:
        scale (float or Tensor): scale of the full Normal distribution
    scaleT	base_distN)r   validate_argsreturnc                    s&   t d|dd}t j|t |d d S )Nr   F)r   )r   super__init__r	   )selfr   r   r   	__class__ M/var/www/auris/lib/python3.9/site-packages/torch/distributions/half_normal.pyr   '   s    zHalfNormal.__init__c                    s   |  t|}t j||dS )N)	_instance)Z_get_checked_instancer
   r   expand)r   Zbatch_shaper   newr   r   r   r   /   s    zHalfNormal.expand)r   c                 C   s   | j jS N)r   r   r   r   r   r   r   3   s    zHalfNormal.scalec                 C   s   | j tdtj  S N   )r   mathsqrtpir   r   r   r   mean7   s    zHalfNormal.meanc                 C   s   t | jS r   )torchZ
zeros_liker   r   r   r   r   mode;   s    zHalfNormal.modec                 C   s   | j dddtj   S Nr      )r   powr   r   r   r   r   r   variance?   s    zHalfNormal.variancec                 C   s>   | j r| | | j|td }t|dk|t }|S )Nr   r   )	_validate_args_validate_sampler   log_probr   logr!   wherer   )r   valuer)   r   r   r   r)   C   s
    
zHalfNormal.log_probc                 C   s$   | j r| | d| j| d S r#   )r'   r(   r   cdf)r   r,   r   r   r   r-   J   s    
zHalfNormal.cdfc                 C   s   | j |d d S )Nr$   r   )r   icdf)r   Zprobr   r   r   r.   O   s    zHalfNormal.icdfc                 C   s   | j  td S r   )r   entropyr   r*   r   r   r   r   r/   R   s    zHalfNormal.entropy)N)N)__name__
__module____qualname____doc__r   ZpositiveZarg_constraintsZnonnegativeZsupportZhas_rsampler   __annotations__r   r   floatr   boolr   r   propertyr   r    r"   r&   r)   r-   r.   r/   __classcell__r   r   r   r   r
      s0   

 
)r   typingr   r   r!   r   r   Ztorch.distributionsr   Ztorch.distributions.normalr   Z,torch.distributions.transformed_distributionr   Ztorch.distributions.transformsr	   __all__r
   r   r   r   r   <module>   s   