o
    ,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deeef dee ddf 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def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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__ Z/var/www/html/scripts/venv/lib/python3.10/site-packages/torch/distributions/half_normal.pyr   '   s   zHalfNormal.__init__c                    s   |  t|}t j||dS )N)	_instance)_get_checked_instancer
   r   expand)r   batch_shaper   newr   r   r   r   /   s   zHalfNormal.expandc                 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   )torch
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   r0   J   s   
zHalfNormal.cdfc                 C   s   | j |d d S )Nr'   r   )r   icdf)r   probr   r   r   r1   O      zHalfNormal.icdfc                 C   s   | j  td S r   )r   entropyr   r-   r   r   r   r   r4   R   r3   zHalfNormal.entropyr   )__name__
__module____qualname____doc__r   positivearg_constraintsnonnegativesupporthas_rsampler   __annotations__r   r   floatr   boolr   r   propertyr   r"   r%   r)   r,   r0   r1   r4   __classcell__r   r   r   r   r
      s6   
 

)r   typingr   r   r#   r   r   torch.distributionsr   torch.distributions.normalr   ,torch.distributions.transformed_distributionr   torch.distributions.transformsr	   __all__r
   r   r   r   r   <module>   s   