
    9iE	                         S SK r S SKJrJr  S SKrS SKJrJr  S SKJr  S SK	J
r
  S SKJr  S SKJr  S/r " S	 S\5      rg)
    N)OptionalUnion)infTensor)constraints)Normal)TransformedDistribution)AbsTransform
HalfNormalc                     ^  \ rS rSr% SrS\R                  0r\R                  r	Sr
\\S'    SS\\\4   S\\   SS4U 4S	 jjjrSU 4S
 jjr\S\4S j5       r\S\4S j5       r\S\4S j5       r\S\4S j5       rS rS rS rS rSrU =r$ )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                 J   > [        SUSS9n[        TU ]	  U[        5       US9  g )Nr   F)r   )r   super__init__r
   )selfr   r   r   	__class__s       _/var/www/html/land-doc-ocr/venv/lib/python3.13/site-packages/torch/distributions/half_normal.pyr   HalfNormal.__init__'   s)    
 1e59	LN-P    c                 J   > U R                  [        U5      n[        TU ]  XS9$ )N)	_instance)_get_checked_instancer   r   expand)r   batch_shaper   newr   s       r   r   HalfNormal.expand/   s&    ((Y?w~k~99r   c                 .    U R                   R                  $ N)r   r   r   s    r   r   HalfNormal.scale3   s    ~~###r   c                 j    U R                   [        R                  " S[        R                  -  5      -  $ N   )r   mathsqrtpir#   s    r   meanHalfNormal.mean7   s"    zzDIIa$''k222r   c                 B    [         R                  " U R                  5      $ r"   )torch
zeros_liker   r#   s    r   modeHalfNormal.mode;   s    

++r   c                 f    U R                   R                  S5      SS[        R                  -  -
  -  $ Nr'      )r   powr(   r*   r#   s    r   varianceHalfNormal.variance?   s&    zz~~a ADGGO44r   c                     U R                   (       a  U R                  U5        U R                  R                  U5      [        R
                  " S5      -   n[        R                  " US:  U[        * 5      nU$ )Nr'   r   )	_validate_args_validate_sampler   log_probr(   logr.   wherer   )r   valuer;   s      r   r;   HalfNormal.log_probC   sW    !!%(>>**51DHHQK?;;uz8cT:r   c                     U R                   (       a  U R                  U5        SU R                  R                  U5      -  S-
  $ r3   )r9   r:   r   cdf)r   r>   s     r   rA   HalfNormal.cdfJ   s8    !!%(4>>%%e,,q00r   c                 D    U R                   R                  US-   S-  5      $ )Nr4   r'   )r   icdf)r   probs     r   rD   HalfNormal.icdfO   s    ~~""D1H>22r   c                 d    U R                   R                  5       [        R                  " S5      -
  $ r&   )r   entropyr(   r<   r#   s    r   rH   HalfNormal.entropyR   s"    ~~%%'$((1+55r    r"   )__name__
__module____qualname____firstlineno____doc__r   positivearg_constraintsnonnegativesupporthas_rsampler   __annotations__r   r   floatr   boolr   r   propertyr   r+   r0   r6   r;   rA   rD   rH   __static_attributes____classcell__)r   s   @r   r   r      s    "  4 45O%%GK
 )-QVU]#Q  ~Q 
	Q Q: $v $ $ 3f 3 3 ,f , , 5& 5 51
36 6r   )r(   typingr   r   r.   r   r   torch.distributionsr   torch.distributions.normalr   ,torch.distributions.transformed_distributionr	   torch.distributions.transformsr
   __all__r   rJ   r   r   <module>ra      s5     "   + - P 7 .C6( C6r   