
    /jc	                     x    d dl 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e	          ZdS )	    N)infTensor)constraints)Normal)TransformedDistribution)AbsTransform
HalfNormalc                       e Zd ZU dZdej        iZej        ZdZ	e
ed<   	 ddeez  dedz  ddf fdZd fd		Zedefd
            Zedefd            Zedefd            Zedefd            Zd Zd Zd Zd Z x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                     t          d|d          }t                                          |t                      |           d S )Nr   F)r   )r   super__init__r   )selfr   r   r   	__class__s       d/home/longshao/multi-rider-rag/.venv/lib/python3.11/site-packages/torch/distributions/half_normal.pyr   zHalfNormal.__init__(   sB    
 1e5999	LNN-PPPPP    c                     |                      t          |          }t                                          ||          S )N)	_instance)_get_checked_instancer	   r   expand)r   batch_shaper   newr   s       r   r   zHalfNormal.expand0   s2    ((Y??ww~~kS~999r   c                     | j         j        S N)r   r   r   s    r   r   zHalfNormal.scale4   s    ~##r   c                 T    | j         t          j        dt          j        z            z  S N   )r   mathsqrtpir   s    r   meanzHalfNormal.mean8   s    zDIa$'k2222r   c                 4    t          j        | j                  S r   )torch
zeros_liker   r   s    r   modezHalfNormal.mode<   s    
+++r   c                 \    | j                             d          ddt          j        z  z
  z  S Nr!      )r   powr"   r$   r   s    r   variancezHalfNormal.variance@   s%    z~~a  ADGO44r   c                     | j         r|                     |           | j                            |          t	          j        d          z   }t          j        |dk    |t                     }|S )Nr!   r   )	_validate_args_validate_sampler   log_probr"   logr'   wherer   )r   valuer2   s      r   r2   zHalfNormal.log_probD   sa     	)!!%(((>**511DHQKK?;uz8cT::r   c                 z    | j         r|                     |           d| j                            |          z  dz
  S r+   )r0   r1   r   cdf)r   r5   s     r   r7   zHalfNormal.cdfK   sA     	)!!%(((4>%%e,,,q00r   c                 B    | j                             |dz   dz            S )Nr,   r!   )r   icdf)r   probs     r   r9   zHalfNormal.icdfP   s     ~""D1H>222r   c                 ^    | j                                         t          j        d          z
  S r    )r   entropyr"   r3   r   s    r   r<   zHalfNormal.entropyS   s#    ~%%''$(1++55r   r   )__name__
__module____qualname____doc__r   positivearg_constraintsnonnegativesupporthas_rsampler   __annotations__r   floatboolr   r   propertyr   r%   r)   r.   r2   r7   r9   r<   __classcell__)r   s   @r   r	   r	      s         "  45O%GK
 &*Q Q~Q d{Q 
	Q Q Q Q Q Q: : : : : : $v $ $ $ X$ 3f 3 3 3 X3 ,f , , , X, 5& 5 5 5 X5  1 1 1
3 3 36 6 6 6 6 6 6r   )r"   r'   r   r   torch.distributionsr   torch.distributions.normalr   ,torch.distributions.transformed_distributionr   torch.distributions.transformsr   __all__r	    r   r   <module>rQ      s              + + + + + + - - - - - - P P P P P P 7 7 7 7 7 7 .E6 E6 E6 E6 E6( E6 E6 E6 E6 E6r   