§
    Ÿ²Åjñ  ã                   óX   — 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 )é    )Úconstraints)ÚNormal)ÚTransformedDistribution)ÚStickBreakingTransformÚLogisticNormalc                   óŒ   ‡ — e Zd ZdZej        ej        dœZej        Z	dZ
d	ˆ fd„	Zd	ˆ fd„	Zed„ ¦   «         Zed„ ¦   «         Zˆ xZS )
r   a9  
    Creates a logistic-normal distribution parameterized by :attr:`loc` and :attr:`scale`
    that define the base `Normal` distribution transformed with the
    `StickBreakingTransform` such that::

        X ~ LogisticNormal(loc, scale)
        Y = log(X / (1 - X.cumsum(-1)))[..., :-1] ~ Normal(loc, scale)

    Args:
        loc (float or Tensor): mean of the base distribution
        scale (float or Tensor): standard deviation of the base distribution

    Example::

        >>> # logistic-normal distributed with mean=(0, 0, 0) and stddev=(1, 1, 1)
        >>> # of the base Normal distribution
        >>> # xdoctest: +IGNORE_WANT("non-deterministic")
        >>> m = LogisticNormal(torch.tensor([0.0] * 3), torch.tensor([1.0] * 3))
        >>> m.sample()
        tensor([ 0.7653,  0.0341,  0.0579,  0.1427])

    )ÚlocÚscaleTNc                 óÆ   •— t          |||¬¦  «        }|j        s|                     dg¦  «        }t          ¦   «                              |t          ¦   «         |¬¦  «         d S )N)Úvalidate_argsé   )r   Úbatch_shapeÚexpandÚsuperÚ__init__r   )Úselfr	   r
   r   Ú	base_distÚ	__class__s        €úTC:\Projects\Historical\venv\Lib\site-packages\torch/distributions/logistic_normal.pyr   zLogisticNormal.__init__&   sp   ø€ Ý˜3 °]ÐCÑCÔCˆ	ØÔ$ð 	.Ø!×(Ò(¨!¨Ñ-Ô-ˆIÝ‰Œ×ÒØÕ-Ñ/Ô/¸}ð 	ñ 	
ô 	
ð 	
ð 	
ð 	
ó    c                 ó€   •— |                       t          |¦  «        }t          ¦   «                              ||¬¦  «        S )N)Ú	_instance)Ú_get_checked_instancer   r   r   )r   r   r   Únewr   s       €r   r   zLogisticNormal.expand.   s2   ø€ Ø×(Ò(­¸ÑCÔCˆÝ‰wŒw�~Š~˜k°Sˆ~Ñ9Ô9Ð9r   c                 ó$   — | j         j         j        S ©N)r   r	   ©r   s    r   r	   zLogisticNormal.loc2   s   € àŒ~Ô'Ô+Ð+r   c                 ó$   — | j         j         j        S r   )r   r
   r   s    r   r
   zLogisticNormal.scale6   s   € àŒ~Ô'Ô-Ð-r   r   )Ú__name__Ú
__module__Ú__qualname__Ú__doc__r   ÚrealÚpositiveÚarg_constraintsÚsimplexÚsupportÚhas_rsampler   r   Úpropertyr	   r
   Ú__classcell__)r   s   @r   r   r      s½   ø€ € € € € ðð ð, *Ô.¸Ô9MÐNÐN€OØÔ!€GØ€Kð
ð 
ð 
ð 
ð 
ð 
ð:ð :ð :ð :ð :ð :ð ð,ð ,ñ „Xð,ð ð.ð .ñ „Xð.ð .ð .ð .ð .r   N)
Útorch.distributionsr   Útorch.distributions.normalr   Ú,torch.distributions.transformed_distributionr   Útorch.distributions.transformsr   Ú__all__r   © r   r   ú<module>r1      sŒ   ðà +Ð +Ð +Ð +Ð +Ð +Ø -Ð -Ð -Ð -Ð -Ð -Ø PÐ PÐ PÐ PÐ PÐ PØ AÐ AÐ AÐ AÐ AÐ Að Ð
€ð-.ð -.ð -.ð -.ð -.Ð,ñ -.ô -.ð -.ð -.ð -.r   