a
    h                     @   sj   d dl mZmZ d dlmZ d dlmZ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 )
    )OptionalUnion)Tensor)constraintsIndependent)Normal)TransformedDistribution)StickBreakingTransformLogisticNormalc                       s   e Zd ZU dZejejdZejZ	dZ
ee ed< deeef 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  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])

    )locscaleT	base_distN)r   r   validate_argsreturnc                    s8   t |||d}|js |dg}t j|t |d d S )N)r      )r   batch_shapeexpandsuper__init__r	   )selfr   r   r   r   	__class__ Q/var/www/auris/lib/python3.9/site-packages/torch/distributions/logistic_normal.pyr   +   s    zLogisticNormal.__init__c                    s   |  t|}t j||dS )N)	_instance)Z_get_checked_instancer
   r   r   )r   r   r   newr   r   r   r   8   s    zLogisticNormal.expand)r   c                 C   s
   | j j jS N)r   r   r   r   r   r   r   <   s    zLogisticNormal.locc                 C   s
   | j j jS r   )r   r   r   r   r   r   r   @   s    zLogisticNormal.scale)N)N)__name__
__module____qualname____doc__r   realZpositiveZarg_constraintsZsimplexZsupportZhas_rsampler   r   __annotations__r   r   floatr   boolr   r   propertyr   r   __classcell__r   r   r   r   r
      s"   
 

N)typingr   r   Ztorchr   Ztorch.distributionsr   r   Ztorch.distributions.normalr   Z,torch.distributions.transformed_distributionr   Ztorch.distributions.transformsr	   __all__r
   r   r   r   r   <module>   s   