
    קg	                     `    d dl 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)constraints)Gamma)TransformedDistribution)PowerTransformInverseGammac                        e Zd ZdZej        ej        dZej        ZdZd fd	Z	d fd	Z
ed             Zed             Zed	             Zed
             Zed             Zd Z xZS )r   a  
    Creates an inverse gamma distribution parameterized by :attr:`concentration` and :attr:`rate`
    where::

        X ~ Gamma(concentration, rate)
        Y = 1 / X ~ InverseGamma(concentration, rate)

    Example::

        >>> # xdoctest: +IGNORE_WANT("non-deterinistic")
        >>> m = InverseGamma(torch.tensor([2.0]), torch.tensor([3.0]))
        >>> m.sample()
        tensor([ 1.2953])

    Args:
        concentration (float or Tensor): shape parameter of the distribution
            (often referred to as alpha)
        rate (float or Tensor): rate = 1 / scale of the distribution
            (often referred to as beta)
    )concentrationrateTNc                     t          |||          }|j                            d           }t                                          |t          |          |           d S )N)validate_args )r   r
   new_onessuper__init__r   )selfr	   r
   r   	base_distneg_one	__class__s         ]/var/www/html/ai-engine/env/lib/python3.11/site-packages/torch/distributions/inverse_gamma.pyr   zInverseGamma.__init__(   si    -]KKK	>**2...~g..m 	 	
 	
 	
 	
 	
    c                     |                      t          |          }t                                          ||          S )N)	_instance)_get_checked_instancer   r   expand)r   batch_shaper   newr   s       r   r   zInverseGamma.expand/   s2    ((yAAww~~kS~999r   c                     | j         j        S N)r   r	   r   s    r   r	   zInverseGamma.concentration3   s    ~++r   c                     | j         j        S r   )r   r
   r   s    r   r
   zInverseGamma.rate7   s    ~""r   c                 x    | j         | j        dz
  z  }t          j        | j        dk    |t          j                  S N   )r
   r	   torchwhereinfr   results     r   meanzInverseGamma.mean;   s4    d0145{4-1659EEEr   c                 &    | j         | j        dz   z  S r"   )r
   r	   r   s    r   modezInverseGamma.mode@   s    yD.233r   c                     | j                                         | j        dz
                                  | j        dz
  z  z  }t          j        | j        dk    |t          j                  S )Nr#      )r
   squarer	   r$   r%   r&   r'   s     r   variancezInverseGamma.varianceD   s^    !!##!#++--1Ca1GH
 {4-1659EEEr   c                     | j         | j                                        z   | j                                         z   d| j         z   | j                                         z  z
  S r"   )r	   r
   loglgammadigammar   s    r   entropyzInverseGamma.entropyK   s]    immoo ''))* 4%%);)C)C)E)EEF	
r   r   )__name__
__module____qualname____doc__r   positivearg_constraintssupporthas_rsampler   r   propertyr	   r
   r)   r+   r/   r4   __classcell__)r   s   @r   r   r      s*        * %-$ O "GK
 
 
 
 
 
: : : : : : , , X, # # X# F F XF 4 4 X4 F F XF
 
 
 
 
 
 
r   )r$   torch.distributionsr   torch.distributions.gammar   ,torch.distributions.transformed_distributionr   torch.distributions.transformsr   __all__r   r   r   r   <module>rD      s     + + + + + + + + + + + + P P P P P P 9 9 9 9 9 9 
E
 E
 E
 E
 E
* E
 E
 E
 E
 E
r   