
    }Yhv                         d dl mZmZm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 ed	e

          Z G d de
ee                   ZdS )    )GenericOptionalTypeVarN)SizeTensor)constraints)Distribution)_sum_rightmost)_sizeIndependentD)boundc            	           e Zd ZU dZi Zeeej        f         e	d<   e
e	d<   	 dde
dedee         ddf fd	Zd fd
	Zedefd            Zedefd            Zej        d             Zedefd            Zedefd            Zedefd            Z ej                    fdefdZ ej                    fdedefdZd Zd ZddZ d Z! xZ"S )r   a  
    Reinterprets some of the batch dims of a distribution as event dims.

    This is mainly useful for changing the shape of the result of
    :meth:`log_prob`. For example to create a diagonal Normal distribution with
    the same shape as a Multivariate Normal distribution (so they are
    interchangeable), you can::

        >>> from torch.distributions.multivariate_normal import MultivariateNormal
        >>> from torch.distributions.normal import Normal
        >>> loc = torch.zeros(3)
        >>> scale = torch.ones(3)
        >>> mvn = MultivariateNormal(loc, scale_tril=torch.diag(scale))
        >>> [mvn.batch_shape, mvn.event_shape]
        [torch.Size([]), torch.Size([3])]
        >>> normal = Normal(loc, scale)
        >>> [normal.batch_shape, normal.event_shape]
        [torch.Size([3]), torch.Size([])]
        >>> diagn = Independent(normal, 1)
        >>> [diagn.batch_shape, diagn.event_shape]
        [torch.Size([]), torch.Size([3])]

    Args:
        base_distribution (torch.distributions.distribution.Distribution): a
            base distribution
        reinterpreted_batch_ndims (int): the number of batch dims to
            reinterpret as event dims
    arg_constraints	base_distNbase_distributionreinterpreted_batch_ndimsvalidate_argsreturnc                    |t          |j                  k    r't          d| dt          |j                             |j        |j        z   }|t          |j                  z   }|d t          |          |z
           }|t          |          |z
  d          }|| _        || _        t                                          |||           d S )NzQExpected reinterpreted_batch_ndims <= len(base_distribution.batch_shape), actual z vs r   )lenbatch_shape
ValueErrorevent_shaper   r   super__init__)	selfr   r   r   shape	event_dimr   r   	__class__s	           q/var/www/tools.fuzzalab.pt/emblema-extractor/venv/lib/python3.11/site-packages/torch/distributions/independent.pyr   zIndependent.__init__3   s     %s+<+H'I'III^3^ ^9<=N=Z9[9[^ ^   (36G6SS2S9J9V5W5WW	4c%jj9445CJJ2445*)B&kOOOOO    c                 ^   |                      t          |          }t          j        |          }| j                            || j        d | j                 z             |_        | j        |_        t          t          |          	                    || j        d           | j
        |_
        |S )NFr   )_get_checked_instancer   torchr   r   expandr   r   r   r   _validate_args)r   r   	_instancenewr!   s       r"   r'   zIndependent.expandF   s    ((i@@j----$*+KT-K+KLL
 
 )-(F%k3(() 	) 	
 	
 	
 "0
r#   c                     | j         j        S N)r   has_rsampler   s    r"   r-   zIndependent.has_rsampleS   s    ~))r#   c                 4    | j         dk    rdS | j        j        S )Nr   F)r   r   has_enumerate_supportr.   s    r"   r0   z!Independent.has_enumerate_supportW   s     )A--5~33r#   c                 `    | j         j        }| j        rt          j        || j                  }|S r,   )r   supportr   r   independent)r   results     r"   r2   zIndependent.support]   s2    ') 	U ,VT5STTFr#   c                     | j         j        S r,   )r   meanr.   s    r"   r6   zIndependent.meand       ~""r#   c                     | j         j        S r,   )r   moder.   s    r"   r9   zIndependent.modeh   r7   r#   c                     | j         j        S r,   )r   variancer.   s    r"   r;   zIndependent.variancel   s    ~&&r#   c                 6    | j                             |          S r,   )r   sampler   sample_shapes     r"   r=   zIndependent.samplep   s    ~$$\222r#   r?   c                 6    | j                             |          S r,   )r   rsampler>   s     r"   rA   zIndependent.rsamples   s    ~%%l333r#   c                 `    | j                             |          }t          || j                  S r,   )r   log_probr
   r   )r   valuerC   s      r"   rC   zIndependent.log_probv   s*    >**511h(FGGGr#   c                 ^    | j                                         }t          || j                  S r,   )r   entropyr
   r   )r   rF   s     r"   rF   zIndependent.entropyz   s(    .((**gt'EFFFr#   Tc                 l    | j         dk    rt          d          | j                            |          S )Nr   z5Enumeration over cartesian product is not implemented)r'   )r   NotImplementedErrorr   enumerate_support)r   r'   s     r"   rI   zIndependent.enumerate_support~   s@    )A--%G   ~//v/>>>r#   c                 B    | j         j        d| j         d| j         dz   S )N(z, ))r!   __name__r   r   r.   s    r"   __repr__zIndependent.__repr__   s0    N#E$.EED$BEEEF	
r#   r,   )T)#rM   
__module____qualname____doc__r   dictstrr   
Constraint__annotations__r   intr   boolr   r'   propertyr-   r0   dependent_propertyr2   r   r6   r9   r;   r&   r   r=   r   rA   rC   rF   rI   rN   __classcell__)r!   s   @r"   r   r      sX         : :<OT#{556;;;LLL )-	P PP $'P  ~	P
 
P P P P P P&      *T * * * X* 4t 4 4 4 X4
 #  $# #f # # # X# #f # # # X# '& ' ' ' X' #-%*,, 3 36 3 3 3 3 -7EJLL 4 4E 4V 4 4 4 4H H HG G G? ? ? ?
 
 
 
 
 
 
r#   )typingr   r   r   r&   r   r   torch.distributionsr    torch.distributions.distributionr	   torch.distributions.utilsr
   torch.typesr   __all__r   r    r#   r"   <module>rb      s    - - - - - - - - - -          + + + + + + 9 9 9 9 9 9 4 4 4 4 4 4       / GC|$$$w
 w
 w
 w
 w
,
 w
 w
 w
 w
 w
r#   