o
    Zh                     @   sv   d dl Z d dl mZ d dlmZ d dlmZ d dlmZmZm	Z	m
Z
 d dlmZ d dlmZ dgZG d	d deZdS )
    N)Tensor)constraints)Distribution)broadcast_alllazy_propertylogits_to_probsprobs_to_logits) binary_cross_entropy_with_logits)_Number	Geometricc                       s   e Zd ZdZejejdZejZ	d fdd	Z
d fdd	Zedefd	d
ZedefddZedefddZedefddZedefddZe fddZdd Zdd Z  ZS )r   a  
    Creates a Geometric distribution parameterized by :attr:`probs`,
    where :attr:`probs` is the probability of success of Bernoulli trials.

    .. math::

        P(X=k) = (1-p)^{k} p, k = 0, 1, ...

    .. note::
        :func:`torch.distributions.geometric.Geometric` :math:`(k+1)`-th trial is the first success
        hence draws samples in :math:`\{0, 1, \ldots\}`, whereas
        :func:`torch.Tensor.geometric_` `k`-th trial is the first success hence draws samples in :math:`\{1, 2, \ldots\}`.

    Example::

        >>> # xdoctest: +IGNORE_WANT("non-deterministic")
        >>> m = Geometric(torch.tensor([0.3]))
        >>> m.sample()  # underlying Bernoulli has 30% chance 1; 70% chance 0
        tensor([ 2.])

    Args:
        probs (Number, Tensor): the probability of sampling `1`. Must be in range (0, 1]
        logits (Number, Tensor): the log-odds of sampling `1`.
    )probslogitsNc           	   	      s   |d u |d u krt d|d urt|\| _nt|\| _|d ur#|n|}t|tr/t }n| }t	 j
||d | jrk|d urm| j}|dk}| so|j|  }t dt|j dt|j dt|  d| d S d S d S )Nz;Either `probs` or `logits` must be specified, but not both.validate_argsr   zExpected parameter probs (z
 of shape z) of distribution z* to be positive but found invalid values:
)
ValueErrorr   r   r   
isinstancer
   torchSizesizesuper__init___validate_argsalldatatype__name__tupleshaperepr)	selfr   r   r   Zprobs_or_logitsbatch_shapevalueZvalidZinvalid_value	__class__ L/var/www/auris/lib/python3.10/site-packages/torch/distributions/geometric.pyr   0   s<   

zGeometric.__init__c                    sf   |  t|}t|}d| jv r| j||_d| jv r#| j||_tt|j	|dd | j
|_
|S )Nr   r   Fr   )Z_get_checked_instancer   r   r   __dict__r   expandr   r   r   r   )r   r    Z	_instancenewr"   r$   r%   r'   L   s   


zGeometric.expandreturnc                 C   s   d| j  d S Ng      ?r   r   r$   r$   r%   meanW      zGeometric.meanc                 C   s   t | jS N)r   Z
zeros_liker   r,   r$   r$   r%   mode[   s   zGeometric.modec                 C   s   d| j  d | j  S r*   r+   r,   r$   r$   r%   variance_   s   zGeometric.variancec                 C      t | jddS NT)Z	is_binary)r   r   r,   r$   r$   r%   r   c   r.   zGeometric.logitsc                 C   r2   r3   )r   r   r,   r$   r$   r%   r   g   r.   zGeometric.probsc                 C   s   |  |}t| jjj}t 6 tj r*tj	|| jj| jj
d}|j|d}n
| j||d}| | j    W  d    S 1 sJw   Y  d S )N)dtypedevice)min   )Z_extended_shaper   Zfinfor   r4   tinyZno_gradZ_CZ_get_tracing_stateZrandr5   clampr(   Zuniform_loglog1pfloor)r   Zsample_shaper   r8   ur$   r$   r%   samplek   s   


$zGeometric.samplec                 C   sZ   | j r| | t|| j\}}|jtjd}d||dk|dk@ < ||   | j  S )N)Zmemory_formatr   r7   )	r   Z_validate_sampler   r   cloner   Zcontiguous_formatr;   r:   )r   r!   r   r$   r$   r%   log_probw   s   
zGeometric.log_probc                 C   s   t | j| jdd| j S )Nnone)Z	reduction)r	   r   r   r,   r$   r$   r%   entropy   s   zGeometric.entropy)NNNr/   )r   
__module____qualname____doc__r   Zunit_intervalrealZarg_constraintsZnonnegative_integerZsupportr   r'   propertyr   r-   r0   r1   r   r   r   r   r   r>   r@   rB   __classcell__r$   r$   r"   r%   r      s&    )r   r   Ztorch.distributionsr   Z torch.distributions.distributionr   Ztorch.distributions.utilsr   r   r   r   Ztorch.nn.functionalr	   Ztorch.typesr
   __all__r   r$   r$   r$   r%   <module>   s   