U
    9%e!                     @   sJ   d dl mZ d dlZd dlmZmZ d dlmZ dgZG dd deZ	dS )    )DictN)Categoricalconstraints)DistributionMixtureSameFamilyc                       s   e Zd ZU dZi Zeeejf e	d< dZ
d fdd	Zd  fdd	Zejd	d
 Zedd Zedd Zedd Zedd Zdd Zdd Ze fddZdd Zdd Zdd Z  ZS )!r   a  
    The `MixtureSameFamily` distribution implements a (batch of) mixture
    distribution where all component are from different parameterizations of
    the same distribution type. It is parameterized by a `Categorical`
    "selecting distribution" (over `k` component) and a component
    distribution, i.e., a `Distribution` with a rightmost batch shape
    (equal to `[k]`) which indexes each (batch of) component.

    Examples::

        >>> # xdoctest: +SKIP("undefined vars")
        >>> # Construct Gaussian Mixture Model in 1D consisting of 5 equally
        >>> # weighted normal distributions
        >>> mix = D.Categorical(torch.ones(5,))
        >>> comp = D.Normal(torch.randn(5,), torch.rand(5,))
        >>> gmm = MixtureSameFamily(mix, comp)

        >>> # Construct Gaussian Mixture Model in 2D consisting of 5 equally
        >>> # weighted bivariate normal distributions
        >>> mix = D.Categorical(torch.ones(5,))
        >>> comp = D.Independent(D.Normal(
        ...          torch.randn(5,2), torch.rand(5,2)), 1)
        >>> gmm = MixtureSameFamily(mix, comp)

        >>> # Construct a batch of 3 Gaussian Mixture Models in 2D each
        >>> # consisting of 5 random weighted bivariate normal distributions
        >>> mix = D.Categorical(torch.rand(3,5))
        >>> comp = D.Independent(D.Normal(
        ...         torch.randn(3,5,2), torch.rand(3,5,2)), 1)
        >>> gmm = MixtureSameFamily(mix, comp)

    Args:
        mixture_distribution: `torch.distributions.Categorical`-like
            instance. Manages the probability of selecting component.
            The number of categories must match the rightmost batch
            dimension of the `component_distribution`. Must have either
            scalar `batch_shape` or `batch_shape` matching
            `component_distribution.batch_shape[:-1]`
        component_distribution: `torch.distributions.Distribution`-like
            instance. Right-most batch dimension indexes component.
    arg_constraintsFNc                    s  || _ || _t| j ts tdt| jts4td| j j}| jjd d }tt|t|D ]6\}}|dkr^|dkr^||kr^td| d| dq^| j j	j
d }| jjd }	|d k	r|	d k	r||	krtd| d	|	 d|| _| jj}
t|
| _t j||
|d
 d S )NzU The Mixture distribution needs to be an  instance of torch.distributions.CategoricalzUThe Component distribution need to be an instance of torch.distributions.Distribution   z$`mixture_distribution.batch_shape` (z>) is not compatible with `component_distribution.batch_shape`()z"`mixture_distribution component` (z;) does not equal `component_distribution.batch_shape[-1]` (batch_shapeevent_shapevalidate_args)_mixture_distribution_component_distribution
isinstancer   
ValueErrorr   r   zipreversedlogitsshape_num_componentr   len_event_ndimssuper__init__)selfmixture_distributioncomponent_distributionr   ZmdbsZcdbsZsize1Zsize2kmkcr   	__class__ f/var/www/html/Darija-Ai-API/env/lib/python3.8/site-packages/torch/distributions/mixture_same_family.pyr   7   s>    
  zMixtureSameFamily.__init__c                    sx   t |}|| jf }| t|}| j||_| j||_| j|_| j|_|jj	}t
t|j||dd | j|_|S )NFr   )torchSizer   Z_get_checked_instancer   r   expandr   r   r   r   r   _validate_args)r   r   Z	_instanceZbatch_shape_compnewr   r!   r#   r$   r'   e   s"    

  zMixtureSameFamily.expandc                 C   s   | j jS N)r   supportr   r#   r#   r$   r+   v   s    zMixtureSameFamily.supportc                 C   s   | j S r*   )r   r,   r#   r#   r$   r   |   s    z&MixtureSameFamily.mixture_distributionc                 C   s   | j S r*   )r   r,   r#   r#   r$   r      s    z(MixtureSameFamily.component_distributionc                 C   s*   |  | jj}tj|| jj d| j dS Nr   dim)_pad_mixture_dimensionsr   probsr%   sumr   meanr   )r   r1   r#   r#   r$   r3      s
    
 zMixtureSameFamily.meanc                 C   s`   |  | jj}tj|| jj d| j d}tj|| jj| 	| j 
d d| j d}|| S )Nr   r.   g       @)r0   r   r1   r%   r2   r   variancer   r3   _padpow)r   r1   Zmean_cond_varZvar_cond_meanr#   r#   r$   r4      s    
 zMixtureSameFamily.variancec                 C   s0   |  |}| j|}| jj}tj|| ddS r-   )r5   r   cdfr   r1   r%   r2   )r   xZcdf_xZmix_probr#   r#   r$   r7      s    
zMixtureSameFamily.cdfc                 C   sJ   | j r| | | |}| j|}tj| jjdd}tj	|| ddS r-   )
r(   Z_validate_sampler5   r   log_probr%   Zlog_softmaxr   r   Z	logsumexp)r   r8   Z
log_prob_xZlog_mix_probr#   r#   r$   r9      s    

 zMixtureSameFamily.log_probc              
   C   s   t   t|}t| j}|| }| j}| j|}|j}| j|}|	|t 
dgt|d   }	|	t 
dgt| t 
dg | }	t |||	}
|
|W  5 Q R  S Q R X d S )Nr	   )r%   Zno_gradr   r   r   r   sampler   r   reshaper&   repeatgatherZsqueeze)r   Zsample_shapeZ
sample_lenZ	batch_lenZ
gather_dimesZ
mix_sampleZ	mix_shapeZcomp_samplesZmix_sample_rZsamplesr#   r#   r$   r:      s     

"zMixtureSameFamily.samplec                 C   s   | d| j S )Nr   )Z	unsqueezer   )r   r8   r#   r#   r$   r5      s    zMixtureSameFamily._padc                 C   st   | j  }| jj  }|dkr"dn|| }|j}||d d t|dg  |dd   t| jdg  }|S )Nr	   r   r   )r   Znumelr   r   r;   r%   r&   r   )r   r8   Zdist_batch_ndimsZcat_batch_ndimsZ	pad_ndimsZxsr#   r#   r$   r0      s    


z)MixtureSameFamily._pad_mixture_dimensionsc                 C   s    d| j  d| j }d| d S )Nz
  z,
  zMixtureSameFamily(r
   )r   r   )r   args_stringr#   r#   r$   __repr__   s    zMixtureSameFamily.__repr__)N)N)__name__
__module____qualname____doc__r   r   strr   
Constraint__annotations__Zhas_rsampler   r'   Zdependent_propertyr+   propertyr   r   r3   r4   r7   r9   r%   r&   r:   r5   r0   r@   __classcell__r#   r#   r!   r$   r   
   s,   
) .





)
typingr   r%   Ztorch.distributionsr   r   Z torch.distributions.distributionr   __all__r   r#   r#   r#   r$   <module>   s
   