o
    h                     @   s   d dl mZ d dlmZ d dlmZmZ d dlZd dlm	  m
Z d dlmZ dZg dZdd	 Zd
d Zdd Zd!ddZdd Zd!ddZG dd dZG dd deeZd"dejdedejfddZd"dejdedejfdd ZdS )#    )update_wrapper)Number)AnyDictNis_tensor_likegox?)broadcast_alllogits_to_probsclamp_probsprobs_to_logitslazy_propertytril_matrix_to_vecvec_to_tril_matrixc                     s   t dd | D stdt dd | D s@tt d | D ]}t|tjr1t|j|jd  nq fdd| D }tj	| S tj	|  S )	a  
    Given a list of values (possibly containing numbers), returns a list where each
    value is broadcasted based on the following rules:
      - `torch.*Tensor` instances are broadcasted as per :ref:`_broadcasting-semantics`.
      - numbers.Number instances (scalars) are upcast to tensors having
        the same size and type as the first tensor passed to `values`.  If all the
        values are scalars, then they are upcasted to scalar Tensors.

    Args:
        values (list of `numbers.Number`, `torch.*Tensor` or objects implementing __torch_function__)

    Raises:
        ValueError: if any of the values is not a `numbers.Number` instance,
            a `torch.*Tensor` instance, or an instance implementing __torch_function__
    c                 s   s"    | ]}t |pt|tV  qd S N)r   
isinstancer   .0v r   O/var/www/html/ai/venv/lib/python3.10/site-packages/torch/distributions/utils.py	<genexpr>&   s     z broadcast_all.<locals>.<genexpr>zqInput arguments must all be instances of numbers.Number, torch.Tensor or objects implementing __torch_function__.c                 s   s    | ]}t |V  qd S r   r   r   r   r   r   r   +   s    )dtyper   devicec                    s*   g | ]}t |r
|ntj|fi  qS r   )r   torchtensorr   optionsr   r   
<listcomp>1   s    z!broadcast_all.<locals>.<listcomp>)
all
ValueErrordictr   get_default_dtyper   Tensorr   r   broadcast_tensors)valuesvalue
new_valuesr   r   r   r      s    


r   c                 C   sB   t j rt t j| ||dt j| ||dS t j| ||d S )Nr   )r   _C_get_tracing_statenormalzerosonesemptynormal_)shaper   r   r   r   r   _standard_normal8   s   
r0   c                 C   s0   |dkr| S | j d|  d }| |dS )z
    Sum out ``dim`` many rightmost dimensions of a given tensor.

    Args:
        value (Tensor): A tensor of ``.dim()`` at least ``dim``.
        dim (int): The number of rightmost dims to sum out.
    r   N)r1   )r/   reshapesum)r&   dimrequired_shaper   r   r   _sum_rightmostB   s   r6   Fc                 C   s   |rt | S tj| ddS )a  
    Converts a tensor of logits into probabilities. Note that for the
    binary case, each value denotes log odds, whereas for the
    multi-dimensional case, the values along the last dimension denote
    the log probabilities (possibly unnormalized) of the events.
    r1   )r4   )r   sigmoidFsoftmax)logits	is_binaryr   r   r   r	   P   s   
r	   c                 C   s    t | jj}| j|d| dS )N   )minmax)r   finfor   epsclamp)probsr@   r   r   r   r
   \   s   r
   c                 C   s,   t | }|rt|t|  S t|S )a$  
    Converts a tensor of probabilities into logits. For the binary case,
    this denotes the probability of occurrence of the event indexed by `1`.
    For the multi-dimensional case, the values along the last dimension
    denote the probabilities of occurrence of each of the events.
    )r
   r   loglog1p)rB   r;   
ps_clampedr   r   r   r   a   s   
r   c                   @   s"   e Zd ZdZdd ZdddZdS )r   z
    Used as a decorator for lazy loading of class attributes. This uses a
    non-data descriptor that calls the wrapped method to compute the property on
    first call; thereafter replacing the wrapped method into an instance
    attribute.
    c                 C   s   || _ t| | d S r   )wrappedr   selfrF   r   r   r   __init__v   s   zlazy_property.__init__Nc                 C   sX   |d u r	t | jS t  | |}W d    n1 sw   Y  t|| jj| |S r   )_lazy_property_and_propertyrF   r   enable_gradsetattr__name__)rH   instanceobj_typer&   r   r   r   __get__z   s   

zlazy_property.__get__r   )rM   
__module____qualname____doc__rI   rP   r   r   r   r   r   n   s    r   c                   @   s   e Zd ZdZdd ZdS )rJ   zWe want lazy properties to look like multiple things.

    * property when Sphinx autodoc looks
    * lazy_property when Distribution validate_args looks
    c                 C   s   t | | d S r   )propertyrI   rG   r   r   r   rI      s   z$_lazy_property_and_property.__init__N)rM   rQ   rR   rS   rI   r   r   r   r   rJ      s    rJ   matdiagreturnc                 C   s   | j d }tj s$|| k s||kr$td| d|  d|d  dtj|| jd}||dd|d  k }| d|f }|S )	z
    Convert a `D x D` matrix or a batch of matrices into a (batched) vector
    which comprises of lower triangular elements from the matrix in row order.
    r1   zdiag (z) provided is outside [z, r<   z].r   .)r/   r   r(   r)   r    aranger   view)rU   rV   nrY   	tril_maskvecr   r   r   r      s   
"r   r]   c                 C   s  dd|   dd|  d d| j d   dt| |d   d  d }t| jj}tj sEt|| |krEt	d| j d  dd	 t
|tjrQt| nt|}| | j d
d t||f }tj|| jd}||dd|d  k }| |d|f< |S )z
    Convert a vector or a batch of vectors into a batched `D x D`
    lower triangular matrix containing elements from the vector in row order.
    r<         r1      g      ?zThe size of last dimension is z which cannot be expressed as z3the lower triangular part of a square D x D matrix.NrX   .)r/   absr   r?   r   r@   r(   r)   roundr    r   r#   item	new_zerosSizerY   r   rZ   )r]   rV   r[   r@   rU   rY   r\   r   r   r   r      s$   4 "r   )F)r   )	functoolsr   numbersr   typingr   r   r   torch.nn.functionalnn
functionalr8   torch.overridesr   euler_constant__all__r   r0   r6   r	   r
   r   r   rT   rJ   r#   intr   r   r   r   r   r   <module>   s$    "


 