o
    hf                     @   sf   U d dl mZmZmZ d dlZd dlm  mZ d dlm	Z	 g Z
ee ed< ejjG dd dZdS )    )DictListOptionalN)Tensor__all__c                   @   s|   e Zd Z								ddee dedededed	ed
ededefddZdedee fddZ	deee  fddZ
dS )_FunctionalSGD{Gz?        Fparamslrmomentum	dampeningweight_decaynesterovmaximizeforeach_allow_empty_param_listc
           
      C   sl   ||||d| _ || _|| _|| _tjttjtt	tjf f i | _
t|dkr/|	s/tdd|i| _d S )N)r   r   r   r   r   z%optimizer got an empty parameter listr
   )defaultsr   r   r   torchjitannotater   r   strstatelen
ValueErrorparam_group)
selfr
   r   r   r   r   r   r   r   r    r   \/var/www/html/ai/venv/lib/python3.10/site-packages/torch/distributed/optim/functional_sgd.py__init__   s   $z_FunctionalSGD.__init__paramgradc                 C   s  | j d }| j d }| j d }| j d }|g}g }g }	d}
|durK|	| |jr+d}
|| jvr5i | j|< | j| }d|vrD|d n||d  t  tj||	|||||| j| j	|
| j
d	 W d   n1 smw   Y  | j| }|d
 }|dur||d< dS dS )z[Similar to self.step, but operates on a single parameter and
        its gradient.
        r   r   r   r   FNTmomentum_bufferr   r   r   r   r   r   has_sparse_gradr   r   )r   append	is_sparser   r   no_gradFsgdr   r   r   )r   r    r!   r   r   r   r   r
   momentum_buffer_listgradsr$   r   r"   r   r   r   
step_param3   sL   









z_FunctionalSGD.step_param	gradientsc                 C   sx  | j d }g }g }g }| jd }| jd }| jd }| jd }	t|t|kr:tddt| d d	t|  d
}
t||D ]7\}}|d urx|| || |jrXd}
|| jvrbi | j|< | j| }d|vrq|d  qA||d  qAt	  t
j|||||||	| j| j|
| jd W d    n1 sw   Y  t|D ]\}}| j| }|| }|d ur||d< qd S )Nr
   r   r   r   r   zEthe gradients passed in does not equal to the size of the parameters!zParams length: z. zGradients length: FTr"   r#   )r   r   r   r   zipr%   r&   r   r   r'   r(   r)   r   r   r   	enumerate)r   r-   r
   params_with_gradr+   r*   r   r   r   r   r$   r    gradientr   ipr"   r   r   r   stepb   sh   











z_FunctionalSGD.stepN)r   r	   r	   r	   FFFF)__name__
__module____qualname__r   r   floatboolr   r   r,   r4   r   r   r   r   r      s<    	

/r   )typingr   r   r   r   torch.optim._functionaloptim_functionalr(   r   r   r   __annotations__r   scriptr   r   r   r   r   <module>   s    