o
    h                     @   sj   U d dl mZ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OptionalTupleN)Tensor__all__c                   @   sh   e Zd Z							ddee dedeeef d	ed
edededefddZdee	e  fddZ
dS )_FunctionalAdamaxMbP?g?g+?:0yE>        Fparamslrbetasepsweight_decayforeachmaximize_allow_empty_param_listc	           	      C   s
  d|kst d| d|kst d| d|d   kr"dk s,n t d|d  d|d   kr8dk sBn t d|d  d|ksMt d	| |||d |d |d
| _|| _|| _tjttjtt	tjf f i | _
t|dkr~|s~t dd|i| _d S )Nr   zInvalid learning rate: zInvalid epsilon value: r   g      ?z#Invalid beta parameter at index 0:    z#Invalid beta parameter at index 1: zInvalid weight_decay value: )r   r   beta1beta2r   z%optimizer got an empty parameter listr   )
ValueErrordefaultsr   r   torchjitannotater   r   strstatelenparam_group)	selfr   r   r   r   r   r   r   r    r"   _/var/www/html/ai/venv/lib/python3.10/site-packages/torch/distributed/optim/functional_adamax.py__init__   s,   $z_FunctionalAdamax.__init__	gradientsc                 C   s  | j d }g }g }g }g }g }t|t|kr*tddt| d dt|  t| j d |D ]V\}}	|	d ur|| ||	 || jvrni | j|< | j| }
td|
d< tj|tj	d|
d	< tj|tj	d|
d
< | j| }
||
d	  ||
d
  ||
d  q2t
 + tj|||||| jd | jd | jd | jd | jd | j| jd W d    d S 1 sw   Y  d S )Nr   zEthe gradients passed in does not equal to the size of the parameters!zParams length: z. zGradients length: r   step)memory_formatexp_avgexp_infr   r   r   r   r   )r   r   r   r   r   r   r   )r    r   r   zipappendr   r   tensor
zeros_likepreserve_formatno_gradFadamaxr   r   r   )r!   r%   r   params_with_gradgradsexp_avgsexp_infsstate_stepsparamgradientr   r"   r"   r#   r&   =   sb   









"z_FunctionalAdamax.stepN)r	   r
   r   r   FFF)__name__
__module____qualname__r   r   floatr   boolr$   r   r&   r"   r"   r"   r#   r      s4    
	
(r   )typingr   r   r   r   r   torch.optim._functionaloptim_functionalr0   r   r   r   __annotations__r   scriptr   r"   r"   r"   r#   <module>   s    