U
    yh                     @   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                   @   sN   e Zd Zdee eeeeeeeeeeeeddd	Zeee  d
ddZ	dS )_FunctionalAdagrad{Gz?              ?绽|=TF)paramslrlr_decayweight_decayinitial_accumulator_valuewarmup_lr_multiplierwarmup_num_itersepscoalesce_gradforeachfusedmaximize_allow_empty_param_listc                 C   s   |||||||d| _ |	| _|
| _|| _|| _tjttj	tt
tj	f f i | _t|dkrj|sjtdd|i| _| jd D ]$}t|j|tdd| j|< q~d S )N)r   r   r   r   r   r   r   r   z%optimizer got an empty parameter listr   r	   )sumstep)defaultsr   r   r   r   torchjitZannotater   r   strstatelen
ValueErrorparam_groupZ	full_likedataZtensor)selfr   r   r   r   r   r   r   r   r   r   r   r   r   p r&   \/var/www/html/venv/lib/python3.8/site-packages/torch/distributed/optim/functional_adagrad.py__init__   s(    	$
z_FunctionalAdagrad.__init__)	gradientsc                 C   s*  | j d }g }g }g }g }t|t|krPtddt| d dt|  d\}}t| j d |D ]b\}	}
|
d k	rh||
jO }|t|	O }||	 ||
 | j|	 }||d  ||d  qht	 L t
j||||| jd	 | jd
 | jd | jd || j| j|| jd d d W 5 Q R X d S )Nr   zEthe gradients passed in does not equal to the size of the parameters!zParams length: z. zGradients length: )FFr   r   r   r   r   r   )r   r   r   r   has_sparse_gradr   r   has_complexr   Z
grad_scaleZ	found_inf)r"   r    r!   zipZ	is_sparser   Z
is_complexappendr   Zno_gradFZadagradr   r   r   r   )r$   r)   r   Zparams_with_gradZgradsZ
state_sumsZstate_stepsr*   r+   paramZgradientr   r&   r&   r'   r   D   sR    





z_FunctionalAdagrad.stepN)r   r	   r	   r	   r
   r	   r   TFFFF)
__name__
__module____qualname__r   r   floatboolr(   r   r   r&   r&   r&   r'   r      s8               .r   )typingr   r   r   r   Ztorch.optim._functionalZoptimZ_functionalr.   r   r   r   __annotations__r   scriptr   r&   r&   r&   r'   <module>   s    