o
    ?߱i                     @   sh   d dl mZ d dlmZ d dlZd dlmZ d dlmZ d dl	m
Z
mZ d dlmZ G dd	 d	eZdS )
    )abstractmethod)OptionalN)ImaginaireModel)ImaginaireTrainer)distributedlog)Callbackc                   @   s   e Zd Z				ddee dededed	df
d
dZ	ddedee	e
jf dee	e
jf de
jded	dfddZedededee	e
jf dee	e
jf de
jded	dfddZdS )EveryNN   TFevery_n	step_sizebarrier_after_runrun_at_startreturnc                 C   s<   || _ | j dkrtd| jj d || _|| _|| _dS )a  Constructor for `EveryN`.

        Args:
            every_n (int): Frequency with which callback is run during training.
            step_size (int): Size of iteration step count. Default 1.
            barrier_after_run (bool): Whether to have a distributed barrier after each execution. Default True, to avoid timeouts.
            run_at_start (bool): Whether to run at the beginning of training. Default False.
        r   zevery_n is set to 0. Callback zp will be invoked only once in the beginning of the training. Calls happens on_training_step_end will be skipped.N)r   r   warning	__class____name__r   r   r   )selfr   r   r   r    r   [/data/cameron/vidgen/cosmos-predict2.5/cosmos_predict2/_src/imaginaire/callbacks/every_n.py__init__   s   

zEveryN.__init__r   model
data_batchoutput_batchloss	iterationc           	      C   s   | j dkrJ| j}|| j }|dkr| jp|| j  dk}|rLtd| jj d|  | |||||| td| jj d|  | j	rNt
  d S d S d S d S )Nr   r
   z	Callback z fired on train_batch_end step z" finished on train_batch_end step )r   trainerr   r   r   debugr   r   every_n_implr   r   barrier)	r   r   r   r   r   r   r   global_step
should_runr   r   r   on_training_step_end5   s   
	
zEveryN.on_training_step_endr   c                 C   s   d S )Nr   )r   r   r   r   r   r   r   r   r   r   r   L   s   	zEveryN.every_n_impl)Nr
   TF)r   )r   
__module____qualname__r   intboolr   r   dictstrtorchTensorr"   r   r   r   r   r   r   r   r	      s\    

r	   )abcr   typingr   r)   %cosmos_predict2._src.imaginaire.modelr   'cosmos_predict2._src.imaginaire.trainerr   %cosmos_predict2._src.imaginaire.utilsr   r   Z.cosmos_predict2._src.imaginaire.utils.callbackr   r	   r   r   r   r   <module>   s   