o
     iN$                     @   s  d dl Z d dlZd dlZd dlZd dlmZ d dlmZ d dlm	Z	m
Z
mZ d dlZd dlZd dlmZ d dlmZmZ d dlmZmZ d dlmZ d dlmZ d d	lmZ d d
lmZ d dlm Z m!Z! d dl"m#Z# G dd de$eZ%de$de	fddZ&de j'de	dej(fddZ)dd Z*de
e$ef fddZ+dd Z,	d+de j'de	de-de	e$ef fd d!Z.d"ej/de	e$e0f fd#d$Z1G d%d& d&eZ2d'd( Z3e4d)kre* Z5e56 Z7e7j8re7j9du re5:d*e3e7 dS dS ),    N)Enum)Path)DictTuplecast)FlopCountAnalysisflop_count_str)ModelCheckpointTQDMProgressBar)TensorBoardLogger)DDPStrategy
DataLoader)
LRADataset)
ModelForSCModelForSCDual)ATTENTION_REGISTRYc                   @   s(   e Zd ZdZdZdZdZdZdZdZ	dS )	Task	retrievallistopsimagepathfinder32-curv_baseline"pathfinder32-curv_contour_length_9#pathfinder32-curv_contour_length_14textN)
__name__
__module____qualname__	RetrievalListOpsImagePathfinderBaselinePathfinderContour9PathfinderContour14Text r%   r%   U/home/ubuntu/.local/lib/python3.10/site-packages/xformers/benchmarks/LRA/run_tasks.pyr      s    r   pathreturnc                 C   sd   t t|  d}t|}W d    n1 sw   Y  |d |d< |d |d< |d |d< |S )Nrpathfinder32r   r   r   )openr   absolutejsonload)r'   fileioconfigr%   r%   r&   load_config'   s   r1   argsr0   c                 C   s&  | j }| j}ttj|tjkrt||  |nt||  |}t	
| tjj|}t	
d|jd d  d t L ||  d d d }td| }td| }td| }	t|j|||	f}
t	
dt|
 d	 d
 d t	
t|
 W d    |S 1 sw   Y  |S )Nznum_parameter: g     @@Mmodelcommonseq_len   zcomplexity: g    eA   z GFlops)task	attentionr   plLightningModuler   r   r   r   logginginfo	utilitiesmodel_summaryLayerSummarynum_parameterstorchno_gradrandlongr   r4   roundtotalr   )r2   r0   r9   attention_namer4   summaryr6   xmaskindicesflopsr%   r%   r&   build_model2   s.   

	
 


rO   c               	   C   s   t  } | jdtdtt  dddd | jdtdd	d
 tD  dddd | jdtdddd | jdtdddd | jdtdddt	
d dd | jdtdd | jdd d!dd"d# | jd$d%d&td'd( | jd)d*d+td d( | S ),Nz--attentionz$Attention mechanism to chose, among zI.             A list can be passed to test several mechanisms in sequencer:   T)typehelpdestrequiredz--taskzTask to chose, among c                 S   s   g | ]}|j qS r%   )value).0tr%   r%   r&   
<listcomp>]   s    z"get_arg_parser.<locals>.<listcomp>.r9   z--skip_trainz4Whether to skip training, and test an existing model
skip_trainF)rP   rQ   rR   defaultz--configzPath to the config being usedr0   z./config.jsonz--checkpoint_dirz Path to the checkpoint directorycheckpoint_dirz/checkpoints/USERz	/xformersz--checkpoint_pathzPath to checkpoint)rP   rQ   z--debugz(Make it easier to debug a possible issuedebug
store_true)rQ   rR   rZ   actionz--world_sizezNumber of GPUs used
world_sizer7   )rQ   rR   rP   rZ   z--sweep_parametersz*Rewrite some hyperparameters in the configsweep_parameters)argparseArgumentParseradd_argumentstrlistr   keysr   boolosgetenvintdict)parserr%   r%   r&   get_arg_parserP   s~   rn   c                 C   s6   | d| }t | jd|d}tj|j|}||fS )N__ )save_dirnameversion)r   r[   ri   r'   join	_save_dir)r2   rI   r9   experiment_nameloggerlog_dirr%   r%   r&   	setup_log   s   ry   c                    s.    fdd |  D ]
\}} | || q
| S )Nc                    sd   t |ddkr|| |< d S |dd }|| v sJ ||t |d d  } | | || d S )N:r7   r   )lensplit)config_dictkv	first_keyreplacer%   r&   r      s   zrewrite_hyper.<locals>.replace)items)r0   rewritesr~   r   r%   r   r&   rewrite_hyper   s   	r      config_trainingnum_workersc                    s   i }dD ]}t d| j d| d|d d||< q|d }td|  |d	 | j | td
|d	  d   fdd| D }|S )N)traindevtestz	datasets/rX   z.pickler6   )	file_pathr6   gradient_accumulationzaccumu_steps=
batch_sizezRequested batch size: zQ. Given world            size and grad accumulation, per-gpu batch is            c              
      s$   i | ]\}}|t |d d dqS )FT)r   shuffle
pin_memoryr   r   )rU   r~   r   r   per_gpu_batch_sizer%   r&   
<dictcomp>   s    z%build_dataloaders.<locals>.<dictcomp>)r   r9   r=   r>   r`   warningr   )r2   r   r   datasets	componentaccumu_stepsdataloadersr%   r   r&   build_dataloaders   s&   
r   trainerc                 C   s.   d| j i}| j D ]
\}}| ||< q
|S )Ntrain_step_idx)global_stepcallback_metricsr   item)r   eval_summaryr~   r   r%   r%   r&   get_eval_summary   s   
r   c                       s   e Zd Z fddZ  ZS )BasicProgressBarc                    s   t  ||}|dd  |S )Nv_num)superget_metricspop)selfr   r4   r   	__class__r%   r&   r      s   zBasicProgressBar.get_metrics)r   r   r   r   __classcell__r%   r%   r   r&   r      s    r   c                 C   s  t | | j | j \}}|| _t| j}|| j  }| jd ur*td t	|| j |d }|d d d |d< td|d   t
|dd	 t| |}t| |}t }td
d| jd|d d}	t
jd| jspt| jdnd |d ||	g| jd| j|d ||d t| j |d rdnd|d tt|d  d}
| js|
j||d |d d |	j}n| j}|
j||d |d t|
}tt j!"|dd}td |j#  t$%|| W d    d S 1 sw   Y  d S )!NzReplacing hyperparameterstrainingr4   r5   r6   zLearning rate: learning_rateseedr   val_accumaxz{epoch}-{val_accu:.2f}eval_frequency)monitormodedirpathfilenameevery_n_train_stepsgpu)find_unused_parametersr   Tnum_eval_stepsnum_train_stepsmixed_precision       r   )acceleratorstrategyaccumulate_grad_batches	callbacksdetect_anomalydeterministicgpuslimit_val_batchesrw   	max_stepsnum_sanity_val_steps	precisionval_check_intervalr   )train_dataloadersval_dataloadersr   )r   	ckpt_pathztest_eval_summary.jsonwzSaving test results at )&ry   r:   r9   rw   r1   r0   ra   r=   r>   r   r;   seed_everythinggetr   rO   r   r	   r[   TrainerrY   r   r]   r`   rk   floatr{   fitbest_model_pathcheckpoint_pathr   r   r+   ri   r'   rt   rr   r-   dump)r2   rx   rw   r0   config_taskr   r   r4   progress_barcheckpoint_callbackr   r   r   fr%   r%   r&   	benchmark   st   





"r   __main__z3Must provide --checkpoint_path if --skip_train=True)r   );rb   r-   r=   ri   enumr   pathlibr   typingr   r   r   pytorch_lightningr;   rC   torch.nnnn	fvcore.nnr   r   pytorch_lightning.callbacksr	   r
   pytorch_lightning.loggersr   pytorch_lightning.strategiesr   torch.utils.datar   $xformers.benchmarks.LRA.code.datasetr   *xformers.benchmarks.LRA.code.model_wrapperr   r   xformers.components.attentionr   re   r   r1   	NamespaceModulerO   rn   ry   r   rk   r   r   r   r   r   r   r   rm   
parse_argsr2   rY   r   errorr%   r%   r%   r&   <module>   sX   
C

'G
