a
    d$                     @   s   d dl Z d dlZd dlmZmZ d dlmZ d dlmZm	Z	m
Z
mZ d dlZd dlmZ d dlmZ ddlmZ dd	lmZ dd
lmZ ddlmZmZmZmZ eeZee  Z!e"dd e!D Z#eG dd dZ$G dd deZ%G dd deZ&dS )    N)	dataclassfield)Enum)DictListOptionalUnion)FileLock)Dataset   )$MODEL_FOR_QUESTION_ANSWERING_MAPPING)PreTrainedTokenizer)logging   )SquadFeaturesSquadV1ProcessorSquadV2Processor"squad_convert_examples_to_featuresc                 c   s   | ]}|j V  qd S N)
model_type).0conf r   i/var/www/html/stable-diffusion-webui/venv/lib/python3.9/site-packages/transformers/data/datasets/squad.py	<genexpr>"       r   c                   @   s<  e Zd ZU dZedddde idZee	d< edddidZ
ee	d	< ed
ddidZee	d< ed
ddidZee	d< edddidZee	d< edddidZee	d< edddidZee	d< edddidZee	d< edddidZee	d< edddidZee	d< eddd idZee	d!< ed"dd#idZee	d$< dS )%SquadDataTrainingArgumentszb
    Arguments pertaining to what data we are going to input our model for training and eval.
    Nhelpz!Model type selected in the list: z, )defaultmetadatar   zFThe input data dir. Should contain the .json files for the SQuAD task.data_dir   zThe maximum total input sequence length after tokenization. Sequences longer than this will be truncated, sequences shorter will be padded.max_seq_lengthzVWhen splitting up a long document into chunks, how much stride to take between chunks.
doc_stride@   zkThe maximum number of tokens for the question. Questions longer than this will be truncated to this length.max_query_length   zThe maximum length of an answer that can be generated. This is needed because the start and end predictions are not conditioned on one another.max_answer_lengthFz1Overwrite the cached training and evaluation setsoverwrite_cachezDIf true, the SQuAD examples contain some that do not have an answer.version_2_with_negativeg        zIIf null_score - best_non_null is greater than the threshold predict null.null_score_diff_threshold   n_best_sizer   zjlanguage id of input for language-specific xlm models (see tokenization_xlm.PRETRAINED_INIT_CONFIGURATION)lang_id   z3multiple threads for converting example to featuresthreads)__name__
__module____qualname____doc__r   joinMODEL_TYPESr   str__annotations__r    r"   intr#   r%   r'   r(   boolr)   r*   floatr,   r-   r/   r   r   r   r   r   %   s`   
				r   c                   @   s   e Zd ZdZdZdS )SplittraindevN)r0   r1   r2   r<   r=   r   r   r   r   r;   h   s   r;   c                	   @   s   e Zd ZU dZeed< ee ed< eed< e	ed< dej
dddfeeee eeef ee	 ee ee d	d
dZdd Zeeejf dddZdS )SquadDatasetzH
    This will be superseded by a framework-agnostic approach soon.
    argsfeaturesmodeis_language_sensitiveNFpt)r?   	tokenizerlimit_lengthrA   rB   	cache_dirdataset_formatc                 C   s  || _ || _|jrt nt | _t|trRzt| }W n t	yP   t	dY n0 || _
|jrbdnd}tj|d urx|n|jd|j d|jj d|j d| }	|	d }
t|
P tj|	rT|jsTt }t|	| _| jd | _| jdd | _| jd	d | _td
|	 dt |  | jd u s@| jd u rt d|	 d n|tj!krr| j"|j| _n| j#|j| _t$| j||j|j%|j&|tj'k|j(|d\| _| _t }t)| j| j| jd|	 td|	 dt | dd W d    n1 s0    Y  d S )Nzmode is not a valid split nameZv2Zv1Zcached__z.lockr@   datasetexamplesz"Loading features from cached file z [took %.3f s]zDeleting cached file z; will allow dataset and examples to be cached in future run)rJ   rD   r"   r#   r%   Zis_trainingr/   Zreturn_dataset)r@   rI   rJ   z!Saving features into cached file z [took z.3fz s])*r?   rB   r)   r   r   	processor
isinstancer6   r;   KeyErrorrA   ospathr4   r    value	__class__r0   r"   r	   existsr(   timetorchloadZold_featuresr@   getrI   rJ   loggerinfowarningr=   Zget_dev_examplesZget_train_examplesr   r#   r%   r<   r/   save)selfr?   rD   rE   rA   rB   rF   rG   Zversion_tagZcached_features_fileZ	lock_pathstartr   r   r   __init__w   sd    

"
zSquadDataset.__init__c                 C   s
   t | jS r   )lenr@   )r[   r   r   r   __len__   s    zSquadDataset.__len__)returnc                 C   s6  | j | }tj|jtjd}tj|jtjd}tj|jtjd}tj|jtjd}tj|jtj	d}tj|j
tj	d}|||d}	| jjdv r|	d= | jjdv r|	||d | jjr|	d|i | jr|	dtj|jtjd| jj i | jtjkr2tj|jtjd}
tj|jtjd}|	|
|d	 |	S )
N)Zdtype)	input_idsattention_masktoken_type_ids)xlmZrobertaZ
distilbertZ	camembertrc   )Zxlnetrd   )	cls_indexp_maskis_impossibleZlangs)start_positionsend_positions)r@   rT   Ztensorra   longrb   rc   re   rf   r:   rg   r?   r   updater)   rB   Zonesshapeint64r-   rA   r;   r<   Zstart_positionZend_position)r[   ifeaturera   rb   rc   re   rf   rg   inputsrh   ri   r   r   r   __getitem__   s0    
$zSquadDataset.__getitem__)r0   r1   r2   r3   r   r7   r   r   r;   r9   r<   r   r   r8   r   r6   r]   r_   r   rT   ZTensorrq   r   r   r   r   r>   m   s*   

Kr>   )'rN   rS   Zdataclassesr   r   enumr   typingr   r   r   r   rT   Zfilelockr	   Ztorch.utils.datar
   Zmodels.auto.modeling_autor   Ztokenization_utilsr   utilsr   Zprocessors.squadr   r   r   r   Z
get_loggerr0   rW   listkeysZMODEL_CONFIG_CLASSEStupler5   r   r;   r>   r   r   r   r   <module>   s$   
B