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Processor class for LayoutLMv2.
    N)OptionalUnion   )ProcessorMixin)BatchEncodingPaddingStrategyPreTokenizedInput	TextInputTruncationStrategy)
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ee	 ee
 f deee
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 f  deeeee  eeee   f  deeee eee  f  dedeeeef deeeef dee dedee dee dee dedededededeeeef  def&dd Zd!d" Zed#d$ Zed%d& Zed'd( Z  ZS )+LayoutLMv2Processorax  
    Constructs a LayoutLMv2 processor which combines a LayoutLMv2 image processor and a LayoutLMv2 tokenizer into a
    single processor.

    [`LayoutLMv2Processor`] offers all the functionalities you need to prepare data for the model.

    It first uses [`LayoutLMv2ImageProcessor`] to resize document images to a fixed size, and optionally applies OCR to
    get words and normalized bounding boxes. These are then provided to [`LayoutLMv2Tokenizer`] or
    [`LayoutLMv2TokenizerFast`], which turns the words and bounding boxes into token-level `input_ids`,
    `attention_mask`, `token_type_ids`, `bbox`. Optionally, one can provide integer `word_labels`, which are turned
    into token-level `labels` for token classification tasks (such as FUNSD, CORD).

    Args:
        image_processor (`LayoutLMv2ImageProcessor`, *optional*):
            An instance of [`LayoutLMv2ImageProcessor`]. The image processor is a required input.
        tokenizer (`LayoutLMv2Tokenizer` or `LayoutLMv2TokenizerFast`, *optional*):
            An instance of [`LayoutLMv2Tokenizer`] or [`LayoutLMv2TokenizerFast`]. The tokenizer is a required input.
    image_processor	tokenizerLayoutLMv2ImageProcessor)LayoutLMv2TokenizerLayoutLMv2TokenizerFastNc                    sD   d }d|v rt dt |d}|d ur|n|}t || d S )Nfeature_extractorzhThe `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor` instead.)warningswarnFutureWarningpopsuper__init__)selfr   r   kwargsr   	__class__ h/home/ubuntu/.local/lib/python3.10/site-packages/transformers/models/layoutlmv2/processing_layoutlmv2.pyr   3   s   
zLayoutLMv2Processor.__init__TFr   text	text_pairboxesword_labelsadd_special_tokenspadding
truncation
max_lengthstridepad_to_multiple_ofreturn_token_type_idsreturn_attention_maskreturn_overflowing_tokensreturn_special_tokens_maskreturn_offsets_mappingreturn_lengthverbosereturn_tensorsreturnc                 K   s\  | j jr|durtd| j jr|durtd|du r$|du r$td| j ||d}|durC| j jrC|du rCt|tr?|g}|d }| jdi d	|durN|n|d d
|durY|ndd|durb|n|d d|d|d|d|d|	d|
d|d|d|d|d|d|d|d|d||}|d}|du r| ||d }||d< |S )a  
        This method first forwards the `images` argument to [`~LayoutLMv2ImageProcessor.__call__`]. In case
        [`LayoutLMv2ImageProcessor`] was initialized with `apply_ocr` set to `True`, it passes the obtained words and
        bounding boxes along with the additional arguments to [`~LayoutLMv2Tokenizer.__call__`] and returns the output,
        together with resized `images`. In case [`LayoutLMv2ImageProcessor`] was initialized with `apply_ocr` set to
        `False`, it passes the words (`text`/``text_pair`) and `boxes` specified by the user along with the additional
        arguments to [`~LayoutLMv2Tokenizer.__call__`] and returns the output, together with resized `images``.

        Please refer to the docstring of the above two methods for more information.
        NzdYou cannot provide bounding boxes if you initialized the image processor with apply_ocr set to True.zaYou cannot provide word labels if you initialized the image processor with apply_ocr set to True.TFzKYou cannot return overflowing tokens without returning the offsets mapping.)imagesr0   wordsr   r    r!   r"   r#   r$   r%   r&   r'   r(   r)   r*   r+   r,   r-   r.   r/   r0   pixel_valuesoverflow_to_sample_mappingimager   )r   	apply_ocr
ValueError
isinstancestrr   r   get_overflowing_images)r   r2   r   r    r!   r"   r#   r$   r%   r&   r'   r(   r)   r*   r+   r,   r-   r.   r/   r0   r   featuresencoded_inputsr   r   r   __call__A   sz   "

	

zLayoutLMv2Processor.__call__c                 C   sL   g }|D ]	}| ||  qt|t|kr$tdt| dt| |S )Nz`Expected length of images to be the same as the length of `overflow_to_sample_mapping`, but got z and )appendlenr8   )r   r2   r5   images_with_overflow
sample_idxr   r   r   r;      s   z*LayoutLMv2Processor.get_overflowing_imagesc                 C   s   g dS )N)	input_idsbboxtoken_type_idsattention_maskr6   r   r   r   r   r   model_input_names   s   z%LayoutLMv2Processor.model_input_namesc                 C      t dt | jS )Nzg`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead.)r   r   r   image_processor_classrG   r   r   r   feature_extractor_class   
   z+LayoutLMv2Processor.feature_extractor_classc                 C   rI   )Nz[`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead.)r   r   r   r   rG   r   r   r   r      rL   z%LayoutLMv2Processor.feature_extractor)NN)NNNNTFFNr   NNNFFFFTN)__name__
__module____qualname____doc__
attributesrJ   tokenizer_classr   r   r	   r   listr   intboolr:   r   r
   r   r   r>   r;   propertyrH   rK   r   __classcell__r   r   r   r   r      s    "	

V

r   )rP   r   typingr   r   processing_utilsr   tokenization_utils_baser   r   r   r	   r
   utilsr   r   __all__r   r   r   r   <module>   s    
 