bCi HSrSSKJrJr "SS\SS9r"SS\5rS/rg ) z& Image/Text processor class for ALIGN )ProcessingKwargsProcessorMixinc"\rSrSrSSSS.0rSrg)AlignProcessorKwargs text_kwargs max_length@)paddingr N)__name__ __module__ __qualname____firstlineno__ _defaults__static_attributes__r d/home/james-whalen/.local/lib/python3.13/site-packages/transformers/models/align/processing_align.pyrrs # IrrF)totalc@^\rSrSrSrSS/rSrSr\r U4Sjr Sr U=r $) AlignProcessor a Constructs an ALIGN processor which wraps [`EfficientNetImageProcessor`] and [`BertTokenizer`]/[`BertTokenizerFast`] into a single processor that inherits both the image processor and tokenizer functionalities. See the [`~AlignProcessor.__call__`] and [`~OwlViTProcessor.decode`] for more information. The preferred way of passing kwargs is as a dictionary per modality, see usage example below. ```python from transformers import AlignProcessor from PIL import Image model_id = "kakaobrain/align-base" processor = AlignProcessor.from_pretrained(model_id) processor( images=your_pil_image, text=["What is that?"], images_kwargs = {"crop_size": {"height": 224, "width": 224}}, text_kwargs = {"padding": "do_not_pad"}, common_kwargs = {"return_tensors": "pt"}, ) ``` Args: image_processor ([`EfficientNetImageProcessor`]): The image processor is a required input. tokenizer ([`BertTokenizer`, `BertTokenizerFast`]): The tokenizer is a required input. image_processor tokenizerEfficientNetImageProcessor) BertTokenizerBertTokenizerFastc$>[TU]X5 g)N)super__init__)selfrr __class__s rr AlignProcessor.__init__Cs 4rr ) r rrr__doc__ attributesimage_processor_classtokenizer_classrvalid_processor_kwargsr r __classcell__)r"s@rrr s/:$[1J8r,s6A+5$5^$5N  r