Ig ddlmZmZmZmZmZmZmZddlZ ddl m Z m Z ddl mZddlmZmZddlmZddlmZmZdd d d d d didddddddd didddddddd didddd dddd diddgZGddeee j0ZGddeZy) )AnyDictIterableListOptionalSequenceTypeN) ImageInput OnnxProvider)OnnxOutputContext)define_cache_dir normalize)ImageEmbeddingBase)ImageEmbeddingWorkerOnnxImageModelzQdrant/clip-ViT-B-32-visioniz4Image embeddings, Multimodal (text&image), 2021 yearmitg(\?hfz model.onnx)modeldim descriptionlicense size_in_GBsources model_filezQdrant/resnet50-onnxiz-Image embeddings, Unimodal (image), 2016 yearz apache-2.0g?zQdrant/Unicom-ViT-B-16izYImage embeddings (more detailed than Unicom-ViT-B-32), Multimodal (text&image), 2023 yearg= ףp=?zQdrant/Unicom-ViT-B-32z4Image embeddings, Multimodal (text&image), 2023 yeargQ?cxeZdZ ddedeedeedeeededee ededeeffd Z dd Z e d e e eeffd Z dd ededeed eej&fdZe d edfdZde eej&fd e eej&ffdZded eej&fdZxZS)OnnxImageEmbedding model_name cache_dirthreads providerscuda device_ids lazy_load device_idc  t ||||fi| ||_||_||_||_|||_n(|j|jd|_nd|_|j||_t||_ |j|j|j|j|_ |js|jyy)a Args: model_name (str): The name of the model to use. cache_dir (str, optional): The path to the cache directory. Can be set using the `FASTEMBED_CACHE_PATH` env variable. Defaults to `fastembed_cache` in the system's temp directory. threads (int, optional): The number of threads single onnxruntime session can use. Defaults to None. providers (Optional[Sequence[OnnxProvider]], optional): The list of onnxruntime providers to use. Mutually exclusive with the `cuda` and `device_ids` arguments. Defaults to None. cuda (bool, optional): Whether to use cuda for inference. Mutually exclusive with `providers` Defaults to False. device_ids (Optional[List[int]], optional): The list of device ids to use for data parallel processing in workers. Should be used with `cuda=True`, mutually exclusive with `providers`. Defaults to None. lazy_load (bool, optional): Whether to load the model during class initialization or on demand. Should be set to True when using multiple-gpu and parallel encoding. Defaults to False. device_id (Optional[int], optional): The device id to use for loading the model in the worker process. Raises: ValueError: If the model_name is not in the format / e.g. BAAI/bge-base-en. Nr)local_files_only)super__init__r r#r"r!r$_get_model_descriptionmodel_descriptionr rdownload_model_local_files_only _model_dirload_onnx_model) selfrrrr r!r"r#r$kwargs __class__s [/var/www/html/answerous/venv/lib/python3.12/site-packages/fastembed/image/onnx_embedding.pyr(zOnnxImageEmbedding.__init__<sB YB6B""%   &DN __ (!__Q/DN!DN!%! 1, data-parallel encoding will be used, recommended for offline encoding of large datasets. If 0, use all available cores. If None, don't use data-parallel processing, use default onnxruntime threading instead. Returns: List of embeddings, one per document )rrr=r>r?r r!r"N) _embed_imagesrstrrr r!r")r/r=r>r?r0s r2embedzOnnxImageEmbedding.embedsb.&4%%  $..)!nn    sAA$A"A$rctSN)OnnxImageEmbeddingWorkerr:s r2_get_worker_classz$OnnxImageEmbedding._get_worker_classs''r3 onnx_inputc |S)z, Preprocess the onnx input. rA)r/rIr0s r2_preprocess_onnx_inputz)OnnxImageEmbedding._preprocess_onnx_inputs r3outputcft|jjtjSrF)r model_outputastypenpfloat32)r/rLs r2_post_process_onnx_outputz,OnnxImageEmbedding._post_process_onnx_outputs",,-44RZZ@@r3)NNNFNFN)r4N)N)__name__ __module__ __qualname__rCrintrr boolrr(r. classmethodrrr<r rrPndarrayrDr rHrKr rR __classcell__)r1s@r2rr;sk$(!%6:*.#'8#8#C=8## 8# H\23 8#  8#T#Y'8#8#C=8#t  %d4S>&:%%"& ! ! ! 3- ! "**  ! F($'=">((sBJJ/ c2::o A0AAhrzzFZAr3rc eZdZdededefdZy)rGrrr4c td||dd|S)N)rrrrA)r)r/rrr0s r2init_embeddingz'OnnxImageEmbeddingWorker.init_embeddings'! !    r3N)rTrUrVrCrr_rAr3r2rGrGs   K] r3rG)typingrrrrrrr numpyrPfastembed.commonr r fastembed.common.onnx_modelr fastembed.common.utilsr r$fastembed.image.image_embedding_baser fastembed.image.onnx_image_modelrrr9rZrrGrAr3r2rgsFFF59>CQ/M / # (F ( # *r * # *M * # E-`CA+^BJJ-GCAL 3 r3