ChwSSKJr SSKrSSKJrJr SSKJr \R"\ 5r \(aSSK J r J r Jr SSKJr SS Sjjrg!\a N f=f) ) annotationsN) TYPE_CHECKINGLiteral)save_or_push_to_hub_model CrossEncoderSentenceTransformer SparseEncoder)OptimizationConfigc ^^^SSKJnJnJn SSKJn Jn SSKJn [X5=(aA [U5=(a/ [USS5=(a [USRU 5n [X5=(aA [U5=(a/ [USS5=(a [USRU 5n [X5=(a [URU 5nU (dU(dU (d [S5eU (dU (aUSRnO URnU R!U5m[T["5(a7TU R$;a [S5eT=(d Tm['U T5"5mTcS m[)UUU4S jS TUUUTS US9 g ![a [S5ef=f)ao Export an optimized ONNX model from a SentenceTransformer, SparseEncoder, or CrossEncoder model. The O1-O4 optimization levels are defined by Optimum and are documented here: https://huggingface.co/docs/optimum/main/en/onnxruntime/usage_guides/optimization The optimization levels are: - O1: basic general optimizations. - O2: basic and extended general optimizations, transformers-specific fusions. - O3: same as O2 with GELU approximation. - O4: same as O3 with mixed precision (fp16, GPU-only) See the following pages for more information & benchmarks: - `Sentence Transformer > Usage > Speeding up Inference `_ - `Cross Encoder > Usage > Speeding up Inference `_ Args: model (SentenceTransformer | SparseEncoder | CrossEncoder): The SentenceTransformer, SparseEncoder, or CrossEncoder model to be optimized. Must be loaded with `backend="onnx"`. optimization_config (OptimizationConfig | Literal["O1", "O2", "O3", "O4"]): The optimization configuration or level. model_name_or_path (str): The path or Hugging Face Hub repository name where the optimized model will be saved. push_to_hub (bool, optional): Whether to push the optimized model to the Hugging Face Hub. Defaults to False. create_pr (bool, optional): Whether to create a pull request when pushing to the Hugging Face Hub. Defaults to False. file_suffix (str | None, optional): The suffix to add to the optimized model file name. Defaults to None. Raises: ImportError: If the required packages `optimum` and `onnxruntime` are not installed. ValueError: If the provided model is not a valid SentenceTransformer, SparseEncoder, or CrossEncoder model loaded with `backend="onnx"`. ValueError: If the provided optimization_config is not valid. Returns: None rr)ORTModel ORTOptimizer)AutoOptimizationConfigzPlease install Optimum and ONNX Runtime to use this function. You can install them with pip: `pip install optimum[onnxruntime]` or `pip install optimum[onnxruntime-gpu]` auto_modelz}The model must be a Transformer-based SentenceTransformer, SparseEncoder, or CrossEncoder model loaded with `backend="onnx"`.z\optimization_config must be an OptimizationConfig instance or one of 'O1', 'O2', 'O3', 'O4'.N optimizedc&>TRTUTS9$)N) file_suffix)optimize)save_dirroptimization_config optimizers ^/var/www/html/shao/venv/lib/python3.13/site-packages/sentence_transformers/backend/optimize.py-export_optimized_onnx_model..os););L 5. 6 J 6 E!Hl + 6 uQx**H 5  5( 6 J 6 E!Hl + 6 uQx**H 5  !5[*U[[RZ:[O / L  /#Ah11 #kk ,,Y7I%s++ &<&D&D Dn "8%8 %&<>QRT! s:"- W   8   s F//G)FFN)r%z2SentenceTransformer | SparseEncoder | CrossEncoderrz4OptimizationConfig | Literal['O1', 'O2', 'O3', 'O4']r!r/r"boolr#r6rz str | NonereturnNone) __future__rloggingtypingrr#sentence_transformers.backend.utilsr getLogger__name__loggerr&rr r r(r r)rrrrAs")I   8 $VV H" e =eMee e  e  e e    sAA$#A$