*jpddlmZddlZddlmZmZddlmZeje Z erddl m Z m Z mZmZ ddlmZn #e$rYnwxYw dddZdS)) annotationsN) TYPE_CHECKINGLiteral)save_or_push_to_hub_model) CrossEncoderMultiVectorEncoderSentenceTransformer SparseEncoder)OptimizationConfigFmodelGSentenceTransformer | SparseEncoder | CrossEncoder | MultiVectorEncoderoptimization_config4OptimizationConfig | Literal['O1', 'O2', 'O3', 'O4']model_name_or_pathstr push_to_hubbool create_pr file_suffix str | NonereturnNonec  ddlm}m}ddlm}n#t $rt dwxYw|j} t| |std| |  ttr4|j vrtdpt|dt fd d |||d | dS) a= Export an optimized ONNX model from a SentenceTransformer, SparseEncoder, CrossEncoder, or MultiVectorEncoder model. The O1-O4 optimization levels are defined by Optimum and are documented here: https://huggingface.co/docs/optimum-onnx/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 | MultiVectorEncoder): The SentenceTransformer, SparseEncoder, CrossEncoder, or MultiVectorEncoder 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, CrossEncoder, or MultiVectorEncoder model loaded with `backend="onnx"`. ValueError: If the provided optimization_config is not valid. Returns: None r)ORTModel ORTOptimizer)AutoOptimizationConfigzPlease install Optimum and ONNX Runtime to use this function. You can install them with pip: `pip install sentence-transformers[onnx]` or `pip install sentence-transformers[onnx-gpu]`zThe model must be a Transformer-based SentenceTransformer, SparseEncoder, CrossEncoder, or MultiVectorEncoder model loaded with `backend="onnx"`.z\optimization_config must be an OptimizationConfig instance or one of 'O1', 'O2', 'O3', 'O4'.N optimizedc4|S)N)r)optimize)save_dirrr optimizers TC:\Projects\DSCons\.venv\Lib\site-packages\sentence_transformers\backend\optimize.pyz-export_optimized_onnx_model..as););>>>>>>>LLLLLLL     ?    (I i * *  H   ,,Y77I%s++U &<&D D Dn "8%8 Rg&<>QRRTT! ssssss:"-      s.)FFN)r r rrrrrrrrrrrr) __future__rloggingtypingrr#sentence_transformers.backend.utilsr getLogger__name__loggersentence_transformersrrr r r,r r-r%r$r"r>s""""""))))))))IIIIII  8 $ $ jjjjjjjjjjjj HHHHHHH      " WWWWWWWs?AA