ó
    �®žj
  ã                  óœ   • S r SSKJr  SSKJrJr  SSKJr  SSKJ	r	  SSK
Jr  SSKJrJr   " S S	\5      r " S
 S\5      r " S S\\	5      rg)z4Engine option helpers for object-detection runtimes.é    )Úannotations)ÚListÚLiteral)ÚField)ÚKserveV2OptionsMixin)Údefault_compile_model)Ú BaseObjectDetectionEngineOptionsÚObjectDetectionEngineTypec                  ó†   • \ rS rSr% Sr\R                  rS\S'   \	" SSS9r
S\S	'   \	" S
 SS9rS\S'   \	" SSS9rS\S'   Srg)Ú'OnnxRuntimeObjectDetectionEngineOptionsé   z¤Runtime configuration for ONNX Runtime based object-detection models.

Preprocessing parameters come from HuggingFace preprocessor configs,
not from these options.
z.Literal[ObjectDetectionEngineType.ONNXRUNTIME]Úengine_typez
model.onnxz7Filename of the ONNX export inside the model repository©ÚdefaultÚdescriptionÚstrÚmodel_filenamec                 ó   • S/$ )NÚCPUExecutionProvider© r   ó    Ún/home/mande/repo/quber/.venv/lib/python3.13/site-packages/docling/datamodel/object_detection_engine_options.pyÚ<lambda>Ú0OnnxRuntimeObjectDetectionEngineOptions.<lambda>%   s   € Ð!7Ñ 8r   z7Ordered list of ONNX Runtime execution providers to try©Údefault_factoryr   z	List[str]Ú	providerséc   zøONNX Runtime graph optimization level. Accepts onnxruntime.GraphOptimizationLevel int values: 0 (ORT_DISABLE_ALL), 1 (ORT_ENABLE_BASIC), 2 (ORT_ENABLE_EXTENDED), 99 (ORT_ENABLE_ALL). Default enables all optimizations including layout optimizations.ÚintÚgraph_optimization_levelr   N)Ú__name__Ú
__module__Ú__qualname__Ú__firstlineno__Ú__doc__r
   ÚONNXRUNTIMEr   Ú__annotations__r   r   r   r    Ú__static_attributes__r   r   r   r   r      sn   ‡ ñð 	"×-Ñ-ð Ð?ó ñ  ØØMñ€N�Có ñ
 !Ù8ØMñ€Iˆyó ñ
 %*ØðPñ	%Ð˜cö 	r   r   c                  ól   • \ rS rSr% Sr\R                  rS\S'   \	" SSS9r
S\S	'   \	" \S
S9rS\S'   Srg)Ú(TransformersObjectDetectionEngineOptionsé5   zERuntime configuration for Transformers-based object-detection models.z/Literal[ObjectDetectionEngineType.TRANSFORMERS]r   NzJPyTorch dtype for model inference (e.g., 'float32', 'float16', 'bfloat16')r   z
str | NoneÚtorch_dtypezIWhether to compile the model with torch.compile() for better performance.r   ÚboolÚcompile_modelr   )r!   r"   r#   r$   r%   r
   ÚTRANSFORMERSr   r'   r   r,   r   r.   r(   r   r   r   r*   r*   5   sO   ‡ ÙOð 	"×.Ñ.ð Ð@ó ñ $ØØ`ñ€K�ó ñ
  Ø-Ø_ñ€M�4ö r   r*   c                  ó<   • \ rS rSr% Sr\R                  rS\S'   Sr	g)Ú'ApiKserveV2ObjectDetectionEngineOptionséG   z5Runtime configuration for remote KServe v2 inference.z0Literal[ObjectDetectionEngineType.API_KSERVE_V2]r   r   N)
r!   r"   r#   r$   r%   r
   ÚAPI_KSERVE_V2r   r'   r(   r   r   r   r1   r1   G   s    ‡ ñ @ð 	"×/Ñ/ð ÐAö r   r1   N)r%   Ú
__future__r   Útypingr   r   Úpydanticr   Ú#docling.datamodel.kserve_v2_optionsr   Údocling.datamodel.settingsr   Ú6docling.models.inference_engines.object_detection.baser	   r
   r   r*   r1   r   r   r   Ú<module>r:      sI   ðñ ;å "ç  å å DÝ <÷ôÐ.Nô ôBÐ/Oô ô$Ø$Ð&:õr   