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    cQêjÚ  ã                   óD   — d dl Z d dlZd dlZd dlZd„ Zedk(  r e«        yy)é    Nc                  ó  — t        j                  t        j                  j	                  t
        «      d¬«      } | j                  dt        j                  d¬«       | j                  dt        j                  d¬«       | j                  «       }t        j                  t        |j                  j                  d¬	«      «      «      }t        d
«       t        j                   |t        |j"                  j                  «       «      «       y )Nz^Update a QDQ format ONNX model to ensure optimal performance when executed using ONNX Runtime.)ÚdescriptionÚinput_modelz%Provide path to ONNX model to update.)ÚtypeÚhelpÚoutput_modelz,Provide path to write updated ONNX model to.T)ÚstrictzfAs of ORT 1.15, the fixing up of DQ nodes with multiple consumers is done by an ORT graph transformer.)ÚargparseÚArgumentParserÚosÚpathÚbasenameÚ__file__Úadd_argumentÚpathlibÚPathÚ
parse_argsÚonnxÚloadÚstrr   ÚresolveÚprintÚsaver   )ÚparserÚargsÚmodels      úu/home/oem/CyberBrain26-unified/.venv/lib/python3.12/site-packages/onnxruntime/tools/qdq_helpers/optimize_qdq_model.pyÚoptimize_qdq_modelr      sÁ   € Ü×$Ñ$Ü
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rÔsô 	‡I�Iˆe”S˜×*Ñ*×2Ñ2Ó4Ó5Õ6ó    Ú__main__)r
   r   r   r   r   Ú__name__© r   r   ú<module>r#      s-   ðó
 Û 	Û ã ò7ð0 ˆzÒÙÕð r   