Fit\ddlmZddlZddlmZddlmZ d ddZy)) annotationsN)Path)LOGGERc 4ddlm}ddlm}|sJdt |j s Jd||dddl}ddlm} tjd |d |jd d d dd|dt|dtj|xsig } |r| jd|r| j!d| j#| t |j$dz } | j r| j't|S)aConvert an ONNX model to MNN format. Args: onnx_file (str): Path to the source ONNX file. output_file (Path | str): Path to save the exported MNN model. half (bool): Whether to enable FP16 conversion. int8 (bool): Whether to enable INT8 weight quantization. metadata (dict | None): Optional metadata embedded via ``--bizCode``. prefix (str): Prefix for log messages. Returns: (str): Path to the exported ``.mnn`` file. r)check_requirements) TORCH_1_10z>MNN export requires torch>=1.10.0 to avoid segmentation faultszfailed to export ONNX file: z MNN>=2.9.6N) mnnconvert z starting export with MNN z...z-fONNXz --modelFilez --MNNModelz --bizCode)z--weightQuantBits8z--fp16z.__convert_external_data.bin)ultralytics.utils.checksrultralytics.utils.torch_utilsrrexistsMNN MNN.toolsr rinfoversionstrjsondumpsextendappendconvertparentunlink) onnx_file output_filehalfint8metadataprefixrrrr mnn_argsconvert_scratchs ^/var/www/pod-logistic/pod-ai/venv/lib/python3.12/site-packages/ultralytics/utils/export/mnn.pyonnx2mnnr& s*<8 WWW:  ? ! ! #O'CI;%OO #|$$ KK"VH6s{{}oSIJ   K 8>r" H 23 !x ;'..1OOO { )FFNr )rrrz Path | strrboolr r(r!z dict | Noner"rreturnr) __future__rrpathlibrultralytics.utilsrr&r'r%r.sh# $   444 4  4  4  4 4r'