|h'JddlZddlmZddlmZmZmZmZmZddl Z ddl m Z m Z ddgdgdfd e jjd e jd ed ed eedeedeeefddfdZ dd edeedeededededeeeeefdeedeedededdfdZy)N)Path)DictListOptionalTupleUnion) IS_JETSONLOGGERimagesoutput0F torch_modelim onnx_fileopset input_names output_namesdynamicreturnc \tjj|||d|d|||xsd y)ah Export a PyTorch model to ONNX format. Args: torch_model (torch.nn.Module): The PyTorch model to export. im (torch.Tensor): Example input tensor for the model. onnx_file (str): Path to save the exported ONNX file. opset (int): ONNX opset version to use for export. input_names (List[str]): List of input tensor names. output_names (List[str]): List of output tensor names. dynamic (bool | Dict, optional): Whether to enable dynamic axes. Notes: Setting `do_constant_folding=True` may cause issues with DNN inference for torch>=1.12. FTN)verbose opset_versiondo_constant_foldingrr dynamic_axes)torchonnxexport)rrrrrrrs W/var/www/html/test/engine/venv/lib/python3.12/site-packages/ultralytics/utils/export.py export_onnxr s:0 JJ  !_  engine_file workspacehalfint8shapedlametadatarprefixc   ddl |xst|jd} j jj} | r% jj j | _ j| } | j}txsddzt jjddddk\}|r,dkDr'|j jjn dkDr|_dt j"j$z}| j'|}| j(xr|}| j*xr|}t,s t/dt1j2| d d |s |s t/d  j4j6|_t|_|j= j>j@ jC|| }|jE|stGd |tI|jJDcgc]}|jM|}}tI|jNDcgc]}|jQ|}}|D]@}t1j2| d |jRd|jTd|jVB|D]@}t1j2| d|jRd|jTd|jVB|r|ddkrt1jX| d| j[}d|dddf}g|ddfd|ddD}|D]!}|j]|jR|||#|j_||r|ja|t1j2| d|rdnd|rdndzd||r|j= j>jb jdjf|_4G fdd jj}||tmt|jd|_7n'|r%|j= j>jp|r | jrn | jt}|||5}tw|d 5}| `tyjz| }|j}t|jd!d"d#$|j}|j|j}|r|n|jddddddycc}wcc}w#1swYxYw#1swYyxYw)%a8 Export a YOLO model to TensorRT engine format. Args: onnx_file (str): Path to the ONNX file to be converted. engine_file (str, optional): Path to save the generated TensorRT engine file. workspace (int, optional): Workspace size in GB for TensorRT. half (bool, optional): Enable FP16 precision. int8 (bool, optional): Enable INT8 precision. dynamic (bool, optional): Enable dynamic input shapes. shape (Tuple[int, int, int, int], optional): Input shape (batch, channels, height, width). dla (int, optional): DLA core to use (Jetson devices only). dataset (ultralytics.data.build.InfiniteDataLoader, optional): Dataset for INT8 calibration. metadata (Dict, optional): Metadata to include in the engine file. verbose (bool, optional): Enable verbose logging. prefix (str, optional): Prefix for log messages. Raises: ValueError: If DLA is enabled on non-Jetson devices or required precision is not set. RuntimeError: If the ONNX file cannot be parsed. Notes: TensorRT version compatibility is handled for workspace size and engine building. INT8 calibration requires a dataset and generates a calibration cache. Metadata is serialized and written to the engine file if provided. rNz.enginei@. z.DLA is only available on NVIDIA Jetson devicesz enabling DLA on core z...ztDLA requires either 'half=True' (FP16) or 'int8=True' (INT8) to be enabled. Please enable one of them and try again.zfailed to load ONNX file: z input "z " with shape z output "z> 'dynamic=True' model requires max batch size, i.e. 'batch=16' c3VK|] }ttdxsd|z"yw)r/N)intmax).0dr"s r z export_engine..s&"Vq3s1in1'='A#B"Vs&))minoptr2z building INT8FP1632z engine as ceZdZdZ d deddffd ZdWj fdZdefdZ de e efdZ de e fd Zde ddfd Zy) 'export_engine..EngineCalibratora Custom INT8 calibrator for TensorRT engine optimization. This calibrator provides the necessary interface for TensorRT to perform INT8 quantization calibration using a dataset. It handles batch generation, caching, and calibration algorithm selection. Attributes: dataset: Dataset for calibration. data_iter: Iterator over the calibration dataset. algo (trt.CalibrationAlgoType): Calibration algorithm type. batch (int): Batch size for calibration. cache (Path): Path to save the calibration cache. Methods: get_algorithm: Get the calibration algorithm to use. get_batch_size: Get the batch size to use for calibration. get_batch: Get the next batch to use for calibration. read_calibration_cache: Use existing cache instead of calibrating again. write_calibration_cache: Write calibration cache to disk. cacherNcjj|||_t||_j j nj j|_|j|_ t||_ y)z;Initialize the INT8 calibrator with dataset and cache path.N) IInt8Calibrator__init__datasetiter data_iterCalibrationAlgoTypeENTROPY_CALIBRATION_2MINMAX_CALIBRATIONalgo batch_sizebatchrr>)selfrBr>r&trts rrAz0export_engine..EngineCalibrator.__init__ss ##,,T2& !%g++AA00CC %// !%[ r c|jS)z%Get the calibration algorithm to use.)rHrKs r get_algorithmz5export_engine..EngineCalibrator.get_algorithms yy r c"|jxsdS)z*Get the batch size to use for calibration.r+)rJrNs rget_batch_sizez6export_engine..EngineCalibrator.get_batch_sizeszzQ&r c t|jddz }|jjdk(r|j dn|}t |j gS#t$rYywxYw)zOGet the next batch to use for calibration, as a list of device memory pointers.imggo@cpucudaN)nextrDdevicetypetor1data_ptr StopIteration)rKnamesim0ss r get_batchz1export_engine..EngineCalibrator.get_batchse /6>D.2kk.>.>%.G4776?TD 011$  sA A## A/.A/c|jjr4|jjdk(r|jjSyy)zSUse existing cache instead of calibrating again, otherwise, implicitly return None..cacheN)r>existssuffix read_bytesrNs rread_calibration_cachez>export_engine..EngineCalibrator.read_calibration_caches?::$$&4::+<+<+H::0022,I&r c:|jj|}y)z Write calibration cache to disk.N)r> write_bytes)rKr>_s rwrite_calibration_cachez?export_engine..EngineCalibrator.write_calibration_cachesJJ**51r ))__name__ __module__ __qualname____doc__strrArErOr1rQrrr^bytesrdrh)r&rLsrEngineCalibratorr=s| 0  ) )  )" !s'>'> ! ' ' (49*=  3 3  2U 2t 2r rpr`)rBr>wblittleT) byteordersigned)Ctensorrtr with_suffixLoggerINFOSeverityVERBOSE min_severityBuildercreate_builder_configr1 __version__splitset_memory_pool_limitMemoryPoolType WORKSPACEmax_workspace_sizeNetworkDefinitionCreationFlagEXPLICIT_BATCHcreate_networkplatform_has_fast_fp16platform_has_fast_int8r ValueErrorr info DeviceTypeDLAdefault_device_typeDLA_coreset_flag BuilderFlag GPU_FALLBACK OnnxParserparse_from_file RuntimeErrorrange num_inputs get_input num_outputs get_outputnamer%dtypewarningcreate_optimization_profile set_shapeadd_optimization_profileset_calibration_profiler8ProfilingVerbosityDETAILEDprofiling_verbosityr@rnint8_calibratorFP16build_serialized_network build_engineopenjsondumpswritelento_bytesencode serialize)!rr!r"r#r$rr%r&rBr'rr(loggerbuilderconfigis_trt10flagnetworkparseriinputsoutputsinpoutprofile min_shape max_shaperpbuildenginetmetarLs! ` ` @r export_enginer1sPGi!DG &)^^%7%7"c(445^^GV ,F  ! !) ,7 {CDD-2'2D2D,E Fqg" FF F.3G4G4G.HIw!!!$IGIV vhhsxxj SYYKq TUVW vhizcii[#))UVW 8q= NNfX%cd e557a"b) WeBQiW"VERSRTI"VW  QC   chhI5i  P Q''0   * *7 3 KK6(*tVSW9X$YYdepdqrs ,,-%(%;%;%D%D"@ 2s22@ 2F"2d9o11(;<"  ,,-19G , ,g>R>RE w <64 T+Brsa 55 /&Z(k!&"" ""  " c " s) "4: " "N"&#'7 #}<}<#}<}}<  }<  }<  }< c3# $}< #}<tn}<}< }< }